Individual skill
binding-affinity
Empirical affinity estimates, ligand energy inspection, docking-score consensus, and batch virtual screening. Full MM/GBSA requires a validated external workflow.
backend/cli/skills/chemistry/binding-affinity/SKILL.md
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- Last checked
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- Nov 6, 2026
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- Apache-2.0
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- agent Repository topic
- ai Repository topic
- bun Repository topic
- cli Repository topic
- llm Repository topic
- ml Repository topic
- open-source Repository topic
- research Repository topic
- science Repository topic
- ai-agent Repository topic
- binding-affinity Declared skill tag
- drug-discovery Declared skill tag
- scoring Declared skill tag
- mm/gbsa Declared skill tag
- virtual-screening Declared skill tag
- operations Derived category
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# Binding Affinity Prediction
## Overview
This skill predicts protein-ligand binding affinity from docked poses — converting structural information into estimated ΔG (kcal/mol), pKd, and Kd (nM). It complements the `molecular-docking` skill's interaction analysis (`score.py`) which counts contacts but does NOT predict binding strength in energy units.
**Key capabilities:**
- **Empirical scoring**: descriptor + contact-based affinity prediction using RDKit and BioPython
- **Ligand energy inspection**: explicitly selected RDKit heuristic; it does not calculate receptor-dependent binding energy
- **Full MM/GBSA**: use a separately validated external method; the bundled script does not implement it
- **Consensus scoring**: combine multiple scoring methods with rank-based normalization
- **Batch virtual screening**: efficiently score large compound libraries
