README.md

metadata

license: cc-by-4.0
tags:
  - protein
  - binder-design
  - alphafold2
  - alphafold3
configs:
  - config_name: default
    data_files: manifest.csv

litscrape: AlphaFold2 + AlphaFold3 metrics

Per-design AlphaFold2 and AlphaFold3 confidence metrics for the binder–target pairs in yk0/litscrape. The source dataset provides sequences only (no structures); these metrics were produced by predicting/scoring each complex from sequence.

4020 rows, one per binder–target pair (4020 scored ok).

How the metrics were computed

1. Target structure — each unique target sequence was folded once with AF2 monomer (ColabDesign hallucination protocol) to obtain a target template.
2. AF2 metrics (af2_*) — de novo AF2-Multimer (ColabDesign binder protocol, single model model_1_multimer_v3, 3 recycles, no MSA, no initial guess): the templated target + the binder sequence are folded into a complex, and confidence metrics are read out.
3. AF3 metrics (af3_*) — AF3Score run on the AF2-predicted complex, conditioned on those coordinates (init_guess=true, no MSA). These are AF3's confidence in the AF2 structure, not an independent de-novo AF3 prediction.

Columns

• Metadata / labels carried over from the source dataset: binder_id, source_publication, target, label, binding_affinity_nm, target_sequence, binder_sequence
• label — binary experimental binding label (1 = binder, 0 = non-binder).
• AF2 (model_1_multimer_v3): af2_complex_plddt, af2_ptm, af2_iptm, af2_pae, af2_ipae, af2_min_ipae (note: af2_complex_plddt/af2_iptm etc. are on a 0–1 scale; PAE values are normalised as in ColabDesign).
• AF3: af3_ptm, af3_iptm, af3_chain_A_plddt, af3_chain_A_pae, af3_chain_A_ptm, af3_chain_A_iptm, af3_chain_B_plddt, af3_chain_B_pae, af3_chain_B_ptm, af3_chain_B_iptm, af3_iptm_A_B (note: AF3 pLDDT is 0–100; af3_chain_B_* = binder chain; the per-chain iptm fields equal af3_iptm for a 2-chain complex).
• status, error.

Important caveats

• These are de-novo predictions from sequence, not refolds of designed structures, so confidence values are markedly lower than initial-guess pipelines (e.g. Proteina-Complexa evals) and are not directly comparable to them in absolute terms.
• The target template is an AF2-predicted monomer, so target-fold error propagates into every complex for that target.
• As classifiers of the experimental label, the metrics are weak-to-modest (binder pLDDT is the most predictive; AUC ~0.60–0.68 on litscrape, lower on proteinbase). AF3 closely tracks AF2 and adds little.