PyKVFinder: an efficient and integrable Python package for biomolecular cavity detection and characterization in data science.

ABSTRACT:

Background

Biomolecular interactions that modulate biological processes occur mainly in cavities throughout the surface of biomolecular structures. In the data science era, structural biology has benefited from the increasing availability of biostructural data due to advances in structural determination and computational methods. In this scenario, data-intensive cavity analysis demands efficient scripting routines built on easily manipulated data structures. To fulfill this need, we developed pyKVFinder, a Python package to detect and characterize cavities in biomolecular structures for data science and automated pipelines.

Results

pyKVFinder efficiently detects cavities in biomolecular structures and computes their volume, area, depth and hydropathy, storing these cavity pr

SUBMITTER: Guerra JVDS 

PROVIDER: S-EPMC8685811 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature