CavVis-A Field-of-View Geometric Algorithm for Protein Cavity Detection

被引:10
作者
Simoes, Tiago M. C. [1 ,2 ]
Gomes, Abel J. P. [1 ,2 ]
机构
[1] Inst Telecomunicacoes, P-6200001 Covilha, Portugal
[2] Univ Beira Interior, Dept Informat, P-6200001 Covilha, Portugal
关键词
BINDING-SITES; TRAVEL DEPTH; POCKETS; SHAPE; IDENTIFICATION; VISUALIZATION; SURFACES; MACROMOLECULES;
D O I
10.1021/acs.jcim.8b00572
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
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.
引用
收藏
页码:786 / 796
页数:11
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