# Cheminformatics

> Chemical informatics and modeling

- Skill: `ffsshhttiikk/cheminformatics` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ffsshhttiikk/cheminformatics`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ffsshhttiikk/cheminformatics/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: MIT
- Author: ffsshhttiikk (https://skillmd.com/u/ffsshhttiikk)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ffsshhttiikk/cheminformatics

---


## What I do

- Apply computational methods to chemical data analysis
- Design and search chemical databases
- Predict molecular properties and reactivity
- Perform molecular similarity analysis
- Develop quantitative structure-activity relationships (QSAR)
- Visualize and analyze chemical structures

## When to use me

- When searching chemical databases
- When predicting molecular properties
- When building QSAR/QSPR models
- When analyzing molecular similarity
- When virtual screening compounds
- When managing chemical data

## Key Concepts

### Molecular Descriptors

**Constitutional Descriptors**
- Molecular weight
- Atom counts (C, H, O, N, etc.)
- Number of rings
- LogP (lipophilicity)

**Topological Descriptors**
- Wiener index
- Balaban index
- Connectivity indices
- Hydrogen bond donors/acceptors

```python
# Example: Simple molecular fingerprint
def morgan_fingerprint(molecule, radius=2):
    """Generate Morgan/ECFP fingerprint."""
    # Simplified representation
    return {
        'features': extract_substructures(molecule, radius),
        'bit_vector': encode_as_bits(features),
        'similarity': lambda other: tanimoto_coefficient(features, other)
    }
```

### Chemical File Formats

- SMILES: String representation
- SDF: Structure-data file
- MOL: MOL file format
- PDB: 3D structure
- InChI: IUPAC identifier

### Similarity Metrics

- Tanimoto coefficient (Jaccard)
- Dice similarity
- Cosine similarity
- Euclidean distance