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

Autor: Guerra JVDS; Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas, SP, 13083-100, Brazil. joao.guerra@lnbio.cnpem.br.; Graduate Program in Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, University of Campinas, Campinas, SP, Brazil. joao.guerra@lnbio.cnpem.br., Ribeiro-Filho HV; Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas, SP, 13083-100, Brazil., Jara GE; Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas, SP, 13083-100, Brazil., Bortot LO; Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas, SP, 13083-100, Brazil., Pereira JGC; Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas, SP, 13083-100, Brazil., Lopes-de-Oliveira PS; Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), R. Giuseppe Máximo Scolfaro, 10000 - Bosque das Palmeiras, Campinas, SP, 13083-100, Brazil. paulo.oliveira@lnbio.cnpem.br.; Graduate Program in Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, University of Campinas, Campinas, SP, Brazil. paulo.oliveira@lnbio.cnpem.br.
Jazyk: angličtina
Zdroj: BMC bioinformatics [BMC Bioinformatics] 2021 Dec 20; Vol. 22 (1), pp. 607. Date of Electronic Publication: 2021 Dec 20.
DOI: 10.1186/s12859-021-04519-4
Abstrakt: 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 properties in NumPy arrays. Benefited from Python ecosystem interoperability and data structures, pyKVFinder can be integrated with third-party scientific packages and libraries for mathematical calculations, machine learning and 3D visualization in automated workflows. As proof of pyKVFinder's capabilities, we successfully identified and compared ADRP substrate-binding site of SARS-CoV-2 and a set of homologous proteins with pyKVFinder, showing its integrability with data science packages such as matplotlib, NGL Viewer, SciPy and Jupyter notebook.
Conclusions: We introduce an efficient, highly versatile and easily integrable software for detecting and characterizing biomolecular cavities in data science applications and automated protocols. pyKVFinder facilitates biostructural data analysis with scripting routines in the Python ecosystem and can be building blocks for data science and drug design applications.
(© 2021. The Author(s).)
Databáze: MEDLINE
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