libraryPDB 0.1.0

Lightweight Python library for large-scale PDB structural analysis

libraryPDB

libraryPDB is a lightweight Python library for searching, downloading, parsing, cleaning and analyzing protein structures from the Protein Data Bank (PDB).

The library is designed for large-scale bioinformatics analyses, with a strong focus on:

• transparency
• reproducibility
• dependency-free workflows
• coarse-grained, interpretable structural descriptors

Unlike full-featured molecular modeling toolkits, libraryPDB deliberately avoids heavy object models and external dependencies, making it suitable for high-throughput structural screening and exploratory data analysis.

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Key features

• 🔍 Programmatic search and download of PDB structures (RCSB PDB Search v2 API)
• 🧹 Lightweight PDB cleaning and normalization
• 🧬 Simple PDB parsing without external parsers
• 📐 Cα-based structural descriptors
• ✅ Structural integrity and quality checks
• 📊 Single-call structure summary for large datasets
• 🚀 Designed for batch processing and big data analysis

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Installation

From GitHub (current version)

pip install git+https://github.com/CJ438837/libraryPDB.git

After installation:

import libraryPDB

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Design philosophy

• No heavy object-oriented models
• No external bioinformatics dependencies
• Direct manipulation of standard PDB text files
• Explicit and reproducible heuristics
• Functional, script-friendly API
• Suitable for thousands of structures

This library is not intended to replace tools such as PyMOL, MDTraj, or Biopython, but to provide a fast and transparent first-pass structural analysis toolkit.

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PDB search and download

libraryPDB provides simple wrappers around the official RCSB PDB Search v2 REST API.

Metadata-based search

from libraryPDB import advanced_search_and_download_pdb

pdb_files = advanced_search_and_download_pdb(
    save_dir="pdb_kinases",
    keywords=["kinase"],
    organisms=["Homo sapiens"],
    methods=["X-RAY DIFFRACTION"],
    max_results=100
)

print(len(pdb_files))

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PDB parsing and basic handling

All parsing functions operate directly on PDB files and return simple Python data structures.

Parse atoms

from libraryPDB import parse_atoms

atoms = parse_atoms("protein.pdb")
print(atoms[0])

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High-level structure summary

from libraryPDB import pdb_summary

summary = pdb_summary("protein.pdb")

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Typical applications

• Large-scale PDB dataset screening
• Structural diversity analysis
• Dataset curation and quality control
• Feature extraction for statistics or machine learning
• Rapid characterization of predicted structures (e.g. AlphaFold)

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License

MIT License