CavVis - A field-of-view geometric algorithm for protein cavity detection

• Autor(a) principal: Simões, Tiago M. C.
• Data de Publicação: 2019
• Outros Autores: Gomes, Abel
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.6/8295
• topic: Protein pocket; Protein pocket detection; Protein cavity; Protein cavity detection; Molecular graphics

Several geometric-based methods have been developed for the last two to three decades to detect and identify cavities (i.e., putative binding sites) on proteins, as needed to study protein–ligand interactions and protein docking. This paper introduces a new protein cavity method, called CavVis, which combines voxelization (i.e., a grid of voxels) and an analytic formulation of Gaussian surfaces that approximates the solvent-excluded surface. This method builds upon visibility of points on protein surface to find its cavities. Specifically, the visibility criterion combines three concepts we borrow from computer graphics, the field-of-view of each surface point, voxel ray casting, and back-face culling.