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

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, whic...

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Bibliographic Details
Published in:Journal of chemical information and modeling 2019-02, Vol.59 (2), p.786-796
Main Authors: Simões, Tiago M. C, Gomes, Abel J. P
Format: Article
Language:English
Subjects:
Algorithms
Binding sites
Computer graphics
Culling
Docking
Field of view
Geometric algorithms
Holes
Ligands
Models, Molecular
Normal Distribution
Protein Conformation
Proteins
Proteins - chemistry
Proteins - metabolism
Surface Properties
Visibility
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Summary: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.
ISSN:1549-9596
1549-960X
DOI:10.1021/acs.jcim.8b00572