Add the PROTAC release

Mirrors the CupOFMoCA-PDC layout: checkpoints/, configs/paper.json with the
reported sampling settings, docs/artifacts.json verified by
scripts/verify_release.py, and the generation outputs behind the reported
tables under results/.

DegradeMaster and EGFR-PROPK are published upstream without a license and are
not redistributed; scripts/fetch_third_party.py retrieves them at the pinned
commits. The unlicensed, unused ORCA C++ sources bundled with DeFoG are
excluded. DeFoG itself is MIT, with its license at src/defog/LICENSE.

CupOFMoCA-PROTAC/CITATION.cff

@@ -0,0 +1,30 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite the CupOFMoCA paper."
+title: "CupOFMoCA: Coupled Objective-Guided Discrete Flows for Molecular Conjugate Assembly"
+type: software
+authors:
+  - family-names: Zhang
+    given-names: Ruoxi Rosie
+  - family-names: Li
+    given-names: Ziang
+  - family-names: Gu
+    given-names: Jiatao
+  - family-names: Chatterjee
+    given-names: Pranam
+license: Apache-2.0
+repository-code: "https://huggingface.co/ChatterjeeLab/CupOFMoCA"
+preferred-citation:
+  type: conference-paper
+  title: "CupOFMoCA: Coupled Objective-Guided Discrete Flows for Molecular Conjugate Assembly"
+  authors:
+    - family-names: Zhang
+      given-names: Ruoxi Rosie
+    - family-names: Li
+      given-names: Ziang
+    - family-names: Gu
+      given-names: Jiatao
+    - family-names: Chatterjee
+      given-names: Pranam
+  collection-title: "Advances in Neural Information Processing Systems"
+  year: 2026
+

CupOFMoCA-PROTAC/LICENSE

@@ -0,0 +1,17 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   Copyright 2026 Anonymous Authors (CupOfMoca ICLR Submission)
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

CupOFMoCA-PROTAC/NOTICE

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+CupOFMoCA — PROTAC release
+Copyright 2026 CupOFMoCA authors
+
+The first-party code in this release is licensed under Apache License 2.0; see
+LICENSE. Model weights and third-party downloads are subject to their own terms,
+which users are responsible for reviewing.
+
+Redistributed third-party code
+------------------------------
+
+src/defog/
+    DeFoG, https://github.com/manuelmlmadeira/DeFoG
+    MIT License, reproduced at src/defog/LICENSE.
+    src/defog/src/datasets/protac_dataset.py is a first-party addition.
+    The upstream graph-benchmark evaluation helpers under
+    src/defog/src/analysis/orca/ are NOT redistributed: that C++ code carries no
+    license header and is unused by the PROTAC pipeline.
+
+Third-party code that is NOT redistributed
+------------------------------------------
+
+Two optional components are published by their authors without any license
+file, so this release cannot lawfully redistribute them. Run
+`python scripts/fetch_third_party.py` to obtain them from their upstream
+repositories at the commits used for the paper, and review the upstream terms
+before use.
+
+    DegradeMaster  https://github.com/ABILiLab/DegradeMaster
+                   pinned commit aa149beaf067a051e070b3b281f7dba43c2f3e90
+                   Needed only for predicted-degradation scoring.
+
+    EGFR-PROPK     https://github.com/Zhang-Ran-0119/EGFR-PROPK
+                   pinned commit 6940cb90c449e6c6d0678508fc2f228da796e028
+                   Needed only for the EGFR-only PK columns of batch_report.py.
+
+Linker generation with scripts/generate.py does not require either component.
+
+Derived data
+------------
+
+The PROTAC-DB derived tables (data/linker.csv) and the target and E3 pocket
+graphs used for degradation scoring were prepared by the CupOFMoCA authors from
+publicly available sources: PROTAC-DB (Weng et al., Nucleic Acids Research 2021)
+and the RCSB Protein Data Bank. The fine-tuned generator checkpoint under
+checkpoints/ is a derivative of the released DeFoG GuacaMol checkpoint and
+inherits its MIT terms.

CupOFMoCA-PROTAC/README.md

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+# CupOFMoCA — PROTAC
+
+Code and PROTAC model artifacts for **CupOFMoCA: Coupled Objective-Guided Discrete Flows for
+Molecular Conjugate Assembly** (NeurIPS 2026).
+
+This release supports the paper's PROTAC experiments: linker generation between a fixed
+warhead and a fixed E3 ligand, under hard assembly-validity constraints and objective
+guidance. For the peptide-drug conjugate half, see [`CupOFMoCA-PDC/`](../CupOFMoCA-PDC).
+
+## Model overview
+
+The generator is a DeFoG discrete flow-matching model over molecular graphs, fine-tuned on
+PROTAC-DB linkers. The warhead and E3-ligand subgraphs are held fixed throughout sampling;
+only the linker subgraph is edited.
+
+| Checkpoint | Role |
+|---|---|
+| `checkpoints/protac_linker_finetune/epoch=99-v1.ckpt` | DeFoG graph discrete-flow generator, fine-tuned for 100 epochs on 2,070 PROTAC-DB linker graphs |
+| `src/classifier/protac_linker_clf.pkl` | generic linker validity/quality classifier |
+| `src/classifier/protac_linker_clf_{ErlotinibVHL,BRD9VHL,CDK6CRBN}.pkl` | target-specific classifiers, auto-selected by `--protac_module` |
+
+The checkpoint is loaded by this repository's own PyTorch code. This is not a Transformers
+pipeline and provides no hosted-inference widget.
+
+## Quickstart
+
+```bash
+hf download ChatterjeeLab/CupOFMoCA --include "CupOFMoCA-PROTAC/*" --local-dir .
+cd CupOFMoCA-PROTAC
+conda env create -f environment.yml && conda activate defog
+pip install -e src/defog
+python scripts/verify_release.py
+```
+
+Generate 100 EGFR-VHL PROTACs with the reported configuration (one of three seeds):
+
+```bash
+cd scripts
+python generate.py \
+  --checkpoint ../checkpoints/protac_linker_finetune/epoch=99-v1.ckpt \
+  --protac_module ErlotinibVHL --fix_termini cooh --fast_scoring \
+  --num_samples 100 --num_batches 1 --num_steps 1500 --warmup_steps 100 \
+  --weights 4.0 2.0 4.0 --seed 42 \
+  --output_file ./protac_linkers_egfrvhl.smi --output_dir ../generation_logs
+```
+
+Swap `--protac_module` for `BRD9VHL` or `CDK6CRBN` for the other two systems. Every
+setting above is recorded in `configs/paper.json`.
+
+`--weights` is positional over the three soft scorers: synthetic accessibility,
+PROTAC-DB chemotype closeness, connectivity. The validity classifier is applied as a hard
+mask and takes no weight.
+
+### Intended uses
+
+- Reproduce and inspect the paper's PROTAC generation experiments.
+- Generate computational PROTAC linker candidates for research and method development.
+- Extend or compare constrained, multi-objective molecular-generation methods.
+
+The release is not intended for clinical decisions, direct therapeutic use, or as a
+substitute for chemical synthesis, experimental validation, toxicology, or safety
+assessment.
+
+### Training data
+
+The generator is the released DeFoG GuacaMol checkpoint fine-tuned on 2,070 PROTAC-DB
+linker graphs (258 validation, 260 test). `data/linker.csv` is the derived linker table.
+Architecture, optimization and scorer details are in Appendix H of the paper. Training
+datasets are not redistributed beyond that derived table.
+
+### Evaluation
+
+The paper evaluates generated PROTACs on EGFR-VHL, BRD9-VHL and CDK6-CRBN for standard
+and assembly validity, predicted degradation, diversity and training-set similarity. The
+runs behind those tables are in `results/`, documented in `results/README.md`. Predicted
+degradation requires DegradeMaster, which is fetched rather than redistributed — see below.
+
+### Limitations
+
+- Outputs and objective values are computational predictions, not experimentally validated
+  compounds or guarantees of efficacy, synthesizability, toxicity or safety.
+- The released configurations cover three target/E3 systems with fixed anchor chemistry;
+  performance outside this scope has not been established.
+- Predicted degradation comes from a model trained on overlapping PROTAC databases, so it
+  is an in-domain evaluation rather than an independent one.
+- `scripts/runs/ablation_egfr.py` sweeps five weight slots, but the current `generate.py`
+  exposes three; the Morgan-fingerprint row of the weight ablation is documented by the
+  archived outputs in `results/` rather than re-runnable as-is.
+- Results can vary with hardware and CUDA/PyTorch versions.
+
+## Repository layout
+
+```text
+checkpoints/              generator weights
+configs/paper.json        the settings used for the reported runs
+data/linker.csv           PROTAC-DB derived linker table
+docs/                     artifact manifest (ARTIFACTS.md, artifacts.json)
+md/                       explicit-solvent molecular dynamics pipeline
+results/                  generation outputs behind the reported tables
+scripts/                  generate.py, batch_report.py, evaluate_linkers.py,
+                          fetch_third_party.py, verify_release.py, runs/
+src/protac/               per-target warhead + E3 builders
+src/classifier/           validity gate, analyzer, classifiers
+src/defog/                DeFoG discrete flow model (MIT, see src/defog/LICENSE)
+```
+
+## Third-party components
+
+DeFoG is redistributed here under MIT. Two optional components — DegradeMaster
+(degradation scoring) and EGFR-PROPK (EGFR-only PK columns) — are published upstream
+without a license and so are **not** redistributed. Fetch them at the pinned commits used
+for the paper:
+
+```bash
+python scripts/fetch_third_party.py
+```
+
+Linker generation does not require either. See `NOTICE` for the full statement.
+
+## Citation
+
+See `CITATION.cff`.

CupOFMoCA-PROTAC/checkpoints/protac_linker_finetune/epoch=99-v1.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8cfb48d9f5b3bcabb28c4dce7548e1a792494c48f05150a1b262b5215c1da78f
+size 255211895

CupOFMoCA-PROTAC/configs/paper.json

@@ -0,0 +1,45 @@
+{
+  "default_seeds": [
+    42,
+    123,
+    456
+  ],
+  "num_candidates_per_seed": 100,
+  "num_batches": 1,
+  "num_steps": 1500,
+  "warmup_steps": 100,
+  "guidance_strength_beta": 5.0,
+  "top_k": 50,
+  "temperature": 1.0,
+  "position_sampling": "weighted",
+  "use_acceptance": false,
+  "fix_termini": "cooh",
+  "fast_scoring": true,
+  "weights": {
+    "synthetic_accessibility": 4.0,
+    "chemotype_closeness": 2.0,
+    "connectivity": 4.0
+  },
+  "weights_positional": [
+    4.0,
+    2.0,
+    4.0
+  ],
+  "targets": {
+    "EGFR-VHL": {
+      "protac_module": "ErlotinibVHL",
+      "warhead": "gefitinib-piperazine (MS39)",
+      "e3": "VH032"
+    },
+    "BRD9-VHL": {
+      "protac_module": "BRD9VHL",
+      "warhead": "BI-7273-piperazine",
+      "e3": "VH032"
+    },
+    "CDK6-CRBN": {
+      "protac_module": "CDK6CRBN",
+      "warhead": "palbociclib-piperazine",
+      "e3": "pomalidomide"
+    }
+  }
+}

CupOFMoCA-PROTAC/docs/ARTIFACTS.md

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+# Model artifacts
+
+Every local artifact the PROTAC pipeline loads. Run `python scripts/verify_release.py`
+to check byte counts, SHA-256 hashes and private-path hygiene. The machine-readable
+manifest is `docs/artifacts.json`.
+
+| Artifact | Purpose | Size | SHA-256 |
+|---|---|---:|---|
+| `checkpoints/protac_linker_finetune/epoch=99-v1.ckpt` | DeFoG generator, fine-tuned on PROTAC-DB linkers | 255,211,895 B | `8cfb48d9f5b3bcabb28c4dce7548e1a792494c48f05150a1b262b5215c1da78f` |
+| `src/classifier/protac_linker_clf.pkl` | linker classifier (generic) | 128,117 B | `fa667025962d132ce9f2ebf8f2dc49752416ed154792ca0c87344335fa714462` |
+| `src/classifier/protac_linker_clf_BRD9VHL.pkl` | linker classifier (BRD9VHL) | 28,117 B | `eae385be1576fec674b8a537e50b56e1ab1fc47599a82ae277912d958c0b7d6f` |
+| `src/classifier/protac_linker_clf_CDK6CRBN.pkl` | linker classifier (CDK6CRBN) | 30,035 B | `85bd40599d82c5cc8a35cc844d12d1066a0d4699bcc7e229937e1fe1d3daad3d` |
+| `src/classifier/protac_linker_clf_ErlotinibVHL.pkl` | linker classifier (ErlotinibVHL) | 26,397 B | `e031d310829c7d196887e2fd077eff95be445ed1984516540ac69308c26384ee` |
+| `src/classifier/protac_linker_clf_amine.pkl` | linker classifier (amine) | 76,524 B | `e0e851f41a004ea26e3b66caef83bf6ab4fa2229447427ab996e8a195c0df2d2` |
+| `src/classifier/protac_linker_clf_amino_acid.pkl` | linker classifier (amino_acid) | 188,080 B | `2558addea35da16ddf82affaf68ea9046bc5b9b3d307f6ee668c117df2798428` |
+| `src/degrademaster/data/case_study/arcrbn_pocket_graph.pt` | ARCRBN pocket graph | 35,405 B | `98f70b82b731760b2b25b9ae0e7b1a917a88fd215f2ba4e61cf1654207d137e3` |
+| `src/degrademaster/data/case_study/brd4_pocket_graph.pt` | BRD4 pocket graph | 15,675 B | `8dbda805c329bc5804d95983acaf4260e712bfa8fefcc5f39d76b4d2cd3583b9` |
+| `src/degrademaster/data/case_study/brd9_pocket_graph.pt` | BRD9 pocket graph | 201,019 B | `89346178dfdc8fd277c57d08293a903133a263b1206184224cf250f71ad8f3a0` |
+| `src/degrademaster/data/case_study/cdk6crbn_pocket_graph.pt` | CDK6CRBN pocket graph | 32,607 B | `0193874c2150e40a2e8c7a6b4eddf1c9b1768ac0573716b0fbf79e365de62310` |
+| `src/degrademaster/data/case_study/crbn_pocket_graph.pt` | CRBN pocket graph | 25,467 B | `6e4e8e6756a343379118150370061f1b781d36f1bc681693d6d7fd8a8d0bce12` |
+| `src/degrademaster/data/case_study/egfr_pocket_graph.pt` | EGFR pocket graph | 32,602 B | `5d86cd0d80363bab3c2835aefa817181cd96b2e0c14b35c55e384cf8e9dc64c1` |
+| `src/degrademaster/data/case_study/krasvhl_pocket_graph.pt` | KRASVHL pocket graph | 25,686 B | `79efc62c546142277c6cba995d7926ca0dc3b600c2e98cce766519054243284c` |
+| `src/degrademaster/data/case_study/processed/ligase_pocket.pt` | VHL E3 pocket graph (collated) | 419,524 B | `3b35bb97bddce48ccc5ebddbdb435a98654b94f569441cf6f8bc66e3a11e4d38` |
+| `src/degrademaster/data/case_study/arcrbn_target_feature.npy` | 30-d feature vector | 368 B | `9ef6c2c04f54c6585cdac4e3d0ffb38c15ba7d1912a29f25f6a4967c7e13799e` |
+| `src/degrademaster/data/case_study/brd4_target_feature.npy` | 30-d feature vector | 368 B | `28a1903da353ff6a92c4d4b8828e66e7264bcd4f07a27329d2f898cf000f63e4` |
+| `src/degrademaster/data/case_study/brd4crbn_target_feature.npy` | 30-d feature vector | 368 B | `28a1903da353ff6a92c4d4b8828e66e7264bcd4f07a27329d2f898cf000f63e4` |
+| `src/degrademaster/data/case_study/brd9_target_feature.npy` | 30-d feature vector | 368 B | `dbe5d7e51907b44396a891a574010544f9e7461c09618d940fe26ddf59ef8473` |
+| `src/degrademaster/data/case_study/cdk6crbn_target_feature.npy` | 30-d feature vector | 368 B | `4da1adf39d018d61cd80a67f5950eaf734b425b69690a157c392d792b020712a` |
+| `src/degrademaster/data/case_study/crbn_e3_feature.npy` | 30-d feature vector | 368 B | `71f830577fd901b6be42b9bb8f02f12e25245aefafac709d0b68910dfa8214db` |
+| `src/degrademaster/data/case_study/egfr_target_feature.npy` | 30-d feature vector | 368 B | `c31f02bfeb6ce63b0fcf41a7b235556dc2b76ab6054626116c08434a29b639de` |
+| `src/degrademaster/data/case_study/krasvhl_target_feature.npy` | 30-d feature vector | 368 B | `51d50af89f905b6a4eb1f1d2b90d9ca8a2ee7e7dbace16fdab56e159f2c0385f` |
+| `src/degrademaster/data/case_study/vhl_e3_feature_egfr.npy` | 30-d feature vector | 368 B | `aca7d4ba3f95a2d903e542f761c3d448323d7ff8a9e1d58e58d9b8bd55d0a74a` |
+| `src/degrademaster/data/PROTAC/name.json` | PROTAC-DB entry table (property windows, similarity) | 3,419,093 B | `bbe5ffe734f416ecf153f4ab42a17c6a3a86a79cfcb0faa5a5f13a672733d575` |
+| `data/linker.csv` | PROTAC-DB derived linker table | 703,569 B | `73e4be1680fe9e2e2cf7256ff3fa9423a9a7e480d9b1baa529081a2bc89ac5b1` |
+
+DegradeMaster and EGFR-PROPK are published upstream without a license and are therefore
+not redistributed; `python scripts/fetch_third_party.py` retrieves them at the commits
+used for the paper. Their absence is reported, not failed, by the verifier.
+
+The ORCA graphlet-counting C++ sources bundled with upstream DeFoG are excluded: they
+carry no license header and are unused by the PROTAC pipeline.
+

CupOFMoCA-PROTAC/docs/artifacts.json

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+    "sha256": "4da1adf39d018d61cd80a67f5950eaf734b425b69690a157c392d792b020712a"
+  },
+  {
+    "path": "src/degrademaster/data/case_study/crbn_e3_feature.npy",
+    "bytes": 368,
+    "sha256": "71f830577fd901b6be42b9bb8f02f12e25245aefafac709d0b68910dfa8214db"
+  },
+  {
+    "path": "src/degrademaster/data/case_study/egfr_target_feature.npy",
+    "bytes": 368,
+    "sha256": "c31f02bfeb6ce63b0fcf41a7b235556dc2b76ab6054626116c08434a29b639de"
+  },
+  {
+    "path": "src/degrademaster/data/case_study/krasvhl_target_feature.npy",
+    "bytes": 368,
+    "sha256": "51d50af89f905b6a4eb1f1d2b90d9ca8a2ee7e7dbace16fdab56e159f2c0385f"
+  },
+  {
+    "path": "src/degrademaster/data/case_study/vhl_e3_feature_egfr.npy",
+    "bytes": 368,
+    "sha256": "aca7d4ba3f95a2d903e542f761c3d448323d7ff8a9e1d58e58d9b8bd55d0a74a"
+  },
+  {
+    "path": "src/degrademaster/data/PROTAC/name.json",
+    "bytes": 3419093,
+    "sha256": "bbe5ffe734f416ecf153f4ab42a17c6a3a86a79cfcb0faa5a5f13a672733d575"
+  },
+  {
+    "path": "data/linker.csv",
+    "bytes": 703569,
+    "sha256": "73e4be1680fe9e2e2cf7256ff3fa9423a9a7e480d9b1baa529081a2bc89ac5b1"
+  }
+]

CupOFMoCA-PROTAC/environment.yml

@@ -0,0 +1,36 @@
+name: defog
+channels:
+  - conda-forge
+  - nvidia
+  - pytorch
+dependencies:
+  - python=3.9
+  - rdkit=2023.03.2
+  - graph-tool=2.45
+  - pytorch==2.4.0 
+  - pytorch-cuda=12.1  
+  - psi4=1.9.1
+  - pip=24.2
+  - pip:
+      - ipykernel==6.29.5
+      - hydra-core==1.3.2
+      - imageio==2.31.1
+      - matplotlib==3.7.1
+      - networkx==2.8.7
+      - numpy==1.23
+      - omegaconf==2.3.0
+      - overrides==7.3.1
+      - pandas==1.4
+      - pyemd==1.0.0
+      - PyGSP==0.5.1
+      - pytorch_lightning==2.0.4
+      - scipy==1.11.0
+      - setuptools==68.0.0
+      - torch_geometric==2.3.1
+      - torchmetrics==0.11.4
+      - tqdm==4.65.0
+      - wandb==0.15.4
+      - seaborn==0.13.2
+      - gpustat==0.6.0
+      - black==24.3.0
+      - -e .

