ProIntVar: Protein Structure and Variation Analysis - Communications Biology Release

ProIntVar is a Python module dedicated to facilitating the integration of protein structure analyses with genetic variation data. It offers robust support for handling PDB/mmCIF structures, running and parsing DSSP, mapping PDB to UniProt sequences via SIFTS, computing and analyzing protein interfaces with Arpeggio, among other features. ProIntVar provides a comprehensive toolkit for researchers working at the intersection of structural biology and genomics.

This release archives the version of ProIntVar utilized in generating data for our publication, "A unified approach to evolutionary conservation and population constraint in protein domains highlights structural features and pathogenic sites.", accepted in principle by Communications Biology.

Please Note: This is an archival release intended for replication and citation purposes related to the publication. For those wishing to utilise ProIntVar for new projects, we recommend exploring more recent versions of the software for the latest features and enhancements.

Features:

• Reading and writing support for PDB/mmCIF structures.
• Integration with DSSP for secondary structure and solvent accessibility analysis.
• Interface computing with Arpeggio and addition of Hydrogen atoms using HBPLUS and Reduce.
• Capabilities to download and fetch data from multiple APIs, including Proteins API, PDBe REST API, and Ensembl REST.
• Simplified data integration using the TableMerger class, handling all data with Pandas data structures for efficient manipulation and analysis.

Citation:

For detailed methodology and findings, refer to our paper: Stuart A. MacGowan, Fábio Madeira, Thiago Britto-Borges, and Geoffrey J. Barton, "A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites." Pre-print available at https://doi.org/10.21203/rs.3.rs-3160340/v1.

License:

Released under the MIT license by Fábio Madeira and contributors at the University of Dundee.

Feedback and contributions to both ProIntVar are highly encouraged, aiming to refine and expand the capabilities of these tools for the scientific community.