YuliaNuzhnenko Agent Skill: RDKit QSAR & Small-Molecule Bioactivity Skill
📌 Description
Computes 2048-bit ECFP4 Morgan fingerprints from SMILES, trains LightGBM regressors for pIC50 prediction, and extracts SHAP feature attributions.
🤖 Agent Execution Protocol
When an AI Agent is tasked with rdkit-qsar-pharmacophore:
- Input Validation: Verify that the required input files or coordinates are supplied.
- Environment Check: Ensure dependencies (
RDKit, LightGBM, SHAP, Scikit-Learn) are installed. - Execution: Run the protocol pipeline snippet below.
- Output Generation: Produce actionable Markdown/JSON summaries with publication figures.
💻 Protocol Code Snippet
from rdkit import Chem
from rdkit.Chem import AllChem
def get_ecfp4(smiles):
mol = Chem.MolFromSmiles(smiles)
return list(AllChem.GetMorganFingerprintAsBitVect(mol, 2, nBits=2048)) if mol else None
📥 Input & Output Specifications
Input Contract
- Target Files: Valid input data matching domain formats.
- Parameters: Quality thresholds and cutoffs.
Output Contract
- Results Table: Structured summary dataframe or matrix.
- Visualization: Rendered SVG/PNG figures.
📄 License
Distributed under the MIT License. See LICENSE for details.