CupOFMoCA-PROTAC/md/README.md

@@ -0,0 +1,172 @@
+# Free-PROTAC molecular dynamics
+
+Explicit-solvent MD of a generated PROTAC on its own, with no target protein and
+no E3 ligase. Runs in chloroform (a membrane-interior mimic) and in water, and
+measures the conformational descriptors published work ties to cell
+permeability: radius of gyration, 3D polar surface area, intramolecular
+H-bonds, and conformational state populations.
+
+The protocol follows "Linker-Dependent Folding Rationalizes PROTAC Cell
+Permeability" (*J. Med. Chem.* 2022, DOI 10.1021/acs.jmedchem.2c00877) and takes
+its permeability cutoffs from Atilaw et al., *ACS Med. Chem. Lett.* 2021, 12,
+107-114. `reference_protocol.md` has the settings and the target numbers.
+
+## Layout
+
+```
+protac_md.py               MD driver: conformer -> parametrize -> solvate -> replicas
+analyze_conformations.py   Rg / RMSD / 3D PSA / H-bonds / clustering dashboard
+rg_basins.py               Rg free-energy profiles and basin populations
+psa_ensemble.py            3D PSA over a finished ensemble
+ternary_span.py            warhead-to-E3 span distribution (water ensembles)
+validate_psa.py            PSA code path checked against grazoprevir
+psa_method_probe.py        element vs charge-threshold polar-atom selection
+plot_results.py            per-replica summary figure
+render_3d.py               extended and collapsed conformations from a trajectory
+run_candidate.sh           detached driver: chloroform + water + analysis
+environment_md.yml         conda environment
+protacmd-lock-linux64.txt  pinned environment, linux-64
+reference_protocol.md      reference protocol and permeability yardsticks
+linker_design.md           linker rules read off this project's own MD runs
+```
+
+PROTAC SMILES are embedded in `protac_md.py` (`CANDIDATES`), so no input files
+are needed; anything else runs through `--smiles`.
+
+## Environment
+
+On linux-64 with a CUDA 12 capable driver (525 or newer), use the lockfile and
+skip dependency solving:
+
+```
+conda create --name protacmd --file protacmd-lock-linux64.txt
+conda activate protacmd
+pip install "setuptools<81"
+```
+
+That reproduces the environment: openmm 8.5.2, ambertools 24.8,
+rdkit 2025.09.5, openff-toolkit 0.16.10, python 3.10.20. The lockfile carries no
+`packmol`, which `--solvent chloroform` needs, so add it afterwards
+(`conda install -c conda-forge packmol`) or solve from the yml instead.
+
+Elsewhere, solve from the yml. Check the driver's CUDA version with
+`nvidia-smi` first and edit `cuda-version` in `environment_md.yml` to match
+(remove it entirely for CPU-only):
+
+```
+conda env create -f environment_md.yml
+conda activate protacmd
+```
+
+The solve takes around ten minutes: ambertools has a large dependency tree and
+libmamba is single-threaded, so the spinner sits still while one core works. The
+install itself takes seconds. Keep `setuptools<81` in the `pip:` section rather
+than as a conda dependency; an upper bound on setuptools triples the solve time.
+
+Activation is not optional. `sqm`, `antechamber` and `packmol` are only on PATH
+inside the env, and calling `<env>/bin/python` directly is not enough.
+
+## Run
+
+```
+conda activate protacmd
+
+# chloroform: the membrane mimic, the permeability-relevant run
+python protac_md.py --solvent chloroform --replicas 3 --prod-ns 50 --gpu 0
+# water: the polar reference; the pair shows chameleonic folding
+python protac_md.py --solvent water      --replicas 3 --prod-ns 50 --gpu 0
+
+python analyze_conformations.py --dir egfrvhl_rank4/chloroform --name egfrvhl_rank4
+python analyze_conformations.py --dir egfrvhl_rank4/water      --name egfrvhl_rank4
+```
+
+Useful flags: `--candidate {egfrvhl_rank4,egfrvhl_rank5,brd9vhl_rank1,cdk6crbn_rank2}`,
+`--smiles "<custom>"` with `--name ms39_ref` for a reference compound,
+`--platform CPU`, `--prod-ns`, `--replicas`, `--gpu N`.
+
+Output lands in `<name>/<solvent>/rep<k>/` (`*_prod.dcd`, `*_prod.csv`, PDBs),
+with the dashboard and the cluster centroid PDBs in `<name>/<solvent>/`.
+
+`run_candidate.sh` chains both solvents and both analyses for one candidate and
+reuses the chloroform charge cache for water, so AM1-BCC is paid once.
+
+Smoke test on a new machine first, about two minutes:
+
+```
+python protac_md.py --solvent chloroform --replicas 1 --prod-ns 0.05 \
+  --heat-ps 5 --equil-ps 10 --report-ps 1 --min-iters 1000 --name smoke
+python analyze_conformations.py --dir smoke/chloroform --name smoke --clusters 4
+```
+
+## Comparing finished runs
+
+These take run directories, one per compound. `ms39_ref` is not bundled: run the
+pipeline on MS39 yourself with `--smiles ... --name ms39_ref`. Its components
+and exact linker are in `../src/protac/ErlotinibVHL.py`.
+
+```
+python rg_basins.py egfrvhl_rank4 ms39_ref --solvents chloroform water
+python psa_ensemble.py egfrvhl_rank4 ms39_ref --solvent chloroform
+python ternary_span.py egfrvhl_rank4 ms39_ref
+```
+
+## Hardware and runtime
+
+The system is small, 2500-2800 atoms, so it is GPU-latency-bound rather than
+memory-bound and fits in under 2 GB of VRAM.
+
+| Platform | Speed | 50 ns x 3 x 2 solvents |
+|---|---|---|
+| Free A100 | ~1100 ns/day | ~6.5 h |
+| Shared GPU (~75% busy) | ~32 ns/day | ~9 days |
+| CPU (16 threads) | ~28 ns/day | ~10 days |
+
+A shared GPU is about 35x slower than a free one and no faster than CPU, so use
+an idle card. Replicas run sequentially in one process; parallelize by launching
+one process per GPU.
+
+The reference converged within 5-10 ns; 50 ns x 3 leaves a wide margin. Confirm
+with the RMSD plateau and the replica-mean spread in the dashboard, and extend
+if either is still drifting.
+
+## Known failure modes
+
+1. `ModuleNotFoundError: No module named 'pkg_resources'` at `SystemGenerator`.
+   `openff.amber_ff_ports` imports `pkg_resources`, which setuptools 81 removed.
+   Install `setuptools<81`.
+2. `OSError: Packmol not found`, chloroform only. `pack_box` resolves `packmol`
+   through PATH, so the env has to be activated, and so does `sqm` /
+   `antechamber` for AM1-BCC charges.
+3. Charge assignment is slow, one to three minutes on a single CPU core, and
+   happens inside `create_system`. Wrapping the run in a short `timeout` kills it
+   mid-charge and leaves a 0-byte `ff_cache.json`. Charges are cached per
+   molecule in `<name>/<solvent>/ff_cache.json`; copying a populated cache in
+   skips the step.
+4. Never select the PROTAC by atom name or element. It carries its own Cl, and
+   counterions named `Na`/`Cl` slip past naive regexes, which inflated Rg by
+   about 13%. Every script here selects it by residue instead: the non-water
+   residue with more than 5 atoms.
+5. mdtraj mislabels DCD frame times, so `traj.time` is not trustworthy. Derive
+   time from the frame index times `--report-ps`, as the scripts do.
+
+## Scope
+
+The simulations show that a generated PROTAC is physically sane and describe its
+conformational ensemble, extended versus folded, along with the folding-linked
+permeability descriptors. That is the same scope as the reference work, which
+also simulates the free PROTAC only.
+
+They do not show that a linker works as a degrader. Degradation needs a
+productive ternary complex of target, PROTAC and E3, which is a different
+simulation. `ternary_span.py` describes the span a linker can hold, not whether
+a complex forms.
+
+Folding propensity only means something against a baseline, so run the same
+pipeline on a reference PROTAC (`--smiles ... --name ms39_ref`) alongside each
+candidate.
+
+Yardsticks, from the 2022 MD paper: a compact minimum at Rg 5.4-5.6 A, and 3D
+PSA 190-265 A^2 for the permeable compounds against 290-330 A^2 for the poorly
+permeable one. From Atilaw 2021: passive permeability below Rg 7 A, and
+low-to-moderate permeability up to roughly 200-210 A^2. The 7 A cutoff on its
+own does not separate the 2022 compounds; see `reference_protocol.md`.

CupOFMoCA-PROTAC/md/analyze_conformations.py

@@ -0,0 +1,205 @@
+#!/usr/bin/env python
+"""
+Conformational analysis of free-PROTAC MD replicas.
+
+Reads all rep*/ trajectories under a solvent directory and computes, per replica
+and pooled: radius of gyration (Rg), RMSD to the first frame (convergence),
+solvent-accessible 3D polar surface area (3D PSA) and intramolecular H-bond
+count, then PCA + K-means clustering into conformational states with populations
+and saved centroid structures. The dashboard PNG carries the literature
+yardsticks (7 A Rg permeability cutoff, 3D PSA ~200-210 A^2).
+
+Time axes assume 10 ps per frame, protac_md.py's default --report-ps; a run made
+with a different --report-ps gets ns labels scaled by that ratio.
+
+Usage:
+    python analyze_conformations.py --dir egfrvhl_rank4/chloroform --name egfrvhl_rank4
+"""
+import argparse, glob, os
+import numpy as np
+import mdtraj as md
+import matplotlib; matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from scipy.cluster.vq import kmeans2
+
+RG_CUT = 0.70          # nm, passive-permeability cutoff (Atilaw 2021)
+PSA_LO, PSA_HI = 200.0, 210.0   # A^2; low-moderate permeability band
+COLORS = ["#0072B2", "#D55E00", "#009E73", "#CC79A7", "#E69F00"]
+INK, MUTED, GRID = "#222", "#666", "#DDD"
+
+
+def ligand_indices(top):
+    return [at.index for res in top.residues
+            if not res.is_water and res.n_atoms > 5 for at in res.atoms]
+
+
+def polar_slice_indices(top_lig):
+    """Indices (within the ligand-only topology) of polar atoms: N, O, and H on N/O."""
+    nbr = {}
+    for b in top_lig.bonds:
+        nbr.setdefault(b[0].index, []).append(b[1].index)
+        nbr.setdefault(b[1].index, []).append(b[0].index)
+    polar = []
+    for at in top_lig.atoms:
+        s = at.element.symbol
+        if s in ("N", "O"):
+            polar.append(at.index)
+        elif s == "H" and any(top_lig.atom(j).element.symbol in ("N", "O")
+                               for j in nbr.get(at.index, [])):
+            polar.append(at.index)
+    return np.array(sorted(set(polar)))
+
+
+def load_replicas(solvent_dir, name):
+    top_pdbs = glob.glob(os.path.join(solvent_dir, f"{name}_*_solvated.pdb"))
+    if not top_pdbs:
+        raise SystemExit(f"no *_solvated.pdb in {solvent_dir}")
+    top = top_pdbs[0]
+    reps = []
+    for rd in sorted(glob.glob(os.path.join(solvent_dir, "rep*"))):
+        dcd = os.path.join(rd, f"{name}_prod.dcd")
+        if os.path.exists(dcd):
+            reps.append((os.path.basename(rd), md.load(dcd, top=top)))
+    if not reps:
+        raise SystemExit(f"no rep*/{name}_prod.dcd trajectories in {solvent_dir}")
+    return reps
+
+
+def per_replica_metrics(traj):
+    top = traj.topology
+    lig = ligand_indices(top)
+    ligtraj = traj.atom_slice(lig)
+    ligtraj.center_coordinates()
+    rg = md.compute_rg(ligtraj)                                   # nm
+    rmsd = md.rmsd(ligtraj, ligtraj, 0) * 10.0                    # A, vs frame 0
+    sasa = md.shrake_rupley(ligtraj, mode="atom")                # nm^2 per atom
+    polar = polar_slice_indices(ligtraj.topology)
+    psa = sasa[:, polar].sum(axis=1) * 100.0                      # A^2
+    hb = [len(x) for x in md.wernet_nilsson(ligtraj)]            # intramolecular H-bonds/frame
+    return dict(rg=rg, rmsd=rmsd, psa=psa, hb=np.array(hb, float), ligtraj=ligtraj)
+
+
+def cluster(ligtrajs, k=5, seed=0):
+    pooled = md.join(ligtrajs)
+    pooled.superpose(pooled, 0)
+    X = pooled.xyz.reshape(pooled.n_frames, -1)
+    X = X - X.mean(0)
+    # PCA via SVD, keeping components up to 90% variance (cap 10)
+    U, S, Vt = np.linalg.svd(X, full_matrices=False)
+    var = (S ** 2) / (S ** 2).sum()
+    ncomp = min(10, max(2, int(np.searchsorted(np.cumsum(var), 0.90) + 1)))
+    proj = U[:, :ncomp] * S[:ncomp]
+    cent, labels = kmeans2(proj, k, minit="++", seed=seed)
+    pops = np.array([(labels == i).mean() for i in range(k)])
+    # global frame index closest to each cluster centroid, in PC space
+    cframes = []
+    for i in range(k):
+        idx = np.where(labels == i)[0]
+        cframes.append(int(idx[np.argmin(((proj[idx] - cent[i]) ** 2).sum(1))]) if len(idx) else -1)
+    return pooled, labels, pops, cframes, proj
+
+
+def style(ax, title, xlabel, ylabel):
+    ax.set_title(title, fontsize=11, color=INK, loc="left", weight="bold", pad=6)
+    ax.set_xlabel(xlabel, fontsize=9, color=MUTED); ax.set_ylabel(ylabel, fontsize=9, color=MUTED)
+    ax.grid(True, color=GRID, lw=0.6, alpha=0.8); ax.set_axisbelow(True)
+    for s in ("top", "right"): ax.spines[s].set_visible(False)
+    for s in ("left", "bottom"): ax.spines[s].set_color(GRID)
+    ax.tick_params(colors=MUTED, labelsize=8)
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--dir", required=True, help="solvent dir containing rep*/")
+    ap.add_argument("--name", required=True)
+    ap.add_argument("--clusters", type=int, default=5)
+    a = ap.parse_args()
+
+    reps = load_replicas(a.dir, a.name)
+    solvent = os.path.basename(a.dir.rstrip("/"))
+    print(f"[analyze] {a.name} / {solvent}: {len(reps)} replicas")
+
+    M = {rn: per_replica_metrics(tr) for rn, tr in reps}
+    ligtrajs = [M[rn]["ligtraj"] for rn, _ in reps]
+    pooled, labels, pops, cframes, proj = cluster(ligtrajs, a.clusters)
+
+    rg_all = np.concatenate([M[rn]["rg"] for rn, _ in reps])
+    psa_all = np.concatenate([M[rn]["psa"] for rn, _ in reps])
+    hb_all = np.concatenate([M[rn]["hb"] for rn, _ in reps])
+    rep_means = [M[rn]["rg"].mean() for rn, _ in reps]
+
+    # ---- dashboard ----
+    fig, axes = plt.subplots(2, 3, figsize=(15, 8.5), dpi=140)
+    fig.patch.set_facecolor("white")
+
+    ax = axes[0, 0]
+    for i, (rn, _) in enumerate(reps):
+        t = np.arange(len(M[rn]["rg"])) * 0.01  # ns; assumes protac_md.py default --report-ps 10
+        ax.plot(t, M[rn]["rg"], color=COLORS[i % 5], lw=0.8, alpha=0.85, label=rn)
+    ax.axhline(RG_CUT, color="k", ls="--", lw=1); ax.text(0.99, RG_CUT+0.003, "7 A permeability cutoff",
+             transform=ax.get_yaxis_transform(), ha="right", fontsize=7, color=MUTED)
+    style(ax, "Radius of gyration", "time (ns)", "Rg (nm)"); ax.legend(fontsize=7, frameon=False)
+
+    ax = axes[0, 1]
+    for i, (rn, _) in enumerate(reps):
+        t = np.arange(len(M[rn]["rmsd"])) * 0.01
+        ax.plot(t, M[rn]["rmsd"], color=COLORS[i % 5], lw=0.8, alpha=0.85)
+    style(ax, "RMSD to start (convergence)", "time (ns)", "RMSD (A)")
+
+    ax = axes[0, 2]
+    ax.hexbin(rg_all, psa_all, gridsize=35, cmap="Blues", mincnt=1)
+    ax.axvline(RG_CUT, color="k", ls="--", lw=1)
+    ax.axhspan(PSA_LO, PSA_HI, color="orange", alpha=0.15)
+    ax.text(0.02, PSA_HI, " PSA ~200-210 A^2", transform=ax.get_yaxis_transform(),
+            fontsize=7, color=MUTED, va="bottom")
+    style(ax, "3D PSA vs Rg (folding->permeability)", "Rg (nm)", "3D PSA (A^2)")
+
+    ax = axes[1, 0]
+    order = np.argsort(-pops)
+    ax.bar(range(len(pops)), pops[order] * 100, color=[COLORS[i % 5] for i in range(len(pops))])
+    for r, i in enumerate(order):
+        idx = labels == i
+        if idx.any():
+            ax.text(r, pops[i]*100 + 0.5, f"Rg {md.compute_rg(pooled[idx]).mean():.2f}",
+                    ha="center", fontsize=7, color=MUTED)
+    style(ax, f"Conformational clusters (k={a.clusters})", "cluster (by population)", "population (%)")
+
+    ax = axes[1, 1]
+    ax.hist(hb_all, bins=np.arange(0, hb_all.max()+2)-0.5, color="#0072B2", alpha=0.85, rwidth=0.9)
+    style(ax, "Intramolecular H-bonds", "H-bonds per frame", "count")
+
+    ax = axes[1, 2]; ax.axis("off")
+    summary = [
+        f"PROTAC : {a.name}",
+        f"Solvent: {solvent}   Replicas: {len(reps)}",
+        f"Frames : {pooled.n_frames} pooled",
+        "",
+        f"Rg      : {rg_all.mean():.3f} ± {rg_all.std():.3f} nm",
+        f"  per-rep means: " + ", ".join(f"{x:.3f}" for x in rep_means),
+        f"  replica spread (std of means): {np.std(rep_means):.3f} nm",
+        f"  frac below 7 A cutoff: {100*np.mean(rg_all<RG_CUT):.0f}%",
+        f"3D PSA  : {psa_all.mean():.0f} ± {psa_all.std():.0f} A^2",
+        f"IMHBs   : {hb_all.mean():.1f} ± {hb_all.std():.1f} per frame",
+        "",
+        "Reference: compact minimum Rg ~5.4-5.6 A;",
+        "3D PSA ~190-265 A^2 permeable vs 290-330 poor.",
+    ]
+    ax.text(0.0, 1.0, "\n".join(summary), va="top", family="monospace", fontsize=9, color=INK)
+
+    fig.suptitle(f"Free-PROTAC conformational analysis - {a.name} in {solvent} "
+                 f"({len(reps)}x{len(M[reps[0][0]]['rg'])*0.01:g} ns)",
+                 fontsize=13, weight="bold", color=INK, x=0.06, ha="left")
+    fig.tight_layout(rect=(0, 0, 1, 0.97))
+    out = os.path.join(a.dir, f"{a.name}_analysis.png")
+    fig.savefig(out, facecolor="white"); print(f"[analyze] wrote {out}")
+
+    # centroid structures
+    for r, i in enumerate(order):
+        if cframes[i] >= 0:
+            pooled[cframes[i]].save_pdb(os.path.join(a.dir, f"{a.name}_cluster{r+1}_pop{pops[i]*100:.0f}.pdb"))
+    print(f"[analyze] Rg {rg_all.mean():.3f} nm | 3D PSA {psa_all.mean():.0f} A^2 | "
+          f"IMHB {hb_all.mean():.1f} | replica-mean spread {np.std(rep_means):.3f} nm")
+
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/environment_md.yml

@@ -0,0 +1,38 @@
+name: protacmd
+# Conda env for the free-PROTAC MD pipeline (protac_md.py + analyze_conformations.py).
+#
+# cuda-version must match the driver on the machine you run on: check `nvidia-smi`
+# (top right). 12.* covers driver 525 and newer; drop the line for a CPU-only host.
+#
+#   conda env create -f environment_md.yml
+#   conda activate protacmd
+#
+# sqm, antechamber and packmol are only on PATH inside the env, so activate it
+# before running the pipeline.
+channels:
+  - conda-forge
+dependencies:
+  - python=3.10
+  # MD engine
+  - openmm=8.*
+  - cuda-version=12.*        # match the target machine's driver; drop for CPU-only
+  # parametrization
+  - openff-toolkit>=0.16
+  - openff-interchange>=0.4  # pack_box(), used to build the chloroform box
+  - openmmforcefields>=0.14
+  - ambertools>=23           # AM1-BCC charges (sqm) + GAFF fallback
+  - packmol                  # chloroform solvation
+  - rdkit>=2024.03
+  # analysis / plotting
+  - mdtraj
+  - parmed
+  - numpy
+  - scipy
+  - matplotlib
+  - pillow
+  - pip
+  # openff.amber_ff_ports imports pkg_resources, which setuptools>=81 dropped;
+  # without the pin the run dies in SystemGenerator. Pinned through pip rather
+  # than conda because an upper bound on setuptools blows up the conda solve.
+  - pip:
+      - "setuptools<81"

CupOFMoCA-PROTAC/md/linker_design.md

@@ -0,0 +1,86 @@
+# Linker rules for EGFR-VHL PROTACs, read off the MD runs
+
+The system is fixed: a gefitinib warhead (3-Cl-4-F-anilinoquinazoline, propyl-O,
+piperazine) and VH032 (tert-leucine, 4-hydroxyproline, 4-methylthiazolyl-
+benzylamine). Only the linker between the piperazine and the tert-leucine
+varies. The EGFR-VHL SMILES bundled in `protac_md.py` are built differently: in
+`egfrvhl_rank4` and `_rank5` the linker acylates the anilino nitrogen and the
+piperazine NH is left free. Everything below comes from explicit-solvent MD on generated linkers,
+run alongside the validated degrader MS39 and a PEG4 negative control.
+
+## Two gates
+
+1. **Permeability.** The linker has to let the molecule fold compact and bury
+   its polar surface in the membrane: low 3D PSA, compact Rg, intramolecular
+   H-bonds. Measured on the chloroform ensemble.
+2. **Ternary geometry.** It still has to reach an extended warhead-to-E3 span of
+   15-20 A at a cost the binding free energy can pay, below the 3.7 kcal/mol
+   conformational penalty of MS39. Measured on the water ensemble.
+
+Passing both means behaving like a molecular chameleon: mostly compact, with an
+accessible extended tail.
+
+## Runs
+
+Same warhead and E3, linker only. Neither the trajectories nor the linker SMILES
+are shipped here, so the table records what those runs showed rather than
+something the scripts regenerate. 3D PSA and Rg come from `psa_ensemble.py` and
+`rg_basins.py`; the clash-free fraction and the penalty come from a rigid
+ternary-geometry check that is not part of this folder.
+
+| linker | core | 3D PSA (A^2) | Rg in chloroform (A) | chameleon | clash-free fraction / penalty (kcal/mol) | verdict |
+|---|---|---|---|---|---|---|
+| dm2 | 2-(n-propyl)malonamide, short and branched | 140 | 5.96 | yes | 2.5% / 2.2 | passes both |
+| perm4 | 2-(allyl)malonamide, short and branched | 141 | 5.92 | yes | 4.3% / 1.9 | passes both |
+| MS39 (reference) | C10 linear diacid, sebacoyl | 178 | 6.51 | mild | 0.2% / 3.7 | validated degrader |
+| perm2 | cyclopentane-1,2-diyl, rigid ring | 172 | 6.40 | no | 0.0% / >5 | fails ternary |
+| perm3 | C6 linear diacid | 194 | 7.39 | no, folds in water and opens in the membrane | 1.3% / 2.6 | fails permeability |
+| PEG4 | PEG4 diacid | 193 | 7.21 | no | 0.1% / 4.1 | fails permeability |
+
+2D descriptors do not see this. TPSA is 191 for every linker except PEG4 at 228,
+so it cannot tell dm2 at 3D PSA 140 from perm3 at 194; the difference is folding
+in three dimensions. Rotatable bonds: 18 for the two winners, 20 for perm3, 24
+for MS39, 27 for PEG4. cLogP: 6.5-6.7 for the winners, 7.3-7.9 for perm2 and
+perm3, 8.8 for MS39, 5.4 for PEG4.
+
+## Rules, cheap enough to pre-screen before MD
+
+1. **Short, branched aliphatic core.** A 2-substituted malonamide or succinamide
+   with a small hydrophobic branch such as propyl or allyl folds compact while
+   the warhead's propyl-O-piperazine extension still covers the ternary span.
+2. **Avoid three failure chemistries.** PEG and poly-ether raise TPSA and HBA
+   and stay floppy, which kills permeability (PEG4); reject high ether-O counts,
+   TPSA above ~200, HBA above ~14. A rigid ring across the linker locks in a
+   non-spanning geometry, which kills ternary formation (perm2). Long linear
+   alkyl or diacid chains fold poorly (perm3) or push cLogP and PSA up (MS39).
+3. **Keep it stiff enough.** Rotatable bonds around 18, not 24-27.
+4. **Moderate cLogP,** roughly 6-7.
+
+## Hard experimental constraint
+
+Published EGFR-VHL SAR: linkers whose fully extended warhead-to-E3 span is under
+about 13 A, fewer than roughly 12 chain atoms end to end, show no degradation.
+Count the full chain from the piperazine anchor to the tert-leucine, not just
+the core, and keep it at 12 atoms or more (Cheng, Yu et al., *J. Med. Chem.*
+2020, the MS39 paper).
+
+## What MD should then confirm
+
+- 3D PSA of the folded state at or below ~150 A^2, a compact chloroform Rg basin
+  at or below ~6.0 A, and at least 95% of frames under 7 A.
+- Chameleonic behavior: chloroform Rg below water Rg, intramolecular H-bonds at
+  1.5 or more.
+- Ternary reach: a span of 15 A or more in 1-2% of the water ensemble, a penalty
+  at or below ~3 kcal/mol.
+
+## Caveats
+
+Propose in 2D, then confirm the top few by MD.
+
+The ternary axis is a rigid free-solution proxy, not a validated degradation
+score. The 12-atom rule still applies on top of it.
+
+## Cores worth imitating
+
+- dm2, 2-propyl malonamide: `CCC[C@@H](C(=O)N-VH032)C(=O)N-piperazine`
+- perm4, the same with an allyl branch: `C=CC`

CupOFMoCA-PROTAC/md/plot_results.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python
+"""One-page summary figure for a single replica of a protac_md.py run: the
+radius of gyration, potential energy and density traces of the production run,
+with the PROTAC 2D structure beside them when --smiles is given. Writes
+<rep>/<name>_summary.png.
+
+Usage:
+    python plot_results.py --rep egfrvhl_rank4/chloroform/rep1
+    python plot_results.py --rep egfrvhl_rank4/chloroform/rep1 --smiles "<SMILES>"
+"""
+import argparse, csv, glob, io, os
+import numpy as np
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from matplotlib.gridspec import GridSpec
+import mdtraj as md
+from rdkit import Chem
+from rdkit.Chem import AllChem
+from rdkit.Chem.Draw import rdMolDraw2D
+from PIL import Image
+
+# Okabe-Ito colorblind-safe hues
+BLUE, VERM, GREEN = "#0072B2", "#D55E00", "#009E73"
+INK, MUTED, GRID = "#222222", "#666666", "#DDDDDD"
+
+
+def load_csv(path):
+    with open(path) as fh:
+        rows = list(csv.reader(fh))
+    header = [h.strip().strip('#"').strip() for h in rows[0]]
+    data = np.array([[float(x) for x in r] for r in rows[1:] if r])
+    col = {h: data[:, i] for i, h in enumerate(header)}
+
+    def find(key):
+        return next(c for h, c in col.items() if key.lower() in h.lower())
+
+    t = find("time") / 1000.0          # ps -> ns
+    return t - t[0], find("potential"), find("temperature"), find("density")
+
+
+def load_rg(rep_dir, name):
+    """Rg of the PROTAC (nm), same selection as analyze_conformations.py."""
+    tops = glob.glob(os.path.join(rep_dir, os.pardir, "*_solvated.pdb"))
+    traj = md.load(os.path.join(rep_dir, f"{name}_prod.dcd"), top=tops[0])
+    lig = [a.index for r in traj.topology.residues
+           if not r.is_water and r.n_atoms > 5 for a in r.atoms]
+    sub = traj.atom_slice(lig)
+    sub.center_coordinates()
+    return md.compute_rg(sub)
+
+
+def mol_image(smiles, px=700):
+    mol = Chem.MolFromSmiles(smiles)
+    AllChem.Compute2DCoords(mol)
+    d = rdMolDraw2D.MolDraw2DCairo(px, px)
+    d.drawOptions().bondLineWidth = 2
+    d.drawOptions().padding = 0.06
+    rdMolDraw2D.PrepareAndDrawMolecule(d, mol)
+    d.FinishDrawing()
+    return Image.open(io.BytesIO(d.GetDrawingText()))
+
+
+def style(ax, title, ylabel):
+    ax.set_title(title, fontsize=11, color=INK, loc="left", pad=6, weight="bold")
+    ax.set_ylabel(ylabel, fontsize=9, color=MUTED)
+    ax.set_xlabel("production time (ns)", fontsize=9, color=MUTED)
+    ax.grid(True, color=GRID, lw=0.6, alpha=0.8)
+    ax.set_axisbelow(True)
+    for s in ("top", "right"):
+        ax.spines[s].set_visible(False)
+    for s in ("left", "bottom"):
+        ax.spines[s].set_color(GRID)
+    ax.tick_params(colors=MUTED, labelsize=8, length=3)
+
+
+def main():
+    p = argparse.ArgumentParser()
+    p.add_argument("--rep", required=True, help="replica directory, e.g. <name>/<solvent>/rep1")
+    p.add_argument("--name", default=None, help="run name (default: the run directory's name)")
+    p.add_argument("--smiles", default=None, help="draw this structure in the left panel")
+    p.add_argument("--report-ps", type=float, default=10.0, help="DCD frame interval")
+    a = p.parse_args()
+
+    rep = a.rep.rstrip("/")
+    name = a.name or os.path.basename(os.path.dirname(os.path.dirname(rep)))
+    solvent = os.path.basename(os.path.dirname(rep))
+
+    t, pe, temp, dens = load_csv(os.path.join(rep, f"{name}_prod.csv"))
+    rg = load_rg(rep, name)
+    rg_t = np.arange(len(rg)) * a.report_ps / 1000.0       # frame index -> ns
+
+    fig = plt.figure(figsize=(13, 7.5), dpi=150)
+    fig.patch.set_facecolor("white")
+    ncol = 3 if a.smiles else 2
+    gs = GridSpec(2, ncol, figure=fig, hspace=0.42, wspace=0.30,
+                  left=0.06, right=0.98, top=0.90, bottom=0.09)
+    off = 0
+
+    if a.smiles:
+        axm = fig.add_subplot(gs[:, 0])
+        axm.axis("off")
+        axm.imshow(mol_image(a.smiles))
+        axm.set_title(name, fontsize=11, color=INK, loc="left", weight="bold", pad=6)
+        off = 1
+
+    ax1 = fig.add_subplot(gs[0, off:])
+    ax1.plot(rg_t, rg, color=BLUE, lw=1.2)
+    m = rg.mean()
+    ax1.axhline(m, color=MUTED, lw=1.0, ls="--")
+    ax1.annotate(f"mean {m:.2f} nm", (rg_t[-1], m), color=MUTED, fontsize=8,
+                 ha="right", va="bottom", xytext=(0, 3), textcoords="offset points")
+    style(ax1, "Radius of gyration", "Rg (nm)")
+
+    ax2 = fig.add_subplot(gs[1, off])
+    ax2.plot(t, pe / 1000.0, color=VERM, lw=1.0)
+    style(ax2, "Potential energy", "PE (10^3 kJ/mol)")
+
+    ax3 = fig.add_subplot(gs[1, off + 1])
+    ax3.plot(t, dens, color=GREEN, lw=1.0)
+    style(ax3, "System density", "density (g/mL)")
+
+    fig.suptitle(f"Free-PROTAC MD summary - {name} in {solvent} "
+                 f"({t[-1]:.0f} ns, 300 K / 1 bar)",
+                 fontsize=13, color=INK, x=0.06, ha="left", weight="bold")
+
+    out = os.path.join(rep, f"{name}_summary.png")
+    fig.savefig(out, facecolor="white")
+    print("wrote", out)
+    print(f"Rg {rg.mean():.3f}±{rg.std():.3f} nm | T {temp.mean():.1f} K | "
+          f"rho {dens.mean():.3f} g/mL")
+
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/protac_md.py

@@ -0,0 +1,314 @@
+#!/usr/bin/env python
+"""
+Explicit-solvent MD of a free PROTAC (no POI, no E3 protein), following the
+protocol of "Linker-Dependent Folding Rationalizes PROTAC Cell Permeability"
+(J. Med. Chem. 2022, DOI 10.1021/acs.jmedchem.2c00877): triplicate ~100 ns runs in
+chloroform (membrane-interior mimic) and/or water, analyzed for Rg, 3D PSA,
+intramolecular H-bonds and conformational clusters.
+
+Pipeline:
+  1. RDKit: SMILES -> add Hs -> ETKDGv3 multi-conformer -> MMFF -> lowest-E conf.
+  2. OpenFF Sage (openff-2.2.0) + AM1-BCC charges via AmberTools for the PROTAC
+     (and for chloroform, when used) through openmmforcefields.
+  3. Solvate:
+       water      -> OpenMM addSolvent (TIP3P, 0.15 M NaCl, neutralized)
+       chloroform -> packmol via openff-interchange pack_box
+  4. Minimize once, then run N independent replicas (different velocity seeds),
+     each: NVT heat 50->T, NPT equilibration, NPT production.
+
+Outputs per replica land in <out>/<solvent>/rep<k>/; analyze them with
+analyze_conformations.py.
+
+Environment: conda env "protacmd" (environment_md.yml). Needs setuptools<81:
+openff.amber_ff_ports imports pkg_resources, which setuptools 81 dropped, and
+the run dies inside SystemGenerator without it.
+
+Usage:
+    python protac_md.py --solvent chloroform --replicas 3 --prod-ns 100 --gpu 0
+    python protac_md.py --solvent water      --replicas 3 --prod-ns 100 --gpu 0
+    python protac_md.py --prep-only                       # just the 3D conformer
+"""
+
+import argparse
+import os
+import sys
+import time
+
+# Top-ranked generated PROTACs for EGFR-VHL, BRD9-VHL and CDK6-CRBN. Any other
+# SMILES can be simulated with --smiles.
+CANDIDATES = {
+    "egfrvhl_rank4": "CCCC(C(=O)N[C@H](C(=O)N1C[C@H](O)C[C@H]1C(=O)NCc1ccc(-c2scnc2C)cc1)"
+                     "C(C)(C)C)C(=O)N(c1ccc(F)c(Cl)c1)c1ncnc2cc(OC)c(OCCCCN3CCNCC3)cc12",
+    "egfrvhl_rank5": "CCNC(=O)C(OC(=O)C(=O)N[C@H](C(=O)N1C[C@H](O)C[C@H]1C(=O)NCc1ccc(-c2scnc2C)cc1)"
+                     "C(C)(C)C)C(=O)N(c1ccc(F)c(Cl)c1)c1ncnc2cc(OC)c(OCCCCN3CCNCC3)cc12",
+    "brd9vhl_rank1": "CCC(C)C(C(=O)N[C@H](C(=O)N1C[C@H](O)C[C@H]1C(=O)NCc1ccc(-c2scnc2C)cc1)C(C)(C)C)"
+                     "C(=O)N1CCN(Cc2c(OC)cc(-c3cn(C)c(=O)c4cnccc34)cc2OC)CC1",
+    "cdk6crbn_rank2": "CC(=O)c1c(C)c2cnc(N(C(=O)CC(C)CC(=O)Nc3cccc4c3C(=O)N(C3CCC(=O)NC3=O)C4=O)"
+                      "c3ccc(N4CCNCC4)nc3)nc2n(C2CCCC2)c1=O",
+}
+DEFAULT_CANDIDATE = "egfrvhl_rank4"
+CHLOROFORM_SMILES = "C(Cl)(Cl)Cl"
+CHLOROFORM_DENSITY_PER_NM3 = 7.51   # molecules/nm^3 at 1.49 g/mL, 300 K
+
+
+# --- 3D conformer -----------------------------------------------------------
+def build_conformer(smiles, name, out_dir, n_confs=20, seed=0xF00D):
+    from rdkit import Chem
+    from rdkit.Chem import AllChem, Descriptors, rdMolDescriptors
+
+    mol = Chem.MolFromSmiles(smiles)
+    if mol is None:
+        sys.exit(f"[fatal] RDKit could not parse SMILES: {smiles}")
+    print(f"[prep] {name}: MW={Descriptors.MolWt(mol):.1f}  "
+          f"charge={Chem.GetFormalCharge(mol):+d}  "
+          f"rot.bonds={rdMolDescriptors.CalcNumRotatableBonds(mol)}")
+
+    molh = Chem.AddHs(mol)
+    params = AllChem.ETKDGv3()
+    params.randomSeed = seed
+    params.useRandomCoords = True
+    cids = AllChem.EmbedMultipleConfs(molh, numConfs=n_confs, params=params)
+    if len(cids) == 0:
+        if AllChem.EmbedMolecule(molh, params) != 0:
+            sys.exit("[fatal] 3D embedding failed.")
+        cids = [0]
+    if not AllChem.MMFFHasAllMoleculeParams(molh):
+        print("[warn] MMFF missing some params; conformer quality may be lower.")
+    results = AllChem.MMFFOptimizeMoleculeConfs(molh, maxIters=2000)
+    best_cid, best_e = min(zip(cids, [e for _, e in results]), key=lambda x: x[1])
+    print(f"[prep] lowest MMFF conformer {best_cid} (E={best_e:.1f} kcal/mol)")
+
+    sdf = os.path.join(out_dir, f"{name}.sdf")
+    w = Chem.SDWriter(sdf); molh.SetProp("_Name", name); w.write(molh, confId=best_cid); w.close()
+    print(f"[prep] wrote {sdf}")
+    keep = Chem.Mol(molh); keep.RemoveAllConformers()
+    keep.AddConformer(molh.GetConformer(best_cid), assignId=True)
+    return keep
+
+
+# --- solvation --------------------------------------------------------------
+def solvate_water(molecule, system_generator, cfg):
+    from openmm import app, unit
+    off_top = molecule.to_topology()
+    modeller = app.Modeller(off_top.to_openmm(), molecule.conformers[0].to_openmm())
+    modeller.addSolvent(system_generator.forcefield, model="tip3p",
+                        padding=cfg.padding * unit.nanometer,
+                        ionicStrength=cfg.ionic * unit.molar, neutralize=True)
+    return modeller.topology, modeller.positions
+
+
+def solvate_chloroform(molecule, chcl3, cfg):
+    import numpy as np
+    from openff.interchange.components._packmol import pack_box
+    from openff.units import unit as ou
+    from openff.units.openmm import to_openmm
+
+    conf = molecule.conformers[0].m_as(ou.nanometer)
+    extent = np.linalg.norm(conf - conf.mean(0), axis=1).max() * 2.0   # ~diameter, nm
+    box = extent + 2.0 * cfg.padding
+    n = int(round(0.90 * CHLOROFORM_DENSITY_PER_NM3 * box ** 3))       # under-fill; NPT compresses
+    print(f"[md] chloroform box {box:.2f} nm, packing {n} CHCl3 (NPT will set final density)")
+    box_vecs = np.eye(3) * box * ou.nanometer
+    packed = pack_box(molecules=[chcl3], number_of_copies=[n],
+                      solute=molecule.to_topology(), box_vectors=box_vecs,
+                      center_solute=True, tolerance=2.0 * ou.angstrom)
+    omm_top = packed.to_openmm()
+    omm_top.setPeriodicBoxVectors(to_openmm(packed.box_vectors))
+    positions = to_openmm(packed.get_positions())
+    return omm_top, positions
+
+
+# --- solvated system, minimized once ----------------------------------------
+def build_system(rdkit_mol, name, out_dir, cfg):
+    from openmm import app, unit, LangevinMiddleIntegrator, Platform
+    from openff.toolkit import Molecule
+    from openmmforcefields.generators import SystemGenerator
+
+    molecule = Molecule.from_rdkit(rdkit_mol, allow_undefined_stereo=True)
+    molecule.name = name
+
+    extra = []
+    chcl3 = None
+    if cfg.solvent == "chloroform":
+        chcl3 = Molecule.from_smiles(CHLOROFORM_SMILES)
+        chcl3.generate_conformers(n_conformers=1)
+        chcl3.name = "CL3"
+        extra = [chcl3]
+
+    forcefield_kwargs = {"constraints": app.HBonds, "rigidWater": True,
+                         "removeCMMotion": True, "hydrogenMass": cfg.hmass * unit.amu}
+    periodic_kwargs = {"nonbondedMethod": app.PME, "nonbondedCutoff": 1.0 * unit.nanometer}
+    system_generator = SystemGenerator(
+        forcefields=["amber/ff14SB.xml", "amber/tip3p_standard.xml",
+                     "amber/tip3p_HFE_multivalent.xml"],
+        small_molecule_forcefield=cfg.small_mol_ff,
+        molecules=[molecule] + extra,
+        forcefield_kwargs=forcefield_kwargs,
+        periodic_forcefield_kwargs=periodic_kwargs,
+        cache=os.path.join(out_dir, "ff_cache.json"))
+    print(f"[md] solvent={cfg.solvent}  small-molecule FF={cfg.small_mol_ff} (AM1-BCC charges)")
+
+    if cfg.solvent == "water":
+        topology, positions = solvate_water(molecule, system_generator, cfg)
+    else:
+        topology, positions = solvate_chloroform(molecule, chcl3, cfg)
+
+    n_atoms = topology.getNumAtoms()
+    print(f"[md] solvated system: {n_atoms} atoms")
+    app.PDBFile.writeFile(topology, positions,
+                          open(os.path.join(out_dir, f"{name}_{cfg.solvent}_solvated.pdb"), "w"))
+
+    base_system = system_generator.create_system(topology)
+
+    # minimize once; replicas branch from here with fresh velocities
+    integ = LangevinMiddleIntegrator(cfg.temperature * unit.kelvin, 1.0 / unit.picosecond,
+                                     cfg.timestep * unit.femtosecond)
+    plat, prop = _pick_platform(Platform, cfg)
+    sim = app.Simulation(topology, base_system, integ, plat, prop)
+    sim.context.setPositions(positions)
+    print("[md] minimizing solvated system...")
+    sim.minimizeEnergy(maxIterations=cfg.min_iters)
+    min_pos = sim.context.getState(getPositions=True).getPositions()
+    del sim, integ
+    return topology, base_system, min_pos, plat, prop
+
+
+# --- one replica: heat, NPT equilibrate, NPT production ---------------------
+def run_replica(topology, base_system, min_pos, plat, prop, name, rep_dir, cfg, seed):
+    import openmm
+    from openmm import app, unit, XmlSerializer
+
+    os.makedirs(rep_dir, exist_ok=True)
+    temperature = cfg.temperature * unit.kelvin
+    pressure = cfg.pressure * unit.bar
+    dt = cfg.timestep * unit.femtosecond
+
+    # independent copy per replica: each adds its own barostat below, so sharing
+    # base_system would stack one barostat per replica
+    system = XmlSerializer.deserialize(XmlSerializer.serialize(base_system))
+    integrator = openmm.LangevinMiddleIntegrator(temperature, 1.0 / unit.picosecond, dt)
+    integrator.setRandomNumberSeed(seed)
+    sim = app.Simulation(topology, system, integrator, plat, prop)
+    sim.context.setPositions(min_pos)
+    sim.context.setVelocitiesToTemperature(50 * unit.kelvin, seed)
+
+    # NVT heating 50 -> T
+    heat_steps = int(cfg.heat_ps * 1000 / cfg.timestep)
+    n_stages = 25
+    for i in range(n_stages):
+        t = 50 + (cfg.temperature - 50) * (i + 1) / n_stages
+        integrator.setTemperature(t * unit.kelvin)
+        sim.step(max(1, heat_steps // n_stages))
+
+    # add barostat -> NPT equilibration
+    baro = openmm.MonteCarloBarostat(pressure, temperature, 25)
+    baro.setRandomNumberSeed(seed)
+    system.addForce(baro)
+    sim.context.reinitialize(preserveState=True)
+    sim.step(int(cfg.equil_ps * 1000 / cfg.timestep))
+    _write_pdb(app, sim, os.path.join(rep_dir, f"{name}_equilibrated.pdb"))
+
+    # production
+    steps_per_ns = int(round(1e6 / cfg.timestep))
+    prod_steps = int(cfg.prod_ns * steps_per_ns)
+    report_every = max(1, int(cfg.report_ps * 1000 / cfg.timestep))
+    sim.currentStep = 0   # so the progress reporter excludes heat + equilibration
+    dcd = os.path.join(rep_dir, f"{name}_prod.dcd")
+    sim.reporters.append(app.DCDReporter(dcd, report_every))
+    sim.reporters.append(app.StateDataReporter(
+        os.path.join(rep_dir, f"{name}_prod.csv"), report_every, step=True, time=True,
+        potentialEnergy=True, temperature=True, density=True, volume=True, speed=True))
+    sim.reporters.append(app.StateDataReporter(
+        sys.stdout, report_every * 20, step=True, temperature=True, density=True,
+        speed=True, progress=True, remainingTime=True, totalSteps=prod_steps))
+    sim.reporters.append(app.CheckpointReporter(os.path.join(rep_dir, f"{name}_prod.chk"),
+                                                report_every * 20))
+    print(f"[md] {os.path.basename(rep_dir)}: production {cfg.prod_ns} ns -> {dcd}")
+    t0 = time.time()
+    sim.step(prod_steps)
+    print(f"[md] {os.path.basename(rep_dir)} done in {(time.time()-t0)/3600:.2f} h")
+    _write_pdb(app, sim, os.path.join(rep_dir, f"{name}_final.pdb"))
+
+
+def run_md(rdkit_mol, name, out_dir, cfg):
+    solvent_dir = os.path.join(out_dir, cfg.solvent)
+    os.makedirs(solvent_dir, exist_ok=True)
+    topology, base_system, min_pos, plat, prop = build_system(rdkit_mol, name, solvent_dir, cfg)
+    for k in range(cfg.replicas):
+        rep_dir = os.path.join(solvent_dir, f"rep{k+1}")
+        run_replica(topology, base_system, min_pos, plat, prop, name, rep_dir, cfg,
+                    seed=cfg.seed + 1000 * (k + 1))
+    print(f"[md] all {cfg.replicas} replicas ({cfg.solvent}) complete -> {solvent_dir}")
+    print(f"[md] analyze with:  python analyze_conformations.py --dir {solvent_dir} --name {name}")
+
+
+def _pick_platform(Platform, cfg):
+    avail = {Platform.getPlatform(i).getName() for i in range(Platform.getNumPlatforms())}
+    order = [cfg.platform] if cfg.platform != "auto" else ["CUDA", "OpenCL", "CPU"]
+    for pn in order:
+        if pn in avail:
+            prop = {"Precision": "mixed", "DeviceIndex": str(cfg.gpu)} if pn in ("CUDA", "OpenCL") else {}
+            print(f"[md] platform = {pn} {prop}")
+            return Platform.getPlatformByName(pn), prop
+    sys.exit(f"[fatal] platform '{cfg.platform}' unavailable; have {sorted(avail)}")
+
+
+def _write_pdb(app, sim, path):
+    st = sim.context.getState(getPositions=True, enforcePeriodicBox=True)
+    with open(path, "w") as fh:
+        app.PDBFile.writeFile(sim.topology, st.getPositions(), fh)
+
+
+def parse_args():
+    p = argparse.ArgumentParser(description=__doc__,
+                                formatter_class=argparse.RawDescriptionHelpFormatter)
+    m = p.add_argument_group("molecule")
+    m.add_argument("--candidate", choices=sorted(CANDIDATES), default=DEFAULT_CANDIDATE)
+    m.add_argument("--smiles", default=None, help="custom PROTAC SMILES (e.g. a reference PROTAC)")
+    m.add_argument("--name", default=None)
+    m.add_argument("--out-dir", default=None)
+    m.add_argument("--n-confs", type=int, default=20)
+
+    r = p.add_argument_group("simulation")
+    r.add_argument("--prep-only", action="store_true", help="only build 3D conformer (rdkit only)")
+    r.add_argument("--solvent", choices=["chloroform", "water"], default="chloroform",
+                   help="chloroform = membrane-interior mimic (permeability); water = polar")
+    r.add_argument("--replicas", type=int, default=3, help="independent runs (different seeds)")
+    r.add_argument("--seed", type=int, default=1234)
+    r.add_argument("--small-mol-ff", dest="small_mol_ff", default="openff-2.2.0")
+    r.add_argument("--padding", type=float, default=1.2, help="solvent padding, nm")
+    r.add_argument("--ionic", type=float, default=0.15, help="NaCl conc (water only), M")
+    r.add_argument("--temperature", type=float, default=300.0)
+    r.add_argument("--pressure", type=float, default=1.0)
+    r.add_argument("--timestep", type=float, default=2.0)
+    r.add_argument("--hmass", type=float, default=1.5)
+    r.add_argument("--min-iters", type=int, default=5000)
+    r.add_argument("--heat-ps", type=float, default=100.0)
+    r.add_argument("--equil-ps", type=float, default=500.0)
+    r.add_argument("--prod-ns", type=float, default=100.0)
+    r.add_argument("--report-ps", type=float, default=10.0)
+
+    h = p.add_argument_group("hardware")
+    h.add_argument("--platform", default="auto", choices=["auto", "CUDA", "OpenCL", "CPU"])
+    h.add_argument("--gpu", type=int, default=0)
+    return p.parse_args()
+
+
+def main():
+    cfg = parse_args()
+    smiles = cfg.smiles or CANDIDATES[cfg.candidate]
+    name = cfg.name or (cfg.candidate if not cfg.smiles else "custom_protac")
+    out_dir = cfg.out_dir or os.path.join(os.path.dirname(os.path.abspath(__file__)), name)
+    os.makedirs(out_dir, exist_ok=True)
+    print(f"[run] name={name}  solvent={cfg.solvent}  replicas={cfg.replicas}  out={out_dir}")
+    print(f"[run] SMILES={smiles}")
+
+    rdkit_mol = build_conformer(smiles, name, out_dir, n_confs=cfg.n_confs)
+    if cfg.prep_only:
+        print("[run] --prep-only: done."); return
+    run_md(rdkit_mol, name, out_dir, cfg)
+    print("[run] all done.")
+
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/protacmd-lock-linux64.txt

