Alterlab pubchem

PubChem Database

Overview

PubChem is the world's largest freely available chemical database with 110M+ compounds and 270M+ bioactivities. Query chemical structures by name, CID, or SMILES, retrieve molecular properties, perform similarity and substructure searches, and access bioactivity data using the PUG-REST API and PubChemPy.

When to Use This Skill

This skill should be used when:

• Searching for chemical compounds by name, structure (SMILES/InChI), or molecular formula
• Retrieving molecular properties (MW, LogP, TPSA, hydrogen bonding descriptors)
• Performing similarity searches to find structurally related compounds
• Conducting substructure searches for specific chemical motifs
• Accessing bioactivity data from screening assays
• Converting between chemical identifier formats (CID, SMILES, InChI)
• Batch processing multiple compounds for drug-likeness screening or property analysis

Core Capabilities

PubChem access is organized into nine capability areas. Copy-ready snippets for each live in references/capabilities.md.

1. Chemical structure search — by name, CID, SMILES, InChI, or molecular formula.
2. Property retrieval — single, specific-list, or batch molecular properties.
3. Similarity search — Tanimoto similarity with threshold/MaxRecords.
4. Substructure search — find compounds containing a structural motif.
5. Format conversion — CID/SMILES/InChI/InChIKey and structure-file download.
6. Structure visualization — 2D PNG images via PubChemPy or direct URL.
7. Synonym retrieval — all known names for a compound.
8. Bioactivity data access — assay summaries via PUG-REST and helper script.
9. Comprehensive annotations — full PUG-View records (properties, drug info, safety, toxicity).

Core Workflow

The canonical entry point resolves an identifier to a compound, then reads properties:

import pubchempy as pcp

compound = pcp.get_compounds('aspirin', 'name')[0]
print(compound.cid, compound.molecular_formula, compound.molecular_weight)
print(compound.smiles, compound.xlogp, compound.tpsa)

Prefer CIDs for repeated queries (more efficient than names/structures). Similarity and substructure searches run asynchronously and may take 15-30 seconds; PubChemPy polls automatically. See references/best_practices.md for rate limits and error handling.

Installation Requirements

uv pip install 'pubchempy>=1.0.5'  # Python-based access (1.0.5 = current SMILES property names)
uv pip install requests            # direct API / bioactivity queries
uv pip install pandas              # optional, for data analysis

SMILES property naming (PubChem changed this in 2025): the PUG-REST CanonicalSMILES and IsomericSMILES properties are deprecated. Use SMILES (full SMILES with stereo/isotope info, replaces IsomericSMILES) and ConnectivitySMILES (connectivity-only, replaces CanonicalSMILES). In PubChemPy 1.0.5 the matching Compound attributes are compound.smiles and compound.connectivity_smiles (the old canonical_smiles / isomeric_smiles attributes still resolve but are deprecated).

Helper Scripts

This skill ships two Python helper scripts under scripts/:

• scripts/compound_search.py — search, property retrieval, similarity/substructure search, synonyms, batch search, and structure download.
• scripts/bioactivity_query.py — bioassay summaries, target identification, target-based compound search, and PUG-View annotations.

Full function inventories and usage are in references/helper_scripts.md.

Reference Index

• references/api_reference.md — Complete PUG-REST endpoint docs, full molecular property list, asynchronous request handling, PubChemPy API, PUG-View API, and official doc links.
• references/capabilities.md — Copy-ready code for all nine capability areas.
• references/workflows.md — Five end-to-end workflows (identifier conversion, drug-likeness screening, similar-candidate search, batch property comparison, substructure virtual screening).
• references/helper_scripts.md — Function inventory and usage for the two helper scripts.
• references/best_practices.md — Rate limits, best practices, error handling, troubleshooting, and additional resources.