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license: cc-by-4.0 |
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license: cc-by-4.0 |
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# 🧬 DrugCLIP data repository |
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This repository hosts benchmark datasets, pre-computed molecular embeddings, pretrained model weights, and supporting files used in the **DrugCLIP** project. It also includes data and models used for **wet lab validation experiments**. |
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## 📁 Repository Contents |
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### 1. `DUD-E.zip` |
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- Full dataset for the **DUD-E benchmark**. |
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- Includes ligand and target files for all targets. |
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### 2. `LIT-PCBA.zip` |
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- Full dataset for the **LIT-PCBA benchmark**. |
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- Includes ligand and target files for all targets. |
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### 3. `encoded_mol_embs.zip` |
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- Pre-encoded molecular embeddings from the **ChemDiv** compound library. |
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- Each `.pkl` file contains: |
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- `name_list`: `[hitid, SMILES]` |
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- `embedding_list`: list of **128-dimensional** vectors |
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- Versions included: |
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- **8-fold** version of the full ChemDiv library |
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- **6-fold** version of the full ChemDiv library |
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- **6-fold** version of a filtered ChemDiv library |
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### 4. `benchmark_weights.zip` |
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Contains **pretrained model weights** for **benchmark experiments** on the DUD-E and LIT-PCBA datasets using various ligand and target filtering strategies. |
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#### 🔬 DUD-E: Ligand Filtering Strategies |
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| Filename | Description | |
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|----------------------|-------------| |
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| `dude_ecfp_90.pt` | Trained by removing ligands with **ECFP4 similarity > 0.9**. | |
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| `dude_ecfp_60.pt` | Trained by removing ligands with **ECFP4 similarity > 0.6**. | |
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| `dude_ecfp_30.pt` | Trained by removing ligands with **ECFP4 similarity > 0.3**. | |
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| `dude_scaffold.pt` | Trained by removing ligands sharing **scaffolds** with test set. | |
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#### 🧬 DUD-E: Target Filtering Strategies |
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| Filename | Description | |
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|------------------------|-------------| |
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| `dude_identity_90.pt` | Removed targets with **MMseqs2 identity > 0.9**. | |
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| `dude_identity_60.pt` | Removed targets with **MMseqs2 identity > 0.6**. | |
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| `dude_identity_30.pt` | Removed targets with **MMseqs2 identity > 0.3**. | |
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| `dude_identity_0.pt` | Removed targets based on **HMMER sequence identity**. | |
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#### 🧪 LIT-PCBA: Target Filtering Strategy |
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| Filename | Description | |
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|-------------------------|-------------| |
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| `litpcba_identity_90.pt`| Removed targets with **MMseqs2 identity > 0.9**. | |
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### 5. `model_weights.zip` |
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Contains model weights trained specifically for **wet lab experiments**. These models were trained using: |
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- **6-fold** data splits |
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- **8-fold** data splits |
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Used to predict compounds validated in real-world assays for the following targets: |
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- `5HT2a` |
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- `NET` |
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- `Trip12` |
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### 6. `WetLab_PDBs_and_LMDBs` |
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Target data used for wet lab validation experiments: |
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- **LMDB files**: For DrugCLIP screening |
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Includes data for: |
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- `5HT2a` |
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- `NET` |
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- `Trip12` |
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### 7. `benchmark_throughput` |
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Files for reproducing throughput benchmark results. |
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