@@ -0,0 +1,296 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+# created-by: conda 26.3.2
+@EXPLICIT
+https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-hbd8a1cb_0.conda
+https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-source-code-pro-2.038-h77eed37_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-h77eed37_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_19.conda
+https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/llvm-openmp-22.1.8-h4922eb0_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/onemkl-license-2025.3.1-hf2ce2f3_12.conda
+https://conda.anaconda.org/conda-forge/noarch/python_abi-3.10-8_cp310.conda
+https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-7_kmp_llvm.conda
+https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-hc364b38_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/zlib-1.3.2-h25fd6f3_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
+https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45.1-default_hbd61a6d_102.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_19.conda
+https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
+https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.6-hb03c661_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.2.0-hb03c661_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.25-h17f619e_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.8.1-hecca717_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/libffi-3.7.0-h3435931_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_19.conda
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.2.0-h68bc16d_19.conda
+https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h3b78370_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-3.1.4.1-hb03c661_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.3-hb03c661_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/libntlm-1.8-hb9d3cd8_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.58-h421ea60_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.53.3-h0c1763c_0.conda
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+https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb03c661_1.conda
+https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h280c20c_3.conda
+https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-12.9.86-hecca717_1.conda
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+https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.1-hcf80075_0.conda
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-15.2.0-hdf11a46_19.conda
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+https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.44-hc749103_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/pixman-0.46.4-h54a6638_1.conda
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CupOFMoCA-PROTAC/md/psa_ensemble.py

@@ -0,0 +1,73 @@
+#!/usr/bin/env python
+"""3D polar surface area over an MD ensemble.
+
+Element-based PSA: N, O and polar H, Bondi radii, 1.4 A probe, mdtraj
+shrake_rupley. validate_psa.py checks this code path against the published
+grazoprevir numbers. Lower PSA in the membrane mimic tracks higher passive
+permeability.
+
+Polar atoms are indexed from each run's SDF, so the SDF and MD atom orders must
+agree. A run whose ligand atom count does not match its SDF is reported and
+dropped from the table rather than summed over the wrong atoms.
+
+Usage:
+    python psa_ensemble.py egfrvhl_rank4 ms39_ref --solvent chloroform --out psa.npy
+"""
+import argparse, glob, os
+import numpy as np
+import mdtraj as md
+from rdkit import Chem
+
+
+def polar_idx_from_sdf(sdf):
+    m = Chem.MolFromMolFile(sdf, removeHs=False)
+    idx = []
+    for a in m.GetAtoms():
+        s = a.GetSymbol()
+        if s in ("N", "O"):
+            idx.append(a.GetIdx())
+        elif s == "H" and any(nb.GetSymbol() in ("N", "O") for nb in a.GetNeighbors()):
+            idx.append(a.GetIdx())
+    return idx, m.GetNumAtoms()
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("runs", nargs="+", help="run directories, one per compound")
+    ap.add_argument("--solvent", default="chloroform")
+    ap.add_argument("--stride", type=int, default=20)
+    ap.add_argument("--out", default=None, help="optional .npy dump of the per-frame values")
+    a = ap.parse_args()
+
+    print(f"{'compound':16s}{'n_pol':6s}{'3D PSA (A^2)  mean(std)':24s}{'frames':8s}")
+    print("-" * 56)
+    out = {}
+    for run in a.runs:
+        name = os.path.basename(run.rstrip("/"))
+        pol, nat = polar_idx_from_sdf(os.path.join(run, f"{name}.sdf"))
+        tops = glob.glob(os.path.join(run, a.solvent, "*_solvated.pdb"))
+        if not tops:
+            print(f"{name:16s}  no {a.solvent} topology"); continue
+        vals = []
+        for dcd in sorted(glob.glob(os.path.join(run, a.solvent, "rep*", f"{name}_prod.dcd"))):
+            tr = md.load(dcd, top=tops[0], stride=a.stride)
+            lig = [at.index for r in tr.topology.residues
+                   if not r.is_water and r.n_atoms > 5 for at in r.atoms]
+            sub = tr.atom_slice(lig)
+            if sub.n_atoms != nat:
+                print(f"{name:16s}  atom count mismatch md={sub.n_atoms} sdf={nat}")
+                vals = None
+                break
+            sasa = md.shrake_rupley(sub, mode="atom", probe_radius=0.14)   # nm^2
+            vals.extend((sasa[:, pol].sum(1) * 100.0).tolist())            # A^2 per frame
+        if vals:
+            v = np.array(vals)
+            print(f"{name:16s}{len(pol):<6d}{f'{v.mean():.0f} ({v.std():.0f})':24s}{len(v):<8d}")
+            out[name] = dict(mean=float(v.mean()), std=float(v.std()), vals=v.tolist())
+    if a.out and out:
+        np.save(a.out, out, allow_pickle=True)
+        print(f"\nsaved {a.out}")
+
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/psa_method_probe.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+"""Compare polar-atom selection conventions for 3D PSA on a finished run.
+
+The element-based selection (N, O, polar H) and the charge-threshold selection
+used in the reference work give different absolute PSA values on the same
+trajectory. This prints both, sweeping the charge threshold, so a gap against
+published numbers can be attributed to convention rather than to conformation.
+Charges come from the run's AM1-BCC cache, so nothing is recomputed.
+
+Takes a run name rather than a path and resolves <name>/<solvent>/ against the
+current directory, so run it from the md folder. Solvent defaults to chloroform.
+
+Usage:
+    python psa_method_probe.py egfrvhl_rank4 [solvent]
+"""
+import json, glob, numpy as np, mdtraj as md
+import xml.etree.ElementTree as ET
+
+def cached_charges(cache_path):
+    d = json.load(open(cache_path))
+    entry = list(list(d.values())[0].values())[0]      # {'openff-2.2.0': {'1': {'ffxml': ...}}}
+    ffxml = entry["ffxml"]
+    root = ET.fromstring(ffxml)
+    # type -> charge from NonbondedForce
+    q_by_type = {}
+    for a in root.iter("Atom"):
+        if a.get("charge") is not None and a.get("type") is not None:
+            q_by_type[a.get("type")] = float(a.get("charge"))
+    # atom order from the Residue template
+    res = root.find(".//Residues/Residue")
+    order = [a.get("type") for a in res.findall("Atom")]
+    return np.array([q_by_type[t] for t in order])
+
+def main():
+    import sys
+    NAME = sys.argv[1] if len(sys.argv) > 1 else "egfrvhl_rank4"
+    SOL = sys.argv[2] if len(sys.argv) > 2 else "chloroform"
+    q = cached_charges(f"{NAME}/{SOL}/ff_cache.json")
+    print(f"charges from cache: n={len(q)}  range [{q.min():.2f},{q.max():.2f}]  "
+          f"#|q|>1.0={(np.abs(q) > 1.0).sum()}")
+
+    top = glob.glob(f"{NAME}/{SOL}/*_solvated.pdb")[0]
+    reps = sorted(glob.glob(f"{NAME}/{SOL}/rep*/{NAME}_prod.dcd"))
+    tr = md.join([md.load(r, top=top) for r in reps])
+    lig = [a.index for r in tr.topology.residues if not r.is_water and r.n_atoms > 5
+           for a in r.atoms]
+    t = tr.atom_slice(lig); t.center_coordinates(); L = t.topology
+    syms = [a.element.symbol for a in L.atoms]
+    if len(syms) != len(q):
+        print(f"atom-count mismatch: cache {len(q)} vs MD {len(syms)}"); return
+    sasa = md.shrake_rupley(t, mode="atom", probe_radius=0.14)   # nm^2
+    def area(mask): return (sasa[:, mask].sum(1) * 100.0).mean()
+
+    nbr = {}
+    for b in L.bonds:
+        nbr.setdefault(b[0].index, []).append(b[1].index)
+        nbr.setdefault(b[1].index, []).append(b[0].index)
+    elem = np.array([i for i, a in enumerate(L.atoms)
+        if a.element.symbol in ("N", "O") or (a.element.symbol == "H" and
+           any(L.atom(j).element.symbol in ("N", "O") for j in nbr.get(a.index, [])))])
+
+    print(f"\nelement selection (N, O, polar H): {area(elem):.0f} A2  ({len(elem)} atoms)")
+    print("charge-threshold selection:")
+    print(f"  {'|q|>thr':>8s}{'#atoms':>8s}{'PSA':>7s}")
+    for thr in [0.10, 0.15, 0.20, 0.25, 0.30, 0.40, 0.50]:
+        m = np.abs(q) > thr
+        print(f"  {thr:>8.2f}{int(m.sum()):>8d}{area(m):>7.0f}")
+    print("\nreference permeable band = 190-265 A2")
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/reference_protocol.md

@@ -0,0 +1,58 @@
+# Reference protocol and permeability yardsticks
+
+The MD pipeline in this folder is a deliberate copy of one published protocol,
+with the numbers it should be read against collected here.
+
+## Sources
+
+- **"Linker-Dependent Folding Rationalizes PROTAC Cell Permeability,"
+  *J. Med. Chem.* 2022 (PMC9574858).** The MD paper, and the template for
+  `protac_md.py` and `analyze_conformations.py`. Three CRBN/BRD4 PROTACs with
+  different linkers, PEG-like against alkyl.
+- **Atilaw et al., "Solution Conformations Shed Light on PROTAC Cell
+  Permeability," *ACS Med. Chem. Lett.* 2021, 12, 107-114.** NMR plus Monte
+  Carlo conformational search and NAMFIS, not MD, on one VHL PROTAC (ERK5). It
+  is the source of the folded-versus-extended framing and of the Rg cutoff
+  below, nothing else.
+
+## Protocol
+
+| Setting | Reference choice | Here |
+|---|---|---|
+| Engine / ligand force field | Amber 18, GAFF, geometry pre-optimized in Gaussian | OpenMM 8, OpenFF Sage 2.2 with AM1-BCC charges |
+| Solvent | explicit chloroform, ~3000 molecules, truncated octahedron | explicit chloroform via packmol, plus water as a polar reference |
+| Production | 100 ns after equilibration | 50-100 ns, `--prod-ns` |
+| Replicas | 3 | 3, independent velocity seeds |
+| Ensemble | 300 K, PBC, ~10,000 snapshots per trajectory | 300 K / 1 bar NPT, 10 ps per frame |
+| Convergence | RMSD, converged within 5-10 ns | RMSD to the first frame plus replica-mean spread |
+| Analyses | Rg (cpptraj), 3D PSA (PyMOL), intramolecular H-bonds, PMI shape, PCA and K-means into 5 clusters | Rg, 3D PSA (mdtraj SASA over N, O and polar H), H-bonds, PCA and K-means |
+
+Chloroform stands in for the membrane interior: its dielectric constant of 4.8
+is close to what a molecule sees while crossing a bilayer.
+
+## Yardsticks
+
+- **Rg below 7 A** marks the folded, passively permeable regime. This cutoff is
+  from the 2021 NMR paper, on a single VHL PROTAC, and it does not separate the
+  compounds in the 2022 MD paper.
+- **Mean Rg alone does not discriminate.** In the 2022 MD paper:
+
+  | compound | P_passive (nm/s) | dominant Rg | compact local minimum |
+  |---|---|---|---|
+  | PROTAC 1, most permeable | 30 ± 1.5 | just over 8 A | 5.6 A |
+  | PROTAC 2 | 11 ± 1.7 | just over 7 A | 5.5 A |
+  | PROTAC 3, least permeable | 6 ± 1.4 | 7-9.5 A, extended | none |
+
+  Their most permeable compound sits mainly just above 8 A, overlapping their
+  worst. What separates the two is whether a compact minimum near 5.5 A is
+  accessible at all: PROTACs 1 and 2 have one, PROTAC 3 does not. Report the Rg
+  distribution and the compact-state population, which is what `rg_basins.py`
+  computes, rather than the mean. Absolute Rg is also not strictly transferable
+  across chemical series; theirs is CRBN/BRD4, the runs here are VHL/EGFR.
+- **3D PSA** rises as permeability falls: 190-265 A^2 for the two more permeable
+  compounds against 290-330 A^2 for the poorly permeable one. The rough cutoff
+  for low-to-moderate permeability is 200-210 A^2, from the 2021 paper. Absolute
+  values depend on the polar-atom selection; `validate_psa.py` and
+  `psa_method_probe.py` pin down where this convention sits relative to theirs.
+- Permeability correlates inversely with 3D PSA and with intramolecular H-bond
+  count.

CupOFMoCA-PROTAC/md/render_3d.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python
+"""Ball-and-stick renders of two PROTAC conformations from a replica trajectory:
+the most extended early frame beside the most collapsed late frame. Both frames
+are also written out as PDBs for PyMOL / VMD / ChimeraX.
+
+Usage:
+    python render_3d.py --rep egfrvhl_rank4/chloroform/rep1
+"""
+import argparse, glob, os
+import numpy as np
+import mdtraj as md
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d.art3d import Line3DCollection
+
+# CPK element colors and relative sizes
+CPK = {"C": ("#4d4d4d", 55), "N": ("#3050f8", 70), "O": ("#ff2d2d", 70),
+       "S": ("#e6c200", 95), "Cl": ("#1fd01f", 95), "F": ("#6fd0c0", 60),
+       "H": ("#dddddd", 20)}
+
+def draw(ax, xyz, syms, bonds, title):
+    xyz = xyz - xyz.mean(0)
+    segs = [[xyz[i], xyz[j]] for i, j in bonds]
+    ax.add_collection3d(Line3DCollection(segs, colors="#888888", linewidths=1.6))
+    for el in set(syms):
+        m = [k for k, s in enumerate(syms) if s == el]
+        c, sz = CPK.get(el, ("#cc44cc", 60))
+        ax.scatter(xyz[m, 0], xyz[m, 1], xyz[m, 2], c=c, s=sz,
+                   edgecolors="white", linewidths=0.4, depthshade=True)
+    ax.set_title(title, fontsize=12, weight="bold", color="#222", pad=0)
+    r = np.abs(xyz).max() * 1.05
+    ax.set_xlim(-r, r); ax.set_ylim(-r, r); ax.set_zlim(-r, r)
+    ax.set_box_aspect((1, 1, 1)); ax.axis("off")
+
+def main():
+    p = argparse.ArgumentParser()
+    p.add_argument("--rep", required=True, help="replica directory, e.g. <name>/<solvent>/rep1")
+    p.add_argument("--name", default=None, help="run name (default: the run directory's name)")
+    p.add_argument("--report-ps", type=float, default=10.0, help="DCD frame interval")
+    a = p.parse_args()
+    rep = a.rep.rstrip("/")
+    name = a.name or os.path.basename(os.path.dirname(os.path.dirname(rep)))
+
+    solvated = glob.glob(os.path.join(rep, os.pardir, "*_solvated.pdb"))[0]
+    traj = md.load(os.path.join(rep, f"{name}_prod.dcd"), top=solvated)
+    top = traj.topology
+    # the PROTAC is the one non-water residue with many atoms; water and ions are tiny
+    lig = [at.index for res in top.residues
+           if not res.is_water and res.n_atoms > 5 for at in res.atoms]
+    heavy = [i for i in lig if top.atom(i).element.symbol != "H"]
+    lset = set(heavy)
+    remap = {g: k for k, g in enumerate(heavy)}
+    bonds = [(remap[b0.index], remap[b1.index]) for b0, b1 in top.bonds
+             if b0.index in lset and b1.index in lset]
+    syms = [top.atom(i).element.symbol for i in heavy]
+
+    sub = traj.atom_slice(heavy)
+    rg = md.compute_rg(sub)  # nm
+    n = len(rg); early = slice(0, n // 3); late = slice(2 * n // 3, n)
+    fe = np.arange(n)[early][np.argmax(rg[early])]     # extended
+    fc = np.arange(n)[late][np.argmin(rg[late])]       # collapsed
+    xyz_A = sub.xyz * 10.0  # nm -> Angstrom
+    ns = a.report_ps / 1000.0
+
+    fig = plt.figure(figsize=(13, 6.5), dpi=150); fig.patch.set_facecolor("white")
+    ax1 = fig.add_subplot(121, projection="3d")
+    draw(ax1, xyz_A[fe], syms, bonds, f"Extended  (t={fe*ns:.1f} ns,  Rg={rg[fe]:.2f} nm)")
+    ax2 = fig.add_subplot(122, projection="3d")
+    draw(ax2, xyz_A[fc], syms, bonds, f"Collapsed  (t={fc*ns:.1f} ns,  Rg={rg[fc]:.2f} nm)")
+    fig.suptitle(f"Free-PROTAC conformations from MD - {name}  (heavy atoms, H hidden)",
+                 fontsize=13, weight="bold", color="#222", y=0.97)
+    out = os.path.join(rep, f"{name}_3d.png")
+    fig.savefig(out, facecolor="white", bbox_inches="tight"); print("wrote", out)
+
+    sub[fe].save_pdb(os.path.join(rep, f"{name}_extended.pdb"))
+    sub[fc].save_pdb(os.path.join(rep, f"{name}_collapsed.pdb"))
+    print(f"extended frame {fe} (Rg {rg[fe]:.2f}), collapsed frame {fc} (Rg {rg[fc]:.2f})")
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/rg_basins.py

@@ -0,0 +1,123 @@
+#!/usr/bin/env python
+"""Rg free-energy profiles and basin populations for one or more finished runs.
+
+Mean Rg does not separate permeable from non-permeable PROTACs in the J. Med.
+Chem. 2022 study: their most permeable compound sits mainly just above 8 A,
+overlapping their least permeable one at 7-9.5 A. What separates them is whether
+a compact minimum near 5.5 A is populated at all. This script computes, per
+compound and solvent,
+
+    PMF(Rg) = -kT ln P(Rg)
+
+locates its basins (local minima), and reports each basin's position and
+population, plus the fraction of frames below 6 and 7 A.
+
+Ligand selection and the Rg calculation match analyze_conformations.py exactly
+(non-water residue with >5 atoms, md.compute_rg on the centred ligand-only
+trajectory).
+
+Usage:
+    python rg_basins.py egfrvhl_rank4 ms39_ref --solvents chloroform water
+"""
+import argparse, glob, os
+import numpy as np
+import mdtraj as md
+from scipy.stats import gaussian_kde
+from scipy.signal import find_peaks
+import matplotlib; matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+KT = 0.593  # kcal/mol at 300 K
+
+
+def pooled_rg(run_dir, solvent):
+    """Rg in Angstrom, pooled over replicas."""
+    name = os.path.basename(run_dir.rstrip("/"))
+    tops = glob.glob(os.path.join(run_dir, solvent, f"{name}_*_solvated.pdb"))
+    dcds = sorted(glob.glob(os.path.join(run_dir, solvent, "rep*", f"{name}_prod.dcd")))
+    if not tops or not dcds:
+        return None
+    out = []
+    for d in dcds:
+        tr = md.load(d, top=tops[0])
+        lig = [a.index for r in tr.topology.residues
+               if not r.is_water and r.n_atoms > 5 for a in r.atoms]
+        lt = tr.atom_slice(lig)
+        lt.center_coordinates()
+        out.append(md.compute_rg(lt) * 10.0)          # nm -> A
+    return np.concatenate(out)
+
+
+def basins(rg, prom_frac=0.05):
+    """Basins = peaks of P(Rg). Returns (grid, pmf, [(rg_position, population)])."""
+    grid = np.linspace(rg.min() - 0.3, rg.max() + 0.3, 400)
+    dens = gaussian_kde(rg, bw_method=0.12)(grid)
+    pmf = -KT * np.log(np.clip(dens, 1e-12, None))
+    pmf -= pmf.min()
+    pk, _ = find_peaks(dens, prominence=prom_frac * dens.max())
+    if len(pk) == 0:
+        pk = np.array([int(np.argmax(dens))])
+    # valley boundaries between adjacent peaks assign frames to basins
+    edges = [rg.min() - 1e-6]
+    for a, b in zip(pk[:-1], pk[1:]):
+        edges.append(grid[a + int(np.argmin(dens[a:b]))])
+    edges.append(rg.max() + 1e-6)
+    out = []
+    for i, p in enumerate(pk):
+        pop = float(((rg > edges[i]) & (rg <= edges[i + 1])).mean())
+        out.append((float(grid[p]), pop))
+    return grid, pmf, out
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("runs", nargs="+", help="run directories, one per compound")
+    ap.add_argument("--solvents", nargs="+", default=["chloroform", "water"])
+    ap.add_argument("--plot-solvent", default="chloroform",
+                    help="solvent whose PMFs go into the figure")
+    ap.add_argument("--out", default="rg_basins.png")
+    a = ap.parse_args()
+
+    print(f"{'compound':22s}{'solv':6s}{'mean':>7s}{'basins (Rg A, pop%)':>44s}{'<6A':>7s}{'<7A':>7s}")
+    print("-" * 96)
+    results = {}
+    for run in a.runs:
+        label = os.path.basename(run.rstrip("/"))
+        for sol in a.solvents:
+            rg = pooled_rg(run, sol)
+            if rg is None:
+                continue
+            grid, pmf, bs = basins(rg)
+            results[(label, sol)] = (rg, grid, pmf, bs)
+            btxt = "  ".join(f"{p:.2f}({100*w:.0f}%)" for p, w in bs)
+            print(f"{label:22s}{sol[:5]:6s}{rg.mean():7.2f}{btxt:>44s}"
+                  f"{100*(rg<6.0).mean():6.0f}%{100*(rg<7.0).mean():6.0f}%")
+
+    have = [k for k in results if k[1] == a.plot_solvent]
+    if not have:
+        return
+    fig, ax = plt.subplots(figsize=(11, 6.5), dpi=150)
+    fig.patch.set_facecolor("white")
+    cmap = plt.get_cmap("viridis")
+    for i, key in enumerate(have):
+        _, grid, pmf, _ = results[key]
+        ax.plot(grid, pmf, lw=2.2, color=cmap(i / max(1, len(have) - 1)), label=key[0])
+    ax.axvspan(5.4, 5.7, color="#009E73", alpha=0.12)
+    ax.text(5.55, ax.get_ylim()[1] * 0.94, "reference compact\nminimum 5.5-5.6 A",
+            ha="center", fontsize=8.5, color="#009E73", weight="bold")
+    ax.axvspan(7.0, 9.5, color="#C0392B", alpha=0.07)
+    ax.text(8.25, ax.get_ylim()[1] * 0.94, "reference least-permeable\ncompound 7-9.5 A",
+            ha="center", fontsize=8.5, color="#C0392B", weight="bold")
+    ax.set_xlabel("Radius of gyration (A)")
+    ax.set_ylabel("PMF  -kT ln P(Rg)   (kcal/mol)")
+    ax.set_title(f"Rg free-energy profiles in {a.plot_solvent}",
+                 fontsize=13, weight="bold", loc="left")
+    ax.set_ylim(0, 3.2); ax.legend(fontsize=8.5, frameon=False, ncol=2)
+    ax.grid(alpha=0.25)
+    fig.tight_layout()
+    fig.savefig(a.out, facecolor="white")
+    print(f"\nwrote {a.out}")
+
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/run_candidate.sh

@@ -0,0 +1,73 @@
+#!/bin/bash
+# Detached driver for one PROTAC candidate: chloroform 3 x 50 ns, analysis,
+# then water 3 x 50 ns, analysis. The chloroform AM1-BCC charge cache is staged
+# into the water run so sqm is only paid once.
+#
+#   run_candidate.sh <NAME> <GPU> <SMILES> [WAIT_LOGFILE] [WAIT_MARKER]
+#
+# With WAIT_LOGFILE and WAIT_MARKER the job queues instead of starting: it polls
+# that log until the marker appears (the predecessor on the same GPU printed
+# CANDIDATE_DONE), so two jobs never share a card. Waiting greps a file rather
+# than process names, which would otherwise match this script's own cmdline.
+# WAIT_LOGFILE resolves against this script's directory, not the caller's cwd,
+# and after MAXWAIT the job stops waiting and starts anyway, which can put two
+# jobs on one card.
+set -u
+
+NAME="$1"; GPU="$2"; SMI="$3"; WLOG="${4:-}"; WMARK="${5:-}"
+MD="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+CONDA_ENV="${CONDA_ENV:-protacmd}"
+MAXWAIT=$((14*3600))     # never queue longer than this
+
+if [ -n "${CONDA_SH:-}" ]; then
+  source "$CONDA_SH"
+elif [ -n "${CONDA_EXE:-}" ]; then
+  source "$(dirname "$(dirname "$CONDA_EXE")")/etc/profile.d/conda.sh"
+fi
+conda activate "$CONDA_ENV"
+cd "$MD"
+
+log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $*"; }
+
+log "CANDIDATE_START name=$NAME gpu=$GPU"
+
+if [ -n "$WLOG" ] && [ -n "$WMARK" ]; then
+  log "QUEUED on GPU $GPU: waiting for '$WMARK' in $WLOG ..."
+  waited=0
+  until grep -q "$WMARK" "$MD/$WLOG" 2>/dev/null; do
+    sleep 60; waited=$((waited+60))
+    if [ "$waited" -ge "$MAXWAIT" ]; then
+      log "waited ${waited}s without seeing '$WMARK', starting anyway"; break
+    fi
+    [ $((waited % 1800)) -eq 0 ] && log "  ... still waiting (${waited}s)"
+  done
+  log "predecessor finished after ${waited}s, starting $NAME on GPU $GPU"
+fi
+
+nvidia-smi --query-gpu=index,utilization.gpu,memory.used --format=csv,noheader | sed 's/^/[gpu] /'
+
+run_solvent() {
+  local sol="$1"
+  log "=== $NAME / $sol : 3 x 50 ns START ==="
+  python protac_md.py --solvent "$sol" --replicas 3 --prod-ns 50 \
+    --smiles "$SMI" --name "$NAME" --gpu "$GPU"
+  local rc=$?
+  log "=== $NAME / $sol : MD finished rc=$rc ==="
+  if [ $rc -eq 0 ]; then
+    log "--- $NAME / $sol : analysis START ---"
+    python analyze_conformations.py --dir "$NAME/$sol" --name "$NAME"
+    log "--- $NAME / $sol : analysis finished rc=$? ---"
+  else
+    log "$NAME / $sol MD failed (rc=$rc), skipping analysis"
+  fi
+}
+
+run_solvent chloroform
+CH="$MD/$NAME/chloroform/ff_cache.json"
+if [ -s "$CH" ]; then
+  mkdir -p "$MD/$NAME/water"; cp -f "$CH" "$MD/$NAME/water/ff_cache.json"
+  log "staged charge cache -> $NAME/water/ff_cache.json"
+fi
+run_solvent water
+
+log "CANDIDATE_DONE name=$NAME"

CupOFMoCA-PROTAC/md/ternary_span.py

@@ -0,0 +1,111 @@
+#!/usr/bin/env python
+"""Warhead-to-E3 span distribution from the water ensembles.
+
+Per frame, the distance between the centroid of the warhead core (the group that
+occupies the target pocket) and the centroid of the E3 ligand core. In a
+productive ternary complex that span has to bridge the two pockets, so the
+distribution shows which separations a linker can hold. Water, not chloroform:
+the ternary complex forms in the cytosol.
+
+This is a description of reach, not a degradation score; scoring it needs a
+target ternary geometry from docking. Replica spread is printed alongside so
+poorly converged runs are visible.
+
+Default SMARTS are for the EGFR-VHL series (anilinoquinazoline warhead,
+4-hydroxyproline E3 anchor); override with --warhead-smarts / --e3-smarts.
+
+Usage:
+    python ternary_span.py egfrvhl_rank4 ms39_ref --out span.png
+"""
+import argparse, glob, os
+import numpy as np
+import mdtraj as md
+from rdkit import Chem
+from scipy.stats import gaussian_kde
+import matplotlib; matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+WH_SMARTS = "c1cc2ncncc2cc1"            # quinazoline bicyclic, target pocket
+E3_SMARTS = "[#6]1[#6][#6](O)[#6][#7]1"  # 4-hydroxypyrrolidine, VHL pocket
+
+
+def anchors(sdf, wh_smarts, e3_smarts):
+    m = Chem.MolFromMolFile(sdf, removeHs=False)
+    wh = list(m.GetSubstructMatch(Chem.MolFromSmarts(wh_smarts)))
+    e3 = list(m.GetSubstructMatch(Chem.MolFromSmarts(e3_smarts)))
+    syms = [a.GetSymbol() for a in m.GetAtoms()]
+    return wh, e3, syms
+
+
+def spans_for_run(run, solvent, wh_smarts, e3_smarts):
+    """Per-replica span arrays (A), or None if the run can't be used."""
+    name = os.path.basename(run.rstrip("/"))
+    tops = glob.glob(os.path.join(run, solvent, "*_solvated.pdb"))
+    dcds = sorted(glob.glob(os.path.join(run, solvent, "rep*", f"{name}_prod.dcd")))
+    if not tops or not dcds:
+        print(f"{name:14s}  no {solvent} data")
+        return None
+    wh, e3, sdf_syms = anchors(os.path.join(run, f"{name}.sdf"), wh_smarts, e3_smarts)
+    if not wh or not e3:
+        print(f"{name:14s}  SMARTS match failed (wh={len(wh)} e3={len(e3)})")
+        return None
+    out = []
+    for d in dcds:
+        tr = md.load(d, top=tops[0])
+        lig = [a.index for r in tr.topology.residues
+               if not r.is_water and r.n_atoms > 5 for a in r.atoms]
+        sub = tr.atom_slice(lig)
+        if [a.element.symbol for a in sub.topology.atoms] != sdf_syms:
+            print(f"{name:14s}  SDF/MD atom-order mismatch, skipping")
+            return None
+        xyz = sub.xyz * 10.0                       # nm -> A
+        out.append(np.linalg.norm(xyz[:, wh, :].mean(1) - xyz[:, e3, :].mean(1), axis=1))
+    return out
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("runs", nargs="+", help="run directories, one per compound")
+    ap.add_argument("--solvent", default="water")
+    ap.add_argument("--warhead-smarts", default=WH_SMARTS)
+    ap.add_argument("--e3-smarts", default=E3_SMARTS)
+    ap.add_argument("--out", default="ternary_span.png")
+    a = ap.parse_args()
+
+    fig, ax = plt.subplots(figsize=(11, 6.5), dpi=150)
+    fig.patch.set_facecolor("white")
+    cmap = plt.get_cmap("viridis")
+    print(f"{'compound':14s}{'mean span':>10s}{'sd':>6s}{'min':>6s}{'max':>6s}"
+          f"{'range':>7s}{'rep spread':>12s}")
+    print("-" * 67)
+    drawn = 0
+    for i, run in enumerate(a.runs):
+        label = os.path.basename(run.rstrip("/"))
+        per_rep = spans_for_run(run, a.solvent, a.warhead_smarts, a.e3_smarts)
+        if not per_rep:
+            continue
+        s = np.concatenate(per_rep)
+        spread = float(np.std([r.mean() for r in per_rep]))
+        print(f"{label:14s}{s.mean():10.1f}{s.std():6.1f}{s.min():6.1f}"
+              f"{s.max():6.1f}{s.max()-s.min():7.1f}{spread:12.1f}")
+        grid = np.linspace(3, 25, 300)
+        ax.plot(grid, gaussian_kde(s, bw_method=0.15)(grid), lw=2.2,
+                color=cmap(i / max(1, len(a.runs) - 1)),
+                label=f"{label} ({s.mean():.0f} A)")
+        drawn += 1
+    if not drawn:
+        return
+    ax.set_xlabel("warhead to E3 pharmacophore separation (A)")
+    ax.set_ylabel("probability density")
+    ax.set_title("Warhead to E3 span\n"
+                 f"centroid distance between the pocket-binding groups ({a.solvent})",
+                 fontsize=12.5, weight="bold", loc="left")
+    ax.legend(fontsize=8.5, frameon=False, ncol=2)
+    ax.grid(alpha=0.25)
+    fig.tight_layout()
+    fig.savefig(a.out, facecolor="white")
+    print(f"\nwrote {a.out}")
+
+
+if __name__ == "__main__":
+    main()

CupOFMoCA-PROTAC/md/validate_psa.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python
+"""Sanity check for the 3D PSA code path used by psa_ensemble.py.
+
+Runs the same element-based PSA (N, O, polar H; Bondi radii; 1.4 A probe; mdtraj
+shrake_rupley) on grazoprevir, whose solution-accessible 3D PSA is reported as
+144-205 A^2 (174 A^2 for the crystal conformer) using a charge-threshold
+selection in PyMOL. Agreement means the two conventions land on the same scale,
+so PROTAC numbers from psa_ensemble.py can be read against published values.
+
+Needs no finished run: grazoprevir and its conformers are generated here, so it
+takes seconds.
+
+Usage:
+    python validate_psa.py
+"""
+import numpy as np, tempfile, os
+from rdkit import Chem
+from rdkit.Chem import AllChem
+import mdtraj as md
+
+# grazoprevir, PubChem CID 44603531 (SMILES field, verbatim)
+SMI = "CC(C)(C)[C@H]1C(=O)N2C[C@@H](C[C@H]2C(=O)N[C@@]3(C[C@H]3C=C)C(=O)NS(=O)(=O)C4CC4)OC5=NC6=C(C=CC(=C6)OC)N=C5CCCCC[C@@H]7C[C@H]7OC(=O)N1"
+
+m = Chem.AddHs(Chem.MolFromSmiles(SMI))
+p = AllChem.ETKDGv3(); p.randomSeed = 1; p.useRandomCoords = True
+cids = AllChem.EmbedMultipleConfs(m, numConfs=25, params=p)
+AllChem.MMFFOptimizeMoleculeConfs(m)
+print(f"grazoprevir: {m.GetNumAtoms()} atoms, {len(cids)} conformers embedded")
+
+def is_polar(atom):
+    s = atom.GetSymbol()
+    if s in ("N", "O"): return True
+    if s == "H":
+        return any(nb.GetSymbol() in ("N", "O") for nb in atom.GetNeighbors())
+    return False
+polar = [a.GetIdx() for a in m.GetAtoms() if is_polar(a)]
+print(f"polar atoms (N,O,polar-H): {len(polar)}")
+
+vals = []
+for cid in cids:
+    pdb = Chem.MolToPDBBlock(m, confId=cid)
+    with tempfile.NamedTemporaryFile("w", suffix=".pdb", delete=False) as fh:
+        fh.write(pdb); path = fh.name
+    t = md.load(path); os.unlink(path)
+    sasa = md.shrake_rupley(t, mode="atom", probe_radius=0.14)[0]  # nm^2
+    vals.append(sasa[polar].sum() * 100.0)  # A^2
+vals = np.array(vals)
+rg = []
+for cid in cids:
+    conf = m.GetConformer(cid)
+    xyz = np.array([list(conf.GetAtomPosition(i)) for i in range(m.GetNumAtoms())])
+    xyz -= xyz.mean(0); rg.append(np.sqrt((xyz**2).sum(1).mean()))
+rg = np.array(rg)
+
+print(f"\nelement-based 3D PSA over {len(vals)} conformers:")
+print(f"  min {vals.min():.0f}  median {np.median(vals):.0f}  max {vals.max():.0f} A2")
+print(f"  (most folded conformer, Rg={rg.min():.2f} A): PSA = {vals[np.argmin(rg)]:.0f} A2")
+print(f"\nreported (PyMOL, |q|>1 selection): grazoprevir SA 3D PSA = 144-205 A2, crystal 174")
+print(f"  grazoprevir 2D TPSA (PubChem) = 204 A2")
+inrange = ((vals >= 140) & (vals <= 210)).mean() * 100
+print(f"\n-> {inrange:.0f}% of the conformers fall in the reported 144-205 range")

CupOFMoCA-PROTAC/requirements.txt

@@ -0,0 +1,18 @@
+hydra-core==1.3.2
+imageio==2.31.1
+matplotlib==3.7.1
+networkx==2.8.7
+numpy==1.23
+omegaconf==2.3.0
+overrides==7.3.1
+pandas==1.4
+pyemd==1.0.0
+PyGSP==0.5.1
+pytorch_lightning==2.0.4
+scipy==1.11.0
+setuptools==68.0.0
+torch_geometric==2.3.1
+torchmetrics==0.11.4
+tqdm==4.65.0
+wandb==0.15.4
+seaborn

CupOFMoCA-PROTAC/results/README.md

@@ -0,0 +1,46 @@
+# Reported results
+
+The generation outputs and scored summaries behind the PROTAC tables. These are the
+runs themselves, not a re-derivation: the aggregates here are what the paper reports.
+
+All runs use the optimized objective, recorded in the logs as the five-slot vector
+`1 0 4 2 4` = `[classifier, morgan_fp, SA, chemotype, connectivity]`. The classifier is
+applied as a hard mask and the Morgan-FP term is zero, so the three live weights are
+`SA 4, chemotype 2, connectivity 4` — the `--weights 4.0 2.0 4.0` the current
+`scripts/generate.py` takes. Seeds are 42 / 123 / 456, 100 candidates each.
+
+## `ablation_all/` — EGFR-VHL
+
+Five conditions × three seeds. `results.csv` is per-seed, `AGGREGATE.txt` is the
+pooled mean ± std (population std, `ddof=0`).
+
+| condition | what it is | appears as |
+|---|---|---|
+| `both` | hard constraints + soft guidance; the full configuration | Table 3 EGFR-VHL, Table J8 "Both", Table H1 "Fine-tuned" |
+| `hard` | validity gate only, no objective guidance | Table J8 "Hard constraints only" |
+| `soft` | objective guidance only, no validity gate | Table J8 "Soft guidance only" |
+| `accept_on` | full configuration plus the monotonic acceptance test | Table J3 "Acceptance on" |
+| `base` | pre-fine-tuning DeFoG checkpoint | Table H1 "Base" |
+
+## `ablation_targets/` — BRD9-VHL and CDK6-CRBN
+
+Per-target directories hold the same per-seed `.smi` outputs plus `ftguid_scored.csv`,
+the per-molecule scored table. At the top level:
+
+- `asm_valid.csv` — assembly validity per target × condition × seed
+- `box_results.csv`, `phaseA_eval.csv` — property-window summaries
+- `dm_ci.txt` — DegradeMaster mean, 95% CI, median and fraction ≥ 0.5 per target
+- `VALIDATION.txt`, `AGGREGATE.txt` — pooled summaries
+
+## Excluded
+
+Per-step sampling traces (`*_steps.json`, ~288 MB) and driver logs (`*.gen.log`) are
+not included. Re-running `scripts/generate.py` with the seed and weights above
+regenerates them.
+
+## Note on counts
+
+`dm_ci.txt` reports the DegradeMaster pool as n=281 (BRD9-VHL) and n=265 (CDK6-CRBN),
+while Table 3 states 247 and 249 assembly-valid molecules. The DegradeMaster pool is
+therefore not identical to the assembly-valid set; check which population each column
+was computed over before quoting these numbers.

CupOFMoCA-PROTAC/results/ablation_all/AGGREGATE.txt

@@ -0,0 +1,9 @@
+OPTIMIZED weights 1 0 4 2 4  (both = accept_off = finetuned baseline)
+
+cond       asm_valid       SA            MW_in_window%   DegradeMaster 
+-----------------------------------------------------------------------
+both       85.0 ± 3.6      2.8 ± 0.0     94.7 ± 1.9      0.5 ± 0.0     
+hard       11.0 ± 3.7      2.5 ± 0.0     99.3 ± 0.5      0.5 ± 0.0     
+soft       0.3 ± 0.5       4.0 ± 0.1     97.0 ± 1.4      0.6 ± 0.0     
+accept_on  58.7 ± 3.4      3.0 ± 0.0     94.7 ± 1.2      0.5 ± 0.0     
+base       78.7 ± 5.4      3.6 ± 0.2     48.7 ± 2.5      0.5 ± 0.0     

CupOFMoCA-PROTAC/results/ablation_all/PROGRESS.txt

@@ -0,0 +1,9 @@
+start Sun Jul 26 10:40:29 PM EDT 2026
+done [both:42 both:123] @ Sun Jul 26 10:48:02 PM EDT 2026
+done [both:456 hard:42] @ Sun Jul 26 10:56:07 PM EDT 2026
+done [hard:123 hard:456] @ Sun Jul 26 11:04:34 PM EDT 2026
+done [soft:42 soft:123] @ Sun Jul 26 11:12:35 PM EDT 2026
+done [soft:456 accept_on:42] @ Sun Jul 26 11:20:41 PM EDT 2026
+done [accept_on:123 accept_on:456] @ Sun Jul 26 11:28:03 PM EDT 2026
+done [base:42 base:123] @ Sun Jul 26 11:43:03 PM EDT 2026
+done [base:456 ] @ Sun Jul 26 11:57:37 PM EDT 2026

CupOFMoCA-PROTAC/results/ablation_all/accept_on_s123.smi

@@ -0,0 +1,100 @@
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+AssemblyReady O=C(O)CC(O)(CCCCCN1CC(C(=O)O)C1)C1CCC1
+INVALID
+AssemblyReady O=C(O)CCCOCCOCC(=O)O
+DISCONNECTED CC(=O)O.CC(O)C(=O)O
+AssemblyReady CCCC(C(=O)O)C(=O)O
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+DISCONNECTED C.C=C=C.CC1CC1.O=CO.O=CO
+AssemblyReady O=C(O)C1CC(C(=O)O)C1
+INVALID
+AssemblyReady CC(C)CC1=CC(N)(CC(COCC(=O)O)CC(=O)O)CC=C1
+AssemblyReady CC(C)(OC1CC1)C(CCCCCC(=O)O)OCNC(=O)C(=O)O
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+AssemblyReady CC(C)(CCCCC(=O)O)CCOCC(=O)O
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+AssemblyReady CCC(C)C(CCCC(=O)O)C(=O)O
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CupOFMoCA-PROTAC/results/ablation_all/accept_on_s123_clean.smi

@@ -0,0 +1,100 @@
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+AssemblyReady CCCC(=O)NC(C(=O)O)=C(C(=O)O)C(=O)OCC
+AssemblyReady O=C(O)CCCC(=O)C(=O)O
+DISCONNECTED C.C=NOC.CC(=O)O.CCOO.O=CO
+DISCONNECTED CCNCN.CNC1=CC1.N.O=CO.O=CO
+DISCONNECTED CCCN.O=CO.O=CO
+AssemblyReady CCCC(CC(C)=CC(=O)O)C(=O)O
+DISCONNECTED C.N=O.O=C(O)CCC(=O)O
+DISCONNECTED CCC(C)(C)OO.NC(=O)O.O=CO

