Python-C parallel KVFinder
The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, openings [WIP], hydropathy, and interface residues and their frequencies) in target biomolecular structures using a dual-probe system. In addition to cavity detection, pyKVFinder also estimates the molecular volume, using van der Waals (vdW) surface, solvent excluded surface (SES), and solvent accessible surface (SAS) to represent the molecular surface.
Python package
The pyKVFinder package is easily imported into Python scripts with a set of functions that enables full and standard workflows and step-by-step analysis.
Command-line interface
The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterizations are depth (per cavity point, maximum and average) and hydropathy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, WimleyWhite, and ZhaoLondon).
What's Changed
* Bump pytest from 7.3.0 to 7.3.1 by dependabot in https://github.com/LBC-LNBio/pyKVFinder/pull/28
* Update average hydropathy calculation by jvsguerra in https://github.com/LBC-LNBio/pyKVFinder/pull/29
**Full Changelog**: https://github.com/LBC-LNBio/pyKVFinder/compare/v0.5.3...v0.5.4