ParKVFinder: A thread-level parallel approach in biomolecular cavity detection

Author(s)

da Silva Guerra, Joao Victor ^{[1, 2]} ; Ribeiro Filho, Helder Veras ^[1] ; Bortot, Leandro Oliveira ^[1] ; Honorato, Rodrigo Vargas ^{[1, 3]} ; de Carvalho Pereira, Jose Geraldo ^[1] ; Lopes-de-Oliveira, Paulo Sergio ^{[1, 2]}

Affiliation

^[1] Brazilian Ctr Res Energy & Mat CNPEM, Brazilian Biosci Natl Lab LNBio, BR-13083100 Campinas, SP - Brazil

^[2] Univ Estadual Campinas, Inst Biol, Grad Program Biosci & Technol Bioact Prod, BR-13083862 Campinas, SP - Brazil

^[3] Univ Utrecht, Fac Sci Chem, Bijvoet Ctr Biomol Res, Padualaan 8, NL-3584 CH Utrecht - Netherlands

• Document type: Journal article
• Source: SOFTWAREX; v. 12, JUL-DEC 2020.
• Web of Science Citations: 0

Abstract

Biological processes are regulated mainly by the binding of small molecules into cavities distributed throughout the biomolecular structure. Computational tools to detect these cavities have an essential role in rational drug design. With the exponential availability of high-order 3D atomic structures and large sets of atomic models, the tools must balance accuracy and speed. In this sense, we developed parKVFinder, a parallelized software for geometry-based cavity detection. Here, we described its functionalities and presented its easy-to-use PyMOL plugin and command-line interface. Finally, we demonstrated parKVFinder by identifying an important HIV-1 protease cavity and compared it with other geometry-based programs. (C) 2020 The Author(s). Published by Elsevier B.V. (AU)

• FAPESP's process: 18/00629-0 - Detection and characterization of protein cavities using parallel computing and molecular descriptors
• Grantee: Paulo Sergio Lopes de Oliveira
• Support Opportunities: Regular Research Grants