CupOFMoCA-PROTAC/results/ablation_all/accept_on_s456_clean.smi

@@ -0,0 +1,100 @@
+INVALID
+CCOC(C(C)C)C1CCOC(C(C(=O)O)C(=O)O)C(C)=C1COC
+CCC(CC(=O)O)C(=O)O
+CCC(C)OCCCC(C)=C(C(=O)O)C(=O)O
+O=C(O)CCCNC(=O)COCC(=O)O
+INVALID
+O=CC(COC(=O)O)=C(COCCCO)OCC(=O)O
+C.C.CN.NC(=O)O.O=CO
+C.C.C.C=COC(N)OCC(C)C.CC.O=C(O)OO.O=CO.OO
+CCCCN(CC(=O)O)CC(=O)O
+COC(=CCC(=O)O)OC1CCC(Cc2cn(CC(=O)O)nn2)CC1
+CCCCN.O=CO.O=CO
+O=CCC(CCCO)(CCCC(=O)O)C(=O)O
+C.C.CCC.O.O=CO.O=CO
+C.C.C.O=C(O)O.O=CO
+CC(C)C.CCC(=O)O.O.O=C(O)CCCN1CC1
+O=C(O)CCC(=O)N(CC(=O)O)C1CCC1
+Cc1cc(CC(=O)C(=O)O)cc(C(=O)O)c1
+O=C(O)CCC1(CC(=O)O)CCCC(O)CCC1
+CC(C(=O)O)C(N)C(=O)O
+CCCCCCC(CCOCC(=O)O)C(=O)O
+C=CC.CCC(O)=C1C=CC1.O=CO.O=CO
+CC(C)CC(C(=O)O)C(=O)O
+NCCOC(CO)=C(CCC(=O)O)CC(=O)O
+C.C.CCCC#CCCC(C(=O)O)C(=O)O
+INVALID
+O=C(O)CC(CCO)(C(=O)O)N1CCCOCC1
+C.C.C.C.CO.CO.NCN.O=C(O)O.O=CO
+CC(C)(CCO)C1(C(=O)O)CC(O)(CCCC(=O)O)C1
+CCN(CCC(=O)O)CCC(=O)O
+CO.CO.O=C(O)CCC(=O)O
+C.C.C=NN.CCC.O=CO.O=CO
+C.C.CC.O=CO.O=CO
+COCC(O)(CCC(=O)O)C(=O)O
+CCCCCC(C(=O)O)=C(C(=O)O)N1CCN(C)CC1
+CC(C)(C)OC(CCC(=O)O)CC(=O)O
+O=C(O)CCCCN1CCCCOC(=O)C1CC(=O)O
+CCC(CC(=O)O)NCCCCC(=O)O
+CCC(CC)(CC(=O)O)C(=O)O
+NCc1cnn(CCOC(COCCOCCNC(=O)O)C(=O)O)c1
+CN(CCC(=C=C1CC1)CCCCCC(=O)O)CC(=O)O
+CC(=O)O.CCC(C)C(O)ON.O.O=CO
+Cc1cc(C(=O)O)c(C(=O)O)n1C
+NC(=CNCCCCC(=O)O)OCCC1(C(=O)O)OCCCNC=[SH]1
+C.C.C.COC.O.O=CO.O=CO
+CC.CCC.O=CO.O=CO
+N=C(CC(=O)O)N(CCCCCCCO)CCC(=O)O
+NC(CCCCCCCCC(=O)O)CCC(=O)O
+CC(=O)C(C(=O)O)C(=O)O
+CC1OC(C2(CCCC(=O)O)CC(CCC(=O)O)C2)O1
+C.C.C.NC(=O)O.O=CO
+CC(CCCCCC(=O)O)COCC(=O)O
+C.CO.O.O.O=CO.O=CO
+C.C.C.C.O=C(O)O.O=C(O)O
+CC(CC(=O)O)C(=O)O.O=O
+CCN.N.O=CO.O=CO
+C.CCC.CCNOC.CCOC(N)(O)C(=O)O.CO.O=CO
+CCOCCC(CCOCCOCCCC(C(=O)O)C(=O)O)OCC
+O=C(O)CCCCCN(CCO)CC(=O)O
+C.C.CN.O=CO.O=CO
+CCCCCCC(CCC(=O)O)C(=O)O
+CCC(COC)OCC(C)CCC(=O)O.O=C(O)O.OCO
+COCCNCNC(=CC(=O)O)C(=O)O
+C.C.C.CNC.O=CO.O=CO
+CCCOCCCCCCC(CC(=O)O)CC(=O)O
+CCC(CC(=O)O)C(=O)O
+CCN(C(=O)O)C(CC(CO)N(N)CC(=O)O)OC
+C.C.CC.O.O=CO.O=CO
+O=C(O)C=C(C(=O)O)C(=O)O
+C.CC.NC(=O)O.O=CO
+CCC(CCC(CO)CO)(C(=O)O)C(=O)O
+CC(C)(CC(=O)O)C(=O)O
+CC(=CCCCCCCCC(=O)O)CCC(=O)O
+CC(CO)(CC(=O)O)C(=O)O
+CC(=O)CCCNC1(CC(=O)O)CCCCCC(C(=O)O)CC1
+C=CCCCCCCC(C)(CC(=O)O)CC(=O)O
+CCOC(C(=CNC)NCOC)=C(C(=O)O)C(=O)O
+CCCC(C(=O)O)C(=O)O
+O=C(O)CCCOCCNCC(=O)O
+C.C.C.N.O=CO.O=CO
+C.CCOC(C)(N)CCC(=O)O.N.N.N.NO.O.O=CO
+C.C.CC.O=CO.O=CO.O=COO
+CC(CCC(=O)O)=C(C)C(=O)O
+CC(C)CCCCCN(CC(=O)O)C(=O)C(=O)O
+O=C(O)CCCC(CC(=O)O)=C1CCCCCC1
+NCCC(CC(=O)O)C(=O)O
+CC(C)(C(=O)O)C(=O)NCCCCC(=O)O
+O=C(O)CCCCCCCCC(=O)O
+CCCCC(CCC1CN(CCC(=O)O)CCN1)C(=O)O
+CC(C)C(C)(C(=O)O)C(=O)O
+CC(CCNC(=O)C(=O)O)C(=O)O
+C.C.CCOC(=O)O.CN.CN(C)C(=O)O.N.NCO.O
+CCCC(=O)NC(C(=O)O)=C(C(=O)O)C(=O)OCC
+O=C(O)CCCC(=O)C(=O)O
+C.C=NOC.CC(=O)O.CCOO.O=CO
+CCNCN.CNC1=CC1.N.O=CO.O=CO
+CCCN.O=CO.O=CO
+CCCC(CC(C)=CC(=O)O)C(=O)O
+C.N=O.O=C(O)CCC(=O)O
+CCC(C)(C)OO.NC(=O)O.O=CO

CupOFMoCA-PROTAC/results/ablation_all/base_s123.smi

@@ -0,0 +1,100 @@
+AssemblyReady O=C(O)CCN(C(=O)Nc1cccc(C(=O)O)c1)c1cc2ccc1-2
+INVALID
+AssemblyReady CCCOc1sc(CCC(=O)NC(CN=CN)C(=O)O)cc1C(=O)O
+INVALID
+AssemblyReady Cc1cc(C(O)c2ccc(NC(=O)C(=O)O)cc2)cc(C(=O)O)c1O
+INVALID
+AssemblyReady COC12C=C3C=C4OCOC41C1C=CCC(C3=C2C(=O)O)C1C(=O)O
+AssemblyReady O=C(O)c1ccc2c(c1)C1(O)N=c3ccc(C(=O)O)cc3=S1OC2=O
+INVALID
+AssemblyReady CC1=CC=CC(Nc2nncs2)(C(=O)O)C(CC(=O)O)=C1
+AssemblyReady CC(C)C(=O)OC(C1CCCO1)C(OC(=O)O)OC(=O)O
+AssemblyReady CC(C)(CC(=O)O)C(NC(=O)C=CC(N)C(=O)O)C(=O)NCCCO
+AssemblyReady CC(OC12C=CC3=C1C2(C(=O)O)N3S1(=O)=C2C3=CC=C2C1=C3)C(=O)O
+INVALID
+AssemblyReady Cc1c(Cc2cc(NC(=S)NCC(=O)O)cc(C(=O)O)c2)coc1O
+AssemblyReady CC(C)c1cc(S(=O)(=O)NCCC(=O)O)cc2c(CC(=O)O)noc12
+INVALID
+INVALID
+AssemblyReady CCN(C1=Cc2cc(C)ccc2N=C(C)O1)C(CCC(=O)O)C(=O)O
+AssemblyReady O=C(O)C=C(NC(=O)CCCCCCC(C(=O)O)C(=O)O)C(=O)O
+INVALID
+AssemblyReady COc1cccc(-c2cccc(CC(=O)O)c2C(=O)O)c1
+AssemblyReady COC12C=C3C=C4OC(CC(=O)O)CC(NC(=[SH]3)N1)C42C(=O)O
+INVALID
+AssemblyReady O=C(O)CCC(CC(=O)Oc1cc(C(F)F)cc(C(F)F)c1)C(=O)O
+AssemblyReady N#CCOC12C(=O)C1(O)c1ccc3cc1C32C(CC(=O)O)C(=O)O
+AssemblyReady O=C(O)c1ccc2c(c1)[N+]([O-])(O)c1cc(ccc1C(=O)O)C(=O)NO2
+AssemblyReady CN(C(=O)C(CC(=O)O)NC(=O)CCCO)C1CCCC(C(=O)O)C1
+AssemblyReady CNC(C(=O)O)C(O)(OCC(=O)O)C(=O)c1cccc2ccccc12
+AssemblyReady O=C(COC(C(=O)O)C(=O)O)c1ccc2c(c1)C(O)=C2O
+AssemblyReady O=CNN=CC(CC(C(=O)O)C(=O)O)C(=O)Oc1ccccc1
+AssemblyReady COCC1CCC(CC(C)(C)CC(=O)O)(NCCC(=O)O)CC1
+AssemblyReady O=C(O)C1=CC(C2CCCCC2)=C2C=CC2C(=O)C(O)C1C(=O)O
+DISCONNECTED CC(=O)O.NC(=O)c1c2cccc1N(c1ccc(C(=O)O)cc1)C2=O
+AssemblyReady O=C(O)C1=NC2=C3C4=CC=C(CC1=C2)C43CC(C(=O)O)C(O)C(=O)O
+AssemblyReady CCCC(=O)C1(CC)C=CC(O)=CC(C(=O)O)=C1C(=O)O
+INVALID
+INVALID
+AssemblyReady O=C(O)CNS(=O)(=O)C1=Cc2cc(C(=O)O)c3c(c2-3)Cn2cccc21
+INVALID
+INVALID
+AssemblyReady O=C(O)NCCC12C=CC(=C(C(S)C(=O)O)Cc3cccc1c3)C=C2
+INVALID
+AssemblyReady O=C(O)c1cccc(C2(C(=O)O)C(O)=COC=C2c2ccsc2)c1O
+INVALID
+DISCONNECTED CC=O.NCC(=O)O.O=C(O)O
+AssemblyReady O=C(O)c1cc(NC(=O)C2(C(=O)O)CCCCCC2)cs1
+AssemblyReady O=C(O)C(=O)Nc1ccc(C(=O)O)s1
+AssemblyReady O=C(O)OC1=CN2CC(Cc3cccc(c3)CC(C(=O)O)NC1=O)C2
+AssemblyReady CC(=O)OC(C=C(C)C(=O)O)CC(C)C(CCC(C)(C)O)CC(=O)O
+AssemblyReady O=C(O)CNC(=O)c1ccc(OCC(=O)O)cc1
+AssemblyReady COc1ccc(CC(Cc2ccccc2C)C(=O)O)cc1CC(=O)O
+AssemblyReady O=C(O)Cc1cccc2c3c([nH]cc(C(=O)O)ccc12)CCCC3=O
+AssemblyReady CCNS(=O)(=O)c1cnc2coc(C(=O)O)c(C(=CC(=O)O)CC)c1-2
+INVALID
+AssemblyReady O=C(O)C1(S)CC(Cc2ccccc2)(C(=O)O)C1
+AssemblyReady O=C(O)c1ccc(N2CCOCCN(CCCO)CC2)c(C(=O)O)c1
+INVALID
+AssemblyReady CC(C)(CO)NC(=O)CC(CC(=O)O)CC(=O)O
+AssemblyReady COc1ccc2nccc(C=C(SC=S)C(=O)O)c2c1C(=O)C(=O)O
+AssemblyReady O=C(O)C1=CS(=O)(=CC2CCC3=CCCCC3C2C(=O)O)C=CC1=O
+INVALID
+AssemblyReady O=C(O)Cc1ccc(F)cc1C(=O)O
+AssemblyReady CC12C(=O)C(C(=O)O)C(C(=O)O)C1(c1ccc(OCCO)cc1)C2=O
+INVALID
+AssemblyReady Cc1cccc(CCCCN(CCC(=O)O)C(=O)CCCC(=O)O)c1
+AssemblyReady CCC(NC(=O)O)c1cc(C(=O)O)ccc1CC(C)(C)CS(N)(=O)=O
+AssemblyReady O=C(O)CCC=c1ccc2c3c1c2C(C(=O)O)=N3
+AssemblyReady CCCCC(CC(=O)O)C1C(O)CC2C(O)OC(C(=O)O)CC2C1C
+INVALID
+INVALID
+AssemblyReady O=C(O)CC(N=C1CCN2CC3=C1C=CCCC2C(O)=C3O)C(=O)O
+AssemblyReady CC(=O)OCCC1(C(=O)O)C(C(C)C)NC(=O)C2(C(=O)O)CCCN21
+INVALID
+AssemblyReady NC(C(=O)O)C(=O)C(C(=O)O)=C(O)C(=O)Nc1ccccc1O
+AssemblyReady COC(=O)C(C)(C)NC(=O)c1cccc(C(CCC(=O)O)C(=O)O)c1
+INVALID
+AssemblyReady COc1ccc(C(=O)O)cc1NC(=Cc1cccs1)C(=O)O
+AssemblyReady CC(ON1CC(CO)OC(C(=O)O)C1OC(=O)O)C1(N=O)CCCO1
+AssemblyReady CCCC(C)(C)C(=O)C(C(=O)C(=O)O)=C(CO)C(=O)O
+AssemblyReady O=C(CCNc1ccc(O)cc1)Nc1c(C(=O)O)cccc1C(=O)O
+INVALID
+AssemblyReady CC(C)(CCCO)C(C(=O)O)c1ccccc1C(CC(=O)O)C(=O)O
+INVALID
+AssemblyReady O=C(O)C=C1C=C(F)C=C(C2=C(O)C(=O)C(=O)OC2=O)C1(O)C(=O)O
+AssemblyReady O=C(O)C1=CC(c2cccs2)=CC(c2ccccc2)=NC(C(=O)O)C1
+AssemblyReady CCC1=C(CCC(Oc2ccccc2C(=O)O)C(=O)O)NC(=O)CC1
+AssemblyReady O=C(O)CCN(C(=O)O)C(=O)C=C(c1ccccc1)c1ccccc1
+AssemblyReady O=C(O)CCCCNc1cc(C(=O)O)c2c(C(=O)O)c(F)ccc2c1
+AssemblyReady Cc1ccc(COCC(=O)O)c2c(C(=O)O)cc(OCCCO)cc12
+INVALID
+AssemblyReady COC(=O)C(CC(=O)O)CC(O)CC(C(=O)O)C(=O)C(C)(C)C(C)C
+AssemblyReady O=C(NC(CC1(C(=O)O)COCCCOC1)C(=O)O)C1CCCCC1
+AssemblyReady CC(=O)NCCCCNC(=O)NC(=CC1=C(O)C(C(=O)O)=C1)C(=O)O
+INVALID
+AssemblyReady CC(=O)OCC(=O)CC(CCC(=O)OCC(=O)NCC(=O)O)C(=O)O
+AssemblyReady O=C(O)CCCCN(CC1CCCCC1)CC1(C(=O)O)C=CC=C1
+AssemblyReady CC(CCC(CS)C(=O)O)(OC(=O)CCCC(N)=O)C(=O)O
+AssemblyReady O=C(O)c1ccc2c(c1)=C1C3=CC4=CC31C1(C(=O)O)C=C(C1=O)C=2N4
+AssemblyReady O=[SH]OC1C(OC(=O)O)OC(O)(C(CO)OC(=O)O)C1O

CupOFMoCA-PROTAC/results/ablation_all/base_s123_clean.smi

@@ -0,0 +1,100 @@
+O=C(O)CCN(C(=O)Nc1cccc(C(=O)O)c1)c1cc2ccc1-2
+INVALID
+CCCOc1sc(CCC(=O)NC(CN=CN)C(=O)O)cc1C(=O)O
+INVALID
+Cc1cc(C(O)c2ccc(NC(=O)C(=O)O)cc2)cc(C(=O)O)c1O
+INVALID
+COC12C=C3C=C4OCOC41C1C=CCC(C3=C2C(=O)O)C1C(=O)O
+O=C(O)c1ccc2c(c1)C1(O)N=c3ccc(C(=O)O)cc3=S1OC2=O
+INVALID
+CC1=CC=CC(Nc2nncs2)(C(=O)O)C(CC(=O)O)=C1
+CC(C)C(=O)OC(C1CCCO1)C(OC(=O)O)OC(=O)O
+CC(C)(CC(=O)O)C(NC(=O)C=CC(N)C(=O)O)C(=O)NCCCO
+CC(OC12C=CC3=C1C2(C(=O)O)N3S1(=O)=C2C3=CC=C2C1=C3)C(=O)O
+INVALID
+Cc1c(Cc2cc(NC(=S)NCC(=O)O)cc(C(=O)O)c2)coc1O
+CC(C)c1cc(S(=O)(=O)NCCC(=O)O)cc2c(CC(=O)O)noc12
+INVALID
+INVALID
+CCN(C1=Cc2cc(C)ccc2N=C(C)O1)C(CCC(=O)O)C(=O)O
+O=C(O)C=C(NC(=O)CCCCCCC(C(=O)O)C(=O)O)C(=O)O
+INVALID
+COc1cccc(-c2cccc(CC(=O)O)c2C(=O)O)c1
+COC12C=C3C=C4OC(CC(=O)O)CC(NC(=[SH]3)N1)C42C(=O)O
+INVALID
+O=C(O)CCC(CC(=O)Oc1cc(C(F)F)cc(C(F)F)c1)C(=O)O
+N#CCOC12C(=O)C1(O)c1ccc3cc1C32C(CC(=O)O)C(=O)O
+O=C(O)c1ccc2c(c1)[N+]([O-])(O)c1cc(ccc1C(=O)O)C(=O)NO2
+CN(C(=O)C(CC(=O)O)NC(=O)CCCO)C1CCCC(C(=O)O)C1
+CNC(C(=O)O)C(O)(OCC(=O)O)C(=O)c1cccc2ccccc12
+O=C(COC(C(=O)O)C(=O)O)c1ccc2c(c1)C(O)=C2O
+O=CNN=CC(CC(C(=O)O)C(=O)O)C(=O)Oc1ccccc1
+COCC1CCC(CC(C)(C)CC(=O)O)(NCCC(=O)O)CC1
+O=C(O)C1=CC(C2CCCCC2)=C2C=CC2C(=O)C(O)C1C(=O)O
+CC(=O)O.NC(=O)c1c2cccc1N(c1ccc(C(=O)O)cc1)C2=O
+O=C(O)C1=NC2=C3C4=CC=C(CC1=C2)C43CC(C(=O)O)C(O)C(=O)O
+CCCC(=O)C1(CC)C=CC(O)=CC(C(=O)O)=C1C(=O)O
+INVALID
+INVALID
+O=C(O)CNS(=O)(=O)C1=Cc2cc(C(=O)O)c3c(c2-3)Cn2cccc21
+INVALID
+INVALID
+O=C(O)NCCC12C=CC(=C(C(S)C(=O)O)Cc3cccc1c3)C=C2
+INVALID
+O=C(O)c1cccc(C2(C(=O)O)C(O)=COC=C2c2ccsc2)c1O
+INVALID
+CC=O.NCC(=O)O.O=C(O)O
+O=C(O)c1cc(NC(=O)C2(C(=O)O)CCCCCC2)cs1
+O=C(O)C(=O)Nc1ccc(C(=O)O)s1
+O=C(O)OC1=CN2CC(Cc3cccc(c3)CC(C(=O)O)NC1=O)C2
+CC(=O)OC(C=C(C)C(=O)O)CC(C)C(CCC(C)(C)O)CC(=O)O
+O=C(O)CNC(=O)c1ccc(OCC(=O)O)cc1
+COc1ccc(CC(Cc2ccccc2C)C(=O)O)cc1CC(=O)O
+O=C(O)Cc1cccc2c3c([nH]cc(C(=O)O)ccc12)CCCC3=O
+CCNS(=O)(=O)c1cnc2coc(C(=O)O)c(C(=CC(=O)O)CC)c1-2
+INVALID
+O=C(O)C1(S)CC(Cc2ccccc2)(C(=O)O)C1
+O=C(O)c1ccc(N2CCOCCN(CCCO)CC2)c(C(=O)O)c1
+INVALID
+CC(C)(CO)NC(=O)CC(CC(=O)O)CC(=O)O
+COc1ccc2nccc(C=C(SC=S)C(=O)O)c2c1C(=O)C(=O)O
+O=C(O)C1=CS(=O)(=CC2CCC3=CCCCC3C2C(=O)O)C=CC1=O
+INVALID
+O=C(O)Cc1ccc(F)cc1C(=O)O
+CC12C(=O)C(C(=O)O)C(C(=O)O)C1(c1ccc(OCCO)cc1)C2=O
+INVALID
+Cc1cccc(CCCCN(CCC(=O)O)C(=O)CCCC(=O)O)c1
+CCC(NC(=O)O)c1cc(C(=O)O)ccc1CC(C)(C)CS(N)(=O)=O
+O=C(O)CCC=c1ccc2c3c1c2C(C(=O)O)=N3
+CCCCC(CC(=O)O)C1C(O)CC2C(O)OC(C(=O)O)CC2C1C
+INVALID
+INVALID
+O=C(O)CC(N=C1CCN2CC3=C1C=CCCC2C(O)=C3O)C(=O)O
+CC(=O)OCCC1(C(=O)O)C(C(C)C)NC(=O)C2(C(=O)O)CCCN21
+INVALID
+NC(C(=O)O)C(=O)C(C(=O)O)=C(O)C(=O)Nc1ccccc1O
+COC(=O)C(C)(C)NC(=O)c1cccc(C(CCC(=O)O)C(=O)O)c1
+INVALID
+COc1ccc(C(=O)O)cc1NC(=Cc1cccs1)C(=O)O
+CC(ON1CC(CO)OC(C(=O)O)C1OC(=O)O)C1(N=O)CCCO1
+CCCC(C)(C)C(=O)C(C(=O)C(=O)O)=C(CO)C(=O)O
+O=C(CCNc1ccc(O)cc1)Nc1c(C(=O)O)cccc1C(=O)O
+INVALID
+CC(C)(CCCO)C(C(=O)O)c1ccccc1C(CC(=O)O)C(=O)O
+INVALID
+O=C(O)C=C1C=C(F)C=C(C2=C(O)C(=O)C(=O)OC2=O)C1(O)C(=O)O
+O=C(O)C1=CC(c2cccs2)=CC(c2ccccc2)=NC(C(=O)O)C1
+CCC1=C(CCC(Oc2ccccc2C(=O)O)C(=O)O)NC(=O)CC1
+O=C(O)CCN(C(=O)O)C(=O)C=C(c1ccccc1)c1ccccc1
+O=C(O)CCCCNc1cc(C(=O)O)c2c(C(=O)O)c(F)ccc2c1
+Cc1ccc(COCC(=O)O)c2c(C(=O)O)cc(OCCCO)cc12
+INVALID
+COC(=O)C(CC(=O)O)CC(O)CC(C(=O)O)C(=O)C(C)(C)C(C)C
+O=C(NC(CC1(C(=O)O)COCCCOC1)C(=O)O)C1CCCCC1
+CC(=O)NCCCCNC(=O)NC(=CC1=C(O)C(C(=O)O)=C1)C(=O)O
+INVALID
+CC(=O)OCC(=O)CC(CCC(=O)OCC(=O)NCC(=O)O)C(=O)O
+O=C(O)CCCCN(CC1CCCCC1)CC1(C(=O)O)C=CC=C1
+CC(CCC(CS)C(=O)O)(OC(=O)CCCC(N)=O)C(=O)O
+O=C(O)c1ccc2c(c1)=C1C3=CC4=CC31C1(C(=O)O)C=C(C1=O)C=2N4
+O=[SH]OC1C(OC(=O)O)OC(O)(C(CO)OC(=O)O)C1O

