What is the RCSB PDB?

The RCSB Protein Data Bank (PDB) is the global repository for 3D structural data of biological macromolecules, including proteins and nucleic acids.

What Python libraries are required?

The skill primarily uses the 'rcsb-api' package. It also integrates well with BioPython for parsing and analyzing the downloaded coordinate files.

Can I search for structures using a protein sequence?

Yes, the skill includes SequenceQuery capabilities, allowing you to find structures by sequence similarity with specific E-value and identity cutoffs.

Which coordinate file formats can I download?

This skill supports downloading structures in modern mmCIF, legacy PDB, and compressed BinaryCIF formats.

Does this skill support AlphaFold models?

Yes, it can access computed structure models, including AlphaFold entries, which typically use the 'AF_' prefix.

PDB Database Structural Biology

Name: PDB Database Structural Biology
Author: ricable

byricable

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Ciencia de Datos y ML

Accesses and analyzes 3D protein and nucleic acid structures from the RCSB Protein Data Bank for research and discovery.

Acerca de

The PDB Database skill enables Claude to programmatically interact with the RCSB PDB, the global repository for macromolecular structural data. It provides comprehensive capabilities for searching over 200,000 structures by text, sequence, or 3D geometry, downloading coordinate files in modern mmCIF or legacy PDB formats, and extracting rich metadata. This skill is essential for structural biologists and bioinformaticians working on drug discovery, protein engineering, and computational biology workflows within the Claude Code environment.

Características Principales

1 GitHub stars
Automated coordinate file downloads in PDB, mmCIF, and BinaryCIF formats
Advanced structure searching by text, attribute, sequence, and 3D geometry
Batch processing and metadata extraction for multiple entries
Flexible data retrieval via GraphQL and standard Python APIs
Seamless integration with structural biology libraries like BioPython

Casos de Uso

Automating the collection of high-resolution structural datasets for machine learning
Finding homologous structures for protein engineering and homology modeling
Identifying drug targets and analyzing ligand binding sites for pharmaceutical research

Acerca de

Características Principales

1 GitHub stars
Automated coordinate file downloads in PDB, mmCIF, and BinaryCIF formats
Advanced structure searching by text, attribute, sequence, and 3D geometry
Batch processing and metadata extraction for multiple entries
Flexible data retrieval via GraphQL and standard Python APIs
Seamless integration with structural biology libraries like BioPython

Casos de Uso

Automating the collection of high-resolution structural datasets for machine learning
Finding homologous structures for protein engineering and homology modeling
Identifying drug targets and analyzing ligand binding sites for pharmaceutical research