CupOFMoCA-PROTAC/results/ablation_all/base_s42.smi

@@ -0,0 +1,100 @@
+AssemblyReady Cc1c(NCC(=O)O)cccc1C(=O)O
+AssemblyReady Cc1cccc(C)c1OCC(=O)Nc1cc(C(=O)O)ccc1C(=O)O
+INVALID
+AssemblyReady O=C(O)N1CCC2(CCCC2)C(N(C(=O)O)c2ccc(F)c(F)c2)C1
+INVALID
+AssemblyReady CCC(N)C(=O)NC(=CC(=O)C1(C(=O)O)CC(C)CC(C)C1)C(=O)O
+AssemblyReady C=CC12OC1(C=CC(=O)O)C1CCCCCOC1(C(=O)O)C2(O)CS
+INVALID
+AssemblyReady O=C(O)CNCc1ccc(C2CCCC2CCCC(O)C(=O)O)cc1
+AssemblyReady O=Nc1c(NS(=O)(=O)c2cccc(O)c2)cc(C(=O)O)cc1C(=O)O
+AssemblyReady COCc1c(O)c(CCC(C)=CCCC(=O)O)cc(C(=O)O)cc1=O
+AssemblyReady O=C1C=CC=NC=CC=S2(=O)C(CN1)CC(C(=O)O)C2C(=O)O
+AssemblyReady COC(=O)c1ccc2c(C)cc(C)c(C(=CC(=O)O)C(=O)O)c2c1O
+INVALID
+AssemblyReady CCNC(=O)CCc1ccccc1C(OC)C(CC(=O)O)CC(=O)O
+AssemblyReady Nc1c2cc(ccc2CC(OC(=O)O)C(=O)O)c2cc(=CC=O)sc12
+AssemblyReady CC12CC3CC(C(=O)O)C4C(=O)C(CC34C)C(CCC1=O)C2C(=O)O
+INVALID
+AssemblyReady CCc1ccc([N+]([O-])(OC(=O)O)c2ccc(OC)c(C(=O)O)c2)cc1
+INVALID
+AssemblyReady CC(C)(NC(=O)c1cc(O)cc(OCC(=O)O)c1)C(=O)O
+AssemblyReady CC1C(=O)NC(=O)NC1(CC(=O)O)c1cccc(NC(=O)O)c1
+INVALID
+AssemblyReady Cc1cccc(-c2ccc(-c3c(C(=O)O)csc3C(=O)O)cc2)c1O
+AssemblyReady O=C(O)C1=CC2(C(=O)O)c3cc4c5cc3CSCCC(=O)N4C52C=C1
+AssemblyReady O=C(O)c1ccc(C=CC(=O)[N+]([O-])(O)c2ccccc2)cc1C(=O)O
+AssemblyReady C=C(CN(C(=O)O)C(CCC(=O)O)C(=O)O)NC(CCSC)C(=O)O
+AssemblyReady Cc1cc2nc3c(C(=O)O)cccc3c3ccccc3c(C(=O)O)c1-2
+AssemblyReady CC1S2=C3C(c4cc(O)cc(O)c4C(=O)O)=C2C2=CC3(C(=O)O)C21C
+INVALID
+AssemblyReady CC(CCCC(CCCCC(=O)O)C(=O)O)OCC(O)CCC(=O)O
+AssemblyReady O=C(O)C=Cc1cc(SCC(=O)O)ccc1O
+AssemblyReady COC1(O)CC2(C(=O)O)CCC3=CC=COC1(CC2O)C(C(=O)O)=C3
+AssemblyReady O=COCOc1c(CC(=O)O)cc(O)c(CC(=O)O)c1OCC(=O)O
+AssemblyReady O=C(O)CCC(NC(=O)c1ccc(NCC(=O)O)cc1)C(=O)O
+AssemblyReady O=C(O)C(=CO)C(=O)c1ccc(C(=O)O)c(-c2ccccc2)c1
+AssemblyReady CC(CC(=O)O)=c1ccc2c(c1)C=2C(=O)O
+INVALID
+INVALID
+AssemblyReady CC(NC(CNC(=O)CC1CCCCC1O)C(=O)O)C(=O)O
+AssemblyReady COC12C=C3C1=CC2(OC)C1(C(=O)O)CC(C(=O)O)CC3C1
+AssemblyReady CCC1=CN(CCCN)C(CCCC(=O)O)(C(=O)O)C(CO)=CC=C1
+AssemblyReady O=C(O)CC1C2=CC34C=C(F)C2(CC1C(=O)O)C1(F)C=CC3(C=C1)O4
+AssemblyReady CC1=CC(NC(CC(C)C)C(=O)O)CC=CC2=C1OC(C(=O)O)C2O
+AssemblyReady CC1=CC(=C2CC=CC(S)(C(=O)O)C2)C=C(CO)C(C(=O)O)=C1
+AssemblyReady CC(CCCOO)C(OC(=O)O)C1(C(O)C=O)COC(C(=O)O)CO1
+AssemblyReady Cn1occcc(C(=O)O)cc1-c1cc(C(=O)O)ccc1C(=O)O
+AssemblyReady CC(C1OC(CO)C(C(O)C=O)O1)C(C)(CCCC(=O)O)OC(=O)O
+AssemblyReady CCCCC(CCC1(C)OC(=O)NC(CCC(=O)O)C(=O)O1)C(=O)O
+INVALID
+AssemblyReady C=CCC1=C(C(=O)O)C(OC)=C(C(=O)C(=O)O)C1=O
+AssemblyReady COc1ccc2c(C(C(=O)O)C(=O)O)c1N2CCN(C)C1CCCC1
+AssemblyReady CC(=O)C(C(=O)O)c1c2c(cn1C)C2=CC(=O)O
+AssemblyReady CCC(N)(C(=O)O)C(=O)N(C(CS)C(=O)O)C1(C2=CC(OC)=C2)C=C1
+INVALID
+AssemblyReady COc1cc(C(=O)O)c(CO)c2oc(=O)cc(C(=O)NCC(=O)O)c12
+AssemblyReady C=CC(=O)OCCC(OC(=O)C(C(=O)O)C(O)CC)C(C)(O)C(=O)O
+AssemblyReady CCCC(C(=O)O)N(CC(=O)O)C(F)(F)CC(=O)O
+AssemblyReady CC(C)(C(=O)O)C12C(C(=O)C(=O)O)=C3C1=C2C3(O)c1ccc(O)cc1
+AssemblyReady COCCN(Cc1ccccc1C(=O)O)C(=O)NC(C)C(=O)C(=O)O
+AssemblyReady CC1CC(CC(O)CC(=O)O)C(O)C(CCCCCCCC(=O)O)O1
+AssemblyReady Cc1ccc(S(=O)(=O)NC(CC2=CC=COC(C(=O)O)=C2)C(=O)O)s1
+INVALID
+AssemblyReady O=C(NCCc1cccc(C(=O)O)c1O)C1=C2OC2(C(=O)O)C=C1
+INVALID
+INVALID
+AssemblyReady CN(C)CC(C)(C(=O)O)C(CC1=CC=C1)C(=O)O
+AssemblyReady O=C(O)C(=O)CC(=O)C(C(=O)O)=C1CC1
+AssemblyReady O=C(O)CCC(C(=O)O)C(=O)N(CC(=O)O)C(=O)c1cccc(O)c1
+AssemblyReady Cn1sc2cccc(C3(C(=O)O)CC(NC(=O)CC(=O)O)C3)c2c1=O
+AssemblyReady CN(C1CCC(CC(=O)O)CC1)C(C(=O)NCCC(=O)O)C(C)(C)O
+AssemblyReady CC1=COC2(Cc3cc(C(=O)O)ccc3C(=O)N2)C(C(=O)O)=C1
+AssemblyReady NCC1CN(C(=O)O)C1=NC(=O)O
+AssemblyReady CC(=O)C(CCc1cc(=O)c(C(=O)O)co1)C(=O)O
+AssemblyReady NC1CC[SH]1c1cc(CC(=O)O)ccc1S(=O)(=O)C(=O)O
+AssemblyReady C#CCC1CCOC2=C3CC(O)(C(=O)O)C=C2C=CC3(CC(=O)O)O1
+AssemblyReady CC=C(NCC(=O)O)C(=O)OCCC(=O)O
+INVALID
+AssemblyReady Nc1cc2c(cc1C=O)-c1c-2ccc(C(=O)O)c1NC1(C(=O)O)CC1
+AssemblyReady COCCC1OC(c2ccc(C(=O)O)cc2)OCC1CC(=O)O
+AssemblyReady O=C(O)CCCC12C=CC(C3CCCN4CCCCC34)=C1N2C(=O)O
+AssemblyReady Cc1cc(C(=O)O)cc2c1NC(C(=O)O)(C(=O)O)C2
+AssemblyReady O=C(O)C1=C2C1=CC1=CC12N=CN1C(=O)C(C(=O)O)CSC1=S
+AssemblyReady CCC(=O)OCCCCCc1cc(OCC(=O)O)cc(O)c1C(=O)O
+AssemblyReady CCC(C(=O)O)N(CCCNC(=O)COC)c1cc(C(=O)O)no1
+AssemblyReady CCSC1N(C(CC(=O)O)C(=O)O)S(=O)(=O)C2=CC3(CO)OC13C=C2
+AssemblyReady CC1(C)C2CCC3(C)C4CC5OC1C(C(C(=O)O)=CC2C(=O)O)C3C54
+AssemblyReady CCNC(=O)C1(NCNC(=O)O)C=CC(C)(C(=O)O)C=C1
+AssemblyReady CCCC(C(=O)OC)N(CCCCC(=O)O)C(=O)C(=O)O
+INVALID
+AssemblyReady CC1=CC2=CS134=C1C=C(C(=O)O)C3=C4C13c1c(ccn13)C2CC(=O)O
+AssemblyReady CCCC1(C2=C(c3cccn3CC(=O)O)C(O)=C2N)CC(C(=O)O)C1
+INVALID
+AssemblyReady CC(=O)Nc1ccc(CNc2cc(C(=O)O)c(C(=O)O)cc2O)cc1
+AssemblyReady CCCC(=O)N1CCCN(C(COC(C)C)C(=O)O)CCC1C(=O)O
+AssemblyReady CC(=O)NC(=O)N1CCC(=C(CC(=O)O)C(=O)O)CC1
+AssemblyReady O=C(O)C(CCCCO)(C(=O)O)C1CCCCCC(O)CCCCC1
+AssemblyReady O=C(O)C1=CC=CNC(Cc2ccc(O)cc2)(C(=O)O)C(C(=O)O)=C1
+AssemblyReady CC(NC(=O)N(CC(=O)C(=O)O)C(=O)c1ccc(CO)cc1)C(=O)O
+AssemblyReady CC1CCN(C(=O)CC=C(CCC(=O)O)C(=O)O)CC1

CupOFMoCA-PROTAC/results/ablation_all/base_s42_clean.smi

@@ -0,0 +1,100 @@
+Cc1c(NCC(=O)O)cccc1C(=O)O
+Cc1cccc(C)c1OCC(=O)Nc1cc(C(=O)O)ccc1C(=O)O
+INVALID
+O=C(O)N1CCC2(CCCC2)C(N(C(=O)O)c2ccc(F)c(F)c2)C1
+INVALID
+CCC(N)C(=O)NC(=CC(=O)C1(C(=O)O)CC(C)CC(C)C1)C(=O)O
+C=CC12OC1(C=CC(=O)O)C1CCCCCOC1(C(=O)O)C2(O)CS
+INVALID
+O=C(O)CNCc1ccc(C2CCCC2CCCC(O)C(=O)O)cc1
+O=Nc1c(NS(=O)(=O)c2cccc(O)c2)cc(C(=O)O)cc1C(=O)O
+COCc1c(O)c(CCC(C)=CCCC(=O)O)cc(C(=O)O)cc1=O
+O=C1C=CC=NC=CC=S2(=O)C(CN1)CC(C(=O)O)C2C(=O)O
+COC(=O)c1ccc2c(C)cc(C)c(C(=CC(=O)O)C(=O)O)c2c1O
+INVALID
+CCNC(=O)CCc1ccccc1C(OC)C(CC(=O)O)CC(=O)O
+Nc1c2cc(ccc2CC(OC(=O)O)C(=O)O)c2cc(=CC=O)sc12
+CC12CC3CC(C(=O)O)C4C(=O)C(CC34C)C(CCC1=O)C2C(=O)O
+INVALID
+CCc1ccc([N+]([O-])(OC(=O)O)c2ccc(OC)c(C(=O)O)c2)cc1
+INVALID
+CC(C)(NC(=O)c1cc(O)cc(OCC(=O)O)c1)C(=O)O
+CC1C(=O)NC(=O)NC1(CC(=O)O)c1cccc(NC(=O)O)c1
+INVALID
+Cc1cccc(-c2ccc(-c3c(C(=O)O)csc3C(=O)O)cc2)c1O
+O=C(O)C1=CC2(C(=O)O)c3cc4c5cc3CSCCC(=O)N4C52C=C1
+O=C(O)c1ccc(C=CC(=O)[N+]([O-])(O)c2ccccc2)cc1C(=O)O
+C=C(CN(C(=O)O)C(CCC(=O)O)C(=O)O)NC(CCSC)C(=O)O
+Cc1cc2nc3c(C(=O)O)cccc3c3ccccc3c(C(=O)O)c1-2
+CC1S2=C3C(c4cc(O)cc(O)c4C(=O)O)=C2C2=CC3(C(=O)O)C21C
+INVALID
+CC(CCCC(CCCCC(=O)O)C(=O)O)OCC(O)CCC(=O)O
+O=C(O)C=Cc1cc(SCC(=O)O)ccc1O
+COC1(O)CC2(C(=O)O)CCC3=CC=COC1(CC2O)C(C(=O)O)=C3
+O=COCOc1c(CC(=O)O)cc(O)c(CC(=O)O)c1OCC(=O)O
+O=C(O)CCC(NC(=O)c1ccc(NCC(=O)O)cc1)C(=O)O
+O=C(O)C(=CO)C(=O)c1ccc(C(=O)O)c(-c2ccccc2)c1
+CC(CC(=O)O)=c1ccc2c(c1)C=2C(=O)O
+INVALID
+INVALID
+CC(NC(CNC(=O)CC1CCCCC1O)C(=O)O)C(=O)O
+COC12C=C3C1=CC2(OC)C1(C(=O)O)CC(C(=O)O)CC3C1
+CCC1=CN(CCCN)C(CCCC(=O)O)(C(=O)O)C(CO)=CC=C1
+O=C(O)CC1C2=CC34C=C(F)C2(CC1C(=O)O)C1(F)C=CC3(C=C1)O4
+CC1=CC(NC(CC(C)C)C(=O)O)CC=CC2=C1OC(C(=O)O)C2O
+CC1=CC(=C2CC=CC(S)(C(=O)O)C2)C=C(CO)C(C(=O)O)=C1
+CC(CCCOO)C(OC(=O)O)C1(C(O)C=O)COC(C(=O)O)CO1
+Cn1occcc(C(=O)O)cc1-c1cc(C(=O)O)ccc1C(=O)O
+CC(C1OC(CO)C(C(O)C=O)O1)C(C)(CCCC(=O)O)OC(=O)O
+CCCCC(CCC1(C)OC(=O)NC(CCC(=O)O)C(=O)O1)C(=O)O
+INVALID
+C=CCC1=C(C(=O)O)C(OC)=C(C(=O)C(=O)O)C1=O
+COc1ccc2c(C(C(=O)O)C(=O)O)c1N2CCN(C)C1CCCC1
+CC(=O)C(C(=O)O)c1c2c(cn1C)C2=CC(=O)O
+CCC(N)(C(=O)O)C(=O)N(C(CS)C(=O)O)C1(C2=CC(OC)=C2)C=C1
+INVALID
+COc1cc(C(=O)O)c(CO)c2oc(=O)cc(C(=O)NCC(=O)O)c12
+C=CC(=O)OCCC(OC(=O)C(C(=O)O)C(O)CC)C(C)(O)C(=O)O
+CCCC(C(=O)O)N(CC(=O)O)C(F)(F)CC(=O)O
+CC(C)(C(=O)O)C12C(C(=O)C(=O)O)=C3C1=C2C3(O)c1ccc(O)cc1
+COCCN(Cc1ccccc1C(=O)O)C(=O)NC(C)C(=O)C(=O)O
+CC1CC(CC(O)CC(=O)O)C(O)C(CCCCCCCC(=O)O)O1
+Cc1ccc(S(=O)(=O)NC(CC2=CC=COC(C(=O)O)=C2)C(=O)O)s1
+INVALID
+O=C(NCCc1cccc(C(=O)O)c1O)C1=C2OC2(C(=O)O)C=C1
+INVALID
+INVALID
+CN(C)CC(C)(C(=O)O)C(CC1=CC=C1)C(=O)O
+O=C(O)C(=O)CC(=O)C(C(=O)O)=C1CC1
+O=C(O)CCC(C(=O)O)C(=O)N(CC(=O)O)C(=O)c1cccc(O)c1
+Cn1sc2cccc(C3(C(=O)O)CC(NC(=O)CC(=O)O)C3)c2c1=O
+CN(C1CCC(CC(=O)O)CC1)C(C(=O)NCCC(=O)O)C(C)(C)O
+CC1=COC2(Cc3cc(C(=O)O)ccc3C(=O)N2)C(C(=O)O)=C1
+NCC1CN(C(=O)O)C1=NC(=O)O
+CC(=O)C(CCc1cc(=O)c(C(=O)O)co1)C(=O)O
+NC1CC[SH]1c1cc(CC(=O)O)ccc1S(=O)(=O)C(=O)O
+C#CCC1CCOC2=C3CC(O)(C(=O)O)C=C2C=CC3(CC(=O)O)O1
+CC=C(NCC(=O)O)C(=O)OCCC(=O)O
+INVALID
+Nc1cc2c(cc1C=O)-c1c-2ccc(C(=O)O)c1NC1(C(=O)O)CC1
+COCCC1OC(c2ccc(C(=O)O)cc2)OCC1CC(=O)O
+O=C(O)CCCC12C=CC(C3CCCN4CCCCC34)=C1N2C(=O)O
+Cc1cc(C(=O)O)cc2c1NC(C(=O)O)(C(=O)O)C2
+O=C(O)C1=C2C1=CC1=CC12N=CN1C(=O)C(C(=O)O)CSC1=S
+CCC(=O)OCCCCCc1cc(OCC(=O)O)cc(O)c1C(=O)O
+CCC(C(=O)O)N(CCCNC(=O)COC)c1cc(C(=O)O)no1
+CCSC1N(C(CC(=O)O)C(=O)O)S(=O)(=O)C2=CC3(CO)OC13C=C2
+CC1(C)C2CCC3(C)C4CC5OC1C(C(C(=O)O)=CC2C(=O)O)C3C54
+CCNC(=O)C1(NCNC(=O)O)C=CC(C)(C(=O)O)C=C1
+CCCC(C(=O)OC)N(CCCCC(=O)O)C(=O)C(=O)O
+INVALID
+CC1=CC2=CS134=C1C=C(C(=O)O)C3=C4C13c1c(ccn13)C2CC(=O)O
+CCCC1(C2=C(c3cccn3CC(=O)O)C(O)=C2N)CC(C(=O)O)C1
+INVALID
+CC(=O)Nc1ccc(CNc2cc(C(=O)O)c(C(=O)O)cc2O)cc1
+CCCC(=O)N1CCCN(C(COC(C)C)C(=O)O)CCC1C(=O)O
+CC(=O)NC(=O)N1CCC(=C(CC(=O)O)C(=O)O)CC1
+O=C(O)C(CCCCO)(C(=O)O)C1CCCCCC(O)CCCCC1
+O=C(O)C1=CC=CNC(Cc2ccc(O)cc2)(C(=O)O)C(C(=O)O)=C1
+CC(NC(=O)N(CC(=O)C(=O)O)C(=O)c1ccc(CO)cc1)C(=O)O
+CC1CCN(C(=O)CC=C(CCC(=O)O)C(=O)O)CC1

CupOFMoCA-PROTAC/results/ablation_all/base_s456.smi

@@ -0,0 +1,100 @@
+DISCONNECTED O=C(O)CC1CCC2=C3C=CC=CC321.O=CO
+AssemblyReady O=C(O)CC12OC1=C(O)C(=COC(=O)CC[SH](=O)=O)C(C(=O)O)=C2O
+AssemblyReady NC(CCC(=O)O)C(=O)O
+AssemblyReady CCCC(=C(O)C(=O)O)C(C(=O)O)C(=O)O
+INVALID
+AssemblyReady CC(O)C1(O)C=CC2(C(=O)O)OC(OC(CC(=O)O)CC(=O)O)CC21
+AssemblyReady O=C(O)CCC(=O)C(=O)C(=O)O
+AssemblyReady CN(Cc1ccc(CC(C=O)NC(=O)CSOC(=O)O)cc1)C(=O)O
+AssemblyReady CC12CC3CC4(OCC35C3=CS5=C34)C(C(=O)O)(NC(=O)O1)C2C(=O)O
+AssemblyReady CC1(CNC(=O)C(=O)O)CCCC(C)(C(=O)O)CCC1
+AssemblyReady Cc1ccc2ccc(C(=O)O)c(O)c2c1-c1ccc(O)cc1C(=O)O
+AssemblyReady O=C(O)CCCCCNC(c1ccccc1)c1ccccc1C(=O)O
+INVALID
+AssemblyReady Nc1cc(C(=O)O)c(C(=O)N(CCO)CCC(=O)O)cc1S(=O)(=O)O
+AssemblyReady CC1=C(C(=O)O)C(CCCC(=CC(=O)O)C(=O)O)=C(C(=O)O)CCC1
+AssemblyReady CCN(C)C(=O)C(NC(=O)O)C(O)(CC(=O)O)c1ccc(NC)cc1
+AssemblyReady CC1=C(C(=O)O)C=CC(N)=NC(Nc2cccc(C(=O)O)c2)=C1
+AssemblyReady C=C(OC1CCCC1)C(CC=CCCCCC(=O)O)NC(=O)C(=O)O
+AssemblyReady O=CNc1scc([N+]([O-])(O)C(=O)O)c1C(=O)O
+AssemblyReady CC(C)(CO)C(C)(C(=O)O)c1cc(-c2ccccc2)ccc1C(=O)O
+AssemblyReady COc1ccc(C(=O)O)c(C2=C(C3=CC(O)=C3C(=O)O)O2)c1O
+AssemblyReady Cc1cc(C(=C(C#N)C(=O)O)c2cc(CO)c(C(=O)O)o2)ccc1O
+AssemblyReady Cc1c(C(=O)NC(CC(=O)O)(NCC(C)C(=O)O)C(=O)O)ncn1C
+AssemblyReady O=C(O)C1=CC23C=CC(C(=O)O)(C=C2)C1C(=O)OC3
+AssemblyReady CC1=CC(CC(=O)O)C(C(=O)O)C(C)=C1
+AssemblyReady O=Cc1cc(CC(CO)(CCO)C(=O)O)c2cc(C(=O)O)ccc2c1
+AssemblyReady CCCC(C(=O)O)C(C=O)N(CNC)C(=O)O
+INVALID
+AssemblyReady CC1CC(CC(=O)O)CCC1OCNC(C(=O)O)C(C)CO
+AssemblyReady CC(CCC1C(C)(C)CCC(O)C1(C)CCCCCC(=O)O)C(=O)O
+AssemblyReady CC(N)C(=O)N1CCC(C)C(CC(=O)C(CC(N)C(=O)O)C(=O)O)C1
+INVALID
+INVALID
+AssemblyReady Cc1c(NC(OC(=O)O)C(=O)O)ncn1C(CCCC(=O)O)C(=O)O
+AssemblyReady N#Cc1ccccc1-c1cc(C(=O)O)ccc1OC1CC(C(=O)O)C1
+AssemblyReady CCCCC(C(=O)O)C(O)(C(=CC(=O)O)C(=O)O)C(O)CNC(C)=O
+AssemblyReady Cc1cc(C(=CC(=O)O)c2ccccc2)cc2c(C(=O)O)cccc12
+AssemblyReady O=C(O)CCCCN(C(C(=O)O)C(F)(F)F)C(F)(F)C(F)(F)C(=O)O
+INVALID
+AssemblyReady O=CC=C(OC(=O)O)S1(=O)=C2C=C(C3CCC(C(=O)O)N3)C=C2C=C1
+AssemblyReady CC(C)C(Nc1ccc(C=C(O)C(=O)NCC(=O)O)cc1)C(=O)O
+AssemblyReady COc1ccc(NC(=O)OCCCC(CC=CC(=O)O)C(=O)O)cc1
+AssemblyReady O=NC1CCC2=CC(C(=O)O)=CC21c1ccc(O)c(C(=O)O)c1O
+AssemblyReady NC12C3=C4B=C(C(=O)O)OC45C(=O)N5C(C(=O)O)C4C5=C6N1C64C3=C52
+INVALID
+AssemblyReady O=C(O)CCCC(CC(=O)O)OCC(=O)O
+DISCONNECTED Cc1nnc2n1N1C(=Nc3cc(C(=O)O)c(O)c1c3)CN2.O=C(O)O
+AssemblyReady O=C(O)c1cccc(CC(NS(=O)(=O)C2=CC=COC=C2)C(=O)O)c1
+AssemblyReady Nc1ccc(C(=O)O)cc1C(=O)NC(C(=O)O)c1ccc(C(=O)O)s1
+AssemblyReady CCC(C(=O)O)(C(=O)O)c1cccc(C(F)(F)F)c1C=NNC(C)=O
+AssemblyReady O=C(O)CNC(=O)c1cc(-c2ccccc2C(=O)O)c(C(=O)O)s1
+AssemblyReady Cc1c2ccc(N)c(c2C(=O)O)c2cc3cc1c2c3NC(=O)C(=O)O
+INVALID
+AssemblyReady O=C(O)NCCCOc1cc(C(=O)O)nc(N(O)O)n1
+AssemblyReady O=C(O)CC1=CC2(NC3(C(=O)O)CC3)C(O)=CC=C(CC(=O)O)C2=C1
+DISCONNECTED C.CCCC(C)=C(C(=O)O)C(=O)C(=O)O
+AssemblyReady CNc1cc(C(=O)O)cc(N(C)c2cccc(C)c2C(=O)O)c1
+INVALID
+AssemblyReady CCC(Oc1c(OCC(=O)O)cc(OC)c(OC)c1COC)C(=O)O
+AssemblyReady NC(C(=O)c1ccc(C(=O)O)cc1)=C(CCCCCC(=O)O)C(=O)O
+AssemblyReady CC(C)C(O)(C(=O)O)C(O)C(O)COC(=O)CC(C)(C)CCC(=O)O
+INVALID
+AssemblyReady O=C(O)CC1CCN(c2c3cccc2C(C(=O)O)=CCO3)CC1
+AssemblyReady Cc1cc(=O)n(CCC(CCCC(=O)O)C(=O)O)c(N)nc1=O
+AssemblyReady O=C(O)Cc1c(OCc2cccc(C(=O)O)c2)ccc2ccccc12
+AssemblyReady CC(C)(O)C(NC(=O)CC(=O)O)C(C(=O)O)C(COC(=O)O)C(=O)O
+AssemblyReady CN(C(=O)C1(C(=O)O)CC1)c1cccc(C(=O)O)c1CO
+INVALID
+AssemblyReady O=C(O)c1cc(-c2ccccc2-c2ccccc2C(=O)O)ccc1O
+AssemblyReady CC(C)(C(=O)O)C(=O)N(CCCCC(=O)OOC(=O)CN)CC(=O)O
+AssemblyReady O=C(O)CNC(=O)c1cccc(-c2sc3ccccc3c2C(=O)O)c1
+INVALID
+AssemblyReady CNC(=O)N(C)C(=O)NC(Cn1c(C)nc(O)c1C(=O)O)C(=O)O
+AssemblyReady O=C(O)Nc1ccc2cc1C=CC=C(C(=O)O)C=CNC(=O)C(=O)N2
+AssemblyReady CCc1ccc([N+](=O)[O-])c(N(C(=O)O)C(C(=O)O)C(N)CC)c1
+AssemblyReady Cc1ccc2c(c1)C(c1ccccc1C(=O)O)([SH](=O)=O)C=C2C(=O)O
+INVALID
+AssemblyReady COc1c(C)c(C(=O)CC(=O)O)cc(C=CC(=O)O)c1OCCCO
+AssemblyReady O=C(O)CCNC(=S)Nc1ccc(C=C(O)C(=O)O)c2ccccc12
+AssemblyReady O=C(O)CCNC(=O)c1[nH]sc(-c2cccs2)nc(C(=O)O)cc1O
+AssemblyReady N#CC(=C1CCCCC1)c1c(C(=O)O)cccc1C(=O)O
+AssemblyReady CCC=C(C(=O)O)C1(C(=O)O)NC2C=C3C4=CC3(C#N)C(F)=CC41O2
+AssemblyReady NS(=O)(=O)c1cc2cn(C=CC(=O)O)c3ccccc3c-2c1C(=O)O
+AssemblyReady CCN(C(=O)CC(C)(CC(=O)O)C(=O)OC)c1ccc(C(=O)O)cc1
+AssemblyReady O=C1C[SH]2CC3=C(C(=O)O)C4=CC35CC3=CC2(C(=O)O)C45C(=C3)CN1
+AssemblyReady COc1ccc(NC(=O)CC(C(=O)O)(C(=O)O)c2ccccc2)cc1
+AssemblyReady Cc1cc(C)n2oc3c(C(=O)O)c4c(c(C(=O)O)c34)c(=O)occ2c1
+AssemblyReady O=C(O)Nc1cc(C(=O)O)c(OC(F)(F)F)c(-c2ccccc2)c1
+AssemblyReady COC1CCC(C(=O)O)C(C(CCNC(=N)NCN)C(N)C(=O)O)C1
+AssemblyReady O=C(O)c1cccc(CNC(=O)c2cccc(C(=O)O)c2)c1
+AssemblyReady CN(CC(=O)O)CC(=O)CC(=O)O
+AssemblyReady NS(=O)(=O)c1c(NCC(=O)O)ccc(OC(=O)O)c1NCC=CC=O
+AssemblyReady O=C(O)CC(O)C1OC2CC3=CCCSC(C=CCC31)C=C2C(=O)O
+AssemblyReady O=C(O)CC(NC1=S2CN12)c1cccc(C(=O)O)c1
+AssemblyReady O=C(O)CCNCC(O)=C(NC(=O)CCCC1=CCCCC1)C(=O)O
+AssemblyReady CCOC(=O)CNC(=C(C)C(=O)O)c1cc(C(C)=O)cc(C(=O)O)c1
+INVALID
+AssemblyReady Cc1nc(-c2cc(CC(=O)O)ccc2COCC(=O)O)cs1
+AssemblyReady CC(CC(=O)O)NC(=O)C(CC(=O)O)C(C)S(=O)C(C)CO
+AssemblyReady O=C(O)OCC1CC(O)C(n2c3cnc2=NC(SOC(=O)O)=NC=3)O1

CupOFMoCA-PROTAC/results/ablation_all/base_s456_clean.smi

@@ -0,0 +1,100 @@
+O=C(O)CC1CCC2=C3C=CC=CC321.O=CO
+O=C(O)CC12OC1=C(O)C(=COC(=O)CC[SH](=O)=O)C(C(=O)O)=C2O
+NC(CCC(=O)O)C(=O)O
+CCCC(=C(O)C(=O)O)C(C(=O)O)C(=O)O
+INVALID
+CC(O)C1(O)C=CC2(C(=O)O)OC(OC(CC(=O)O)CC(=O)O)CC21
+O=C(O)CCC(=O)C(=O)C(=O)O
+CN(Cc1ccc(CC(C=O)NC(=O)CSOC(=O)O)cc1)C(=O)O
+CC12CC3CC4(OCC35C3=CS5=C34)C(C(=O)O)(NC(=O)O1)C2C(=O)O
+CC1(CNC(=O)C(=O)O)CCCC(C)(C(=O)O)CCC1
+Cc1ccc2ccc(C(=O)O)c(O)c2c1-c1ccc(O)cc1C(=O)O
+O=C(O)CCCCCNC(c1ccccc1)c1ccccc1C(=O)O
+INVALID
+Nc1cc(C(=O)O)c(C(=O)N(CCO)CCC(=O)O)cc1S(=O)(=O)O
+CC1=C(C(=O)O)C(CCCC(=CC(=O)O)C(=O)O)=C(C(=O)O)CCC1
+CCN(C)C(=O)C(NC(=O)O)C(O)(CC(=O)O)c1ccc(NC)cc1
+CC1=C(C(=O)O)C=CC(N)=NC(Nc2cccc(C(=O)O)c2)=C1
+C=C(OC1CCCC1)C(CC=CCCCCC(=O)O)NC(=O)C(=O)O
+O=CNc1scc([N+]([O-])(O)C(=O)O)c1C(=O)O
+CC(C)(CO)C(C)(C(=O)O)c1cc(-c2ccccc2)ccc1C(=O)O
+COc1ccc(C(=O)O)c(C2=C(C3=CC(O)=C3C(=O)O)O2)c1O
+Cc1cc(C(=C(C#N)C(=O)O)c2cc(CO)c(C(=O)O)o2)ccc1O
+Cc1c(C(=O)NC(CC(=O)O)(NCC(C)C(=O)O)C(=O)O)ncn1C
+O=C(O)C1=CC23C=CC(C(=O)O)(C=C2)C1C(=O)OC3
+CC1=CC(CC(=O)O)C(C(=O)O)C(C)=C1
+O=Cc1cc(CC(CO)(CCO)C(=O)O)c2cc(C(=O)O)ccc2c1
+CCCC(C(=O)O)C(C=O)N(CNC)C(=O)O
+INVALID
+CC1CC(CC(=O)O)CCC1OCNC(C(=O)O)C(C)CO
+CC(CCC1C(C)(C)CCC(O)C1(C)CCCCCC(=O)O)C(=O)O
+CC(N)C(=O)N1CCC(C)C(CC(=O)C(CC(N)C(=O)O)C(=O)O)C1
+INVALID
+INVALID
+Cc1c(NC(OC(=O)O)C(=O)O)ncn1C(CCCC(=O)O)C(=O)O
+N#Cc1ccccc1-c1cc(C(=O)O)ccc1OC1CC(C(=O)O)C1
+CCCCC(C(=O)O)C(O)(C(=CC(=O)O)C(=O)O)C(O)CNC(C)=O
+Cc1cc(C(=CC(=O)O)c2ccccc2)cc2c(C(=O)O)cccc12
+O=C(O)CCCCN(C(C(=O)O)C(F)(F)F)C(F)(F)C(F)(F)C(=O)O
+INVALID
+O=CC=C(OC(=O)O)S1(=O)=C2C=C(C3CCC(C(=O)O)N3)C=C2C=C1
+CC(C)C(Nc1ccc(C=C(O)C(=O)NCC(=O)O)cc1)C(=O)O
+COc1ccc(NC(=O)OCCCC(CC=CC(=O)O)C(=O)O)cc1
+O=NC1CCC2=CC(C(=O)O)=CC21c1ccc(O)c(C(=O)O)c1O
+NC12C3=C4B=C(C(=O)O)OC45C(=O)N5C(C(=O)O)C4C5=C6N1C64C3=C52
+INVALID
+O=C(O)CCCC(CC(=O)O)OCC(=O)O
+Cc1nnc2n1N1C(=Nc3cc(C(=O)O)c(O)c1c3)CN2.O=C(O)O
+O=C(O)c1cccc(CC(NS(=O)(=O)C2=CC=COC=C2)C(=O)O)c1
+Nc1ccc(C(=O)O)cc1C(=O)NC(C(=O)O)c1ccc(C(=O)O)s1
+CCC(C(=O)O)(C(=O)O)c1cccc(C(F)(F)F)c1C=NNC(C)=O
+O=C(O)CNC(=O)c1cc(-c2ccccc2C(=O)O)c(C(=O)O)s1
+Cc1c2ccc(N)c(c2C(=O)O)c2cc3cc1c2c3NC(=O)C(=O)O
+INVALID
+O=C(O)NCCCOc1cc(C(=O)O)nc(N(O)O)n1
+O=C(O)CC1=CC2(NC3(C(=O)O)CC3)C(O)=CC=C(CC(=O)O)C2=C1
+C.CCCC(C)=C(C(=O)O)C(=O)C(=O)O
+CNc1cc(C(=O)O)cc(N(C)c2cccc(C)c2C(=O)O)c1
+INVALID
+CCC(Oc1c(OCC(=O)O)cc(OC)c(OC)c1COC)C(=O)O
+NC(C(=O)c1ccc(C(=O)O)cc1)=C(CCCCCC(=O)O)C(=O)O
+CC(C)C(O)(C(=O)O)C(O)C(O)COC(=O)CC(C)(C)CCC(=O)O
+INVALID
+O=C(O)CC1CCN(c2c3cccc2C(C(=O)O)=CCO3)CC1
+Cc1cc(=O)n(CCC(CCCC(=O)O)C(=O)O)c(N)nc1=O
+O=C(O)Cc1c(OCc2cccc(C(=O)O)c2)ccc2ccccc12
+CC(C)(O)C(NC(=O)CC(=O)O)C(C(=O)O)C(COC(=O)O)C(=O)O
+CN(C(=O)C1(C(=O)O)CC1)c1cccc(C(=O)O)c1CO
+INVALID
+O=C(O)c1cc(-c2ccccc2-c2ccccc2C(=O)O)ccc1O
+CC(C)(C(=O)O)C(=O)N(CCCCC(=O)OOC(=O)CN)CC(=O)O
+O=C(O)CNC(=O)c1cccc(-c2sc3ccccc3c2C(=O)O)c1
+INVALID
+CNC(=O)N(C)C(=O)NC(Cn1c(C)nc(O)c1C(=O)O)C(=O)O
+O=C(O)Nc1ccc2cc1C=CC=C(C(=O)O)C=CNC(=O)C(=O)N2
+CCc1ccc([N+](=O)[O-])c(N(C(=O)O)C(C(=O)O)C(N)CC)c1
+Cc1ccc2c(c1)C(c1ccccc1C(=O)O)([SH](=O)=O)C=C2C(=O)O
+INVALID
+COc1c(C)c(C(=O)CC(=O)O)cc(C=CC(=O)O)c1OCCCO
+O=C(O)CCNC(=S)Nc1ccc(C=C(O)C(=O)O)c2ccccc12
+O=C(O)CCNC(=O)c1[nH]sc(-c2cccs2)nc(C(=O)O)cc1O
+N#CC(=C1CCCCC1)c1c(C(=O)O)cccc1C(=O)O
+CCC=C(C(=O)O)C1(C(=O)O)NC2C=C3C4=CC3(C#N)C(F)=CC41O2
+NS(=O)(=O)c1cc2cn(C=CC(=O)O)c3ccccc3c-2c1C(=O)O
+CCN(C(=O)CC(C)(CC(=O)O)C(=O)OC)c1ccc(C(=O)O)cc1
+O=C1C[SH]2CC3=C(C(=O)O)C4=CC35CC3=CC2(C(=O)O)C45C(=C3)CN1
+COc1ccc(NC(=O)CC(C(=O)O)(C(=O)O)c2ccccc2)cc1
+Cc1cc(C)n2oc3c(C(=O)O)c4c(c(C(=O)O)c34)c(=O)occ2c1
+O=C(O)Nc1cc(C(=O)O)c(OC(F)(F)F)c(-c2ccccc2)c1
+COC1CCC(C(=O)O)C(C(CCNC(=N)NCN)C(N)C(=O)O)C1
+O=C(O)c1cccc(CNC(=O)c2cccc(C(=O)O)c2)c1
+CN(CC(=O)O)CC(=O)CC(=O)O
+NS(=O)(=O)c1c(NCC(=O)O)ccc(OC(=O)O)c1NCC=CC=O
+O=C(O)CC(O)C1OC2CC3=CCCSC(C=CCC31)C=C2C(=O)O
+O=C(O)CC(NC1=S2CN12)c1cccc(C(=O)O)c1
+O=C(O)CCNCC(O)=C(NC(=O)CCCC1=CCCCC1)C(=O)O
+CCOC(=O)CNC(=C(C)C(=O)O)c1cc(C(C)=O)cc(C(=O)O)c1
+INVALID
+Cc1nc(-c2cc(CC(=O)O)ccc2COCC(=O)O)cs1
+CC(CC(=O)O)NC(=O)C(CC(=O)O)C(C)S(=O)C(C)CO
+O=C(O)OCC1CC(O)C(n2c3cnc2=NC(SOC(=O)O)=NC=3)O1

CupOFMoCA-PROTAC/results/ablation_all/both_s123.smi

@@ -0,0 +1,100 @@
+DISCONNECTED CC(=O)O.CCOCC(=O)O
+AssemblyReady CCC(CC)=C(CC(=O)O)C(=O)O
+AssemblyReady CC(CCC(=O)O)C(=O)O
+AssemblyReady O=C(O)C1CCCC(C(NC(=O)C2CC2)C(=O)O)CCC1
+AssemblyReady O=C(O)C(=O)C1CCC(C(=O)O)CC1
+AssemblyReady CC(C(=O)O)C(C)(C)C(=O)O
+AssemblyReady CCCCNC(CC(=O)O)C(=O)O
+AssemblyReady NC(=O)CCC(CCCC(=O)O)CCCC(=O)O
+AssemblyReady CCCCCN(C)CCOC(CCCNC(=O)O)NC(=O)O
+AssemblyReady CCCC(CCC(=O)O)C(N)C(=O)O
+AssemblyReady CC(C)N(C)CCC(C(=O)O)C(=O)O
+AssemblyReady C=Cc1c(C(C)(CC(=O)O)C(=O)O)c(C)c(C)n(C)c1=O
+AssemblyReady COCCOC1CCC(CCC(=O)O)CN(C(C)C(=O)O)C1
+INVALID
+AssemblyReady CCC(C)(C(=O)O)C(CC(=O)O)OC
+INVALID
+AssemblyReady CCCC(C(=O)O)C(=O)O
+DISCONNECTED C.CCC(=CC(=O)O)C(=O)O
+AssemblyReady CC(C)(CCC(=O)O)C(=O)O
+INVALID
+AssemblyReady CCc1cc(CC(=O)O)cc(C(=O)O)c1
+DISCONNECTED CC(=O)O.NC(=O)C(=O)O
+AssemblyReady CC(C(=O)O)=C(C)C(=O)O
+AssemblyReady O=C(O)CCC(O)C(=O)O
+DISCONNECTED N.NC(CC(=O)O)C(=O)O
+AssemblyReady CC(CCC(=O)O)C(=O)O
+AssemblyReady CCCCCC(=O)C(C(=O)O)C(=O)O
+AssemblyReady O=C(O)C=CC(=O)NCCCCC(=O)O
+AssemblyReady CC(C(=O)O)=C(C)C(=O)O
+AssemblyReady CCOC(=O)CCC(CC(=O)O)C(=O)O
+AssemblyReady CCC(CC(=O)O)C(=O)O
+AssemblyReady O=C(O)NCC#CCCCCNC(=O)O
+AssemblyReady CC(C(=O)O)=C(C)C(=O)O
+AssemblyReady Cc1cc(C(=O)O)cc2noc(C(=O)O)c12
+AssemblyReady C#CCC(CCCC)=C(CC(=O)O)C(=O)O
+AssemblyReady CCC(C(=O)O)C(O)(C(=O)O)C(C)C
+AssemblyReady O=C(O)C1CC(C(=O)O)C1
+INVALID
+AssemblyReady O=C(O)CCCCCC(CCC(=O)O)NCCCOCCCO
+AssemblyReady COCCN(CC(=O)O)C(CCCCCCCCCCO)C(=O)O
+AssemblyReady O=C(O)NCC1CC[N+]2([O-])NC(C(=O)O)CCCCCC12
+AssemblyReady O=C(O)CCN1CCC(C(=O)O)CC1
+AssemblyReady CCCN(CC)C(C(=O)O)C(=O)O
+AssemblyReady CCCCCCCCCN(CC(=O)O)CC(=O)O
+AssemblyReady CCCC(C(=O)O)N(CCC)CC(=O)O
+AssemblyReady CNCC(C)(C(=O)O)C(=O)O
+AssemblyReady CC(C(=O)O)C(=O)C(=O)O
+DISCONNECTED C#N.O=C(O)CCC(=O)O
+AssemblyReady CCNC(CCCCCC(=O)O)CCC(=O)O
+AssemblyReady COC(C(=O)O)=C(C)CC(C(=O)O)C(=O)O
+INVALID
+DISCONNECTED C=C.O=C(O)CCCCCC(=O)O.O=S
+AssemblyReady CNCCC(CCC(CCC(C)C)C(=O)O)C(=O)O
+DISCONNECTED C.CCC(C(=O)O)C(=O)O
+INVALID
+INVALID
+AssemblyReady CCCCN(CCC(=O)O)C(CC)CCC(=O)O
+AssemblyReady CC=C(CC(=O)O)C(=O)O
+AssemblyReady COCCC(C(=O)O)C(=O)NN=NC(=O)O
+AssemblyReady CCCCNCCN(CCC(=O)O)CC(=O)O
+AssemblyReady O=C(O)CCCCCCC(=O)C(=O)O
+AssemblyReady CCCCC(C(=O)O)C(=O)O
+AssemblyReady C=C(O)C(OCCCCCC(=O)O)C(=O)O
+AssemblyReady CNC(C)(CCC(C)C(=O)O)C(=O)O
+AssemblyReady O=C(O)C=CCCCCC(=O)O
+AssemblyReady NCCCCCCCCCCCC(C(=O)O)=C(CCC(=O)O)C(=O)O
+AssemblyReady O=C(O)CCCCCN(CCC(=O)O)C1CCCCCC1
+AssemblyReady CCC=NNC(C)=C(CCCCCC(=O)O)C(=O)O
+AssemblyReady CCC(C)=C(CC(O)(O)C(=O)O)C(=O)O
+AssemblyReady CCCNN(C(=O)O)C(=O)CC(C)C(=O)O
+DISCONNECTED C.CCN.O=CO.O=CO
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CupOFMoCA-PROTAC/results/ablation_all/both_s123_clean.smi

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CupOFMoCA-PROTAC/results/ablation_all/both_s42.smi

@@ -0,0 +1,100 @@
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CupOFMoCA-PROTAC/results/ablation_all/both_s42_clean.smi

@@ -0,0 +1,100 @@
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CupOFMoCA-PROTAC/results/ablation_all/both_s456.smi

@@ -0,0 +1,100 @@
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CupOFMoCA-PROTAC/results/ablation_all/both_s456_clean.smi

@@ -0,0 +1,100 @@
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CupOFMoCA-PROTAC/results/ablation_all/defog_local_edit_20260726_224039_final.json

@@ -0,0 +1,2502 @@
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CupOFMoCA-PROTAC/results/ablation_all/defog_local_edit_20260726_224039_summary.csv

@@ -0,0 +1,101 @@
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