Title: An improved convex and concave index for revealing the exposure degree of atoms in protein 3D structure

Authors: Xiao Wang; Jian Zhao; Yujiao Yan; Jingye Qian; Ping Han; Xiaofeng Song

Addresses: Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China ' Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China ' Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China ' Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China ' Department of Gynaecology and Obstetrics, The First affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, 210029, China ' Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China

Abstract: Geometric property of protein surface contributes largely to the protein function in the cells, and descriptors of measuring the convexity and concavity of protein surfaces can help understand the protein function. Motivated by CX algorithm, we developed an improved surface structural parameter named convex-and-concave index (CCI) to describe geometric properties of protein surface. The proposed CCI eliminates the defect of coarse computing for the overlap volume of two adjacent atom spheres in CX algorithm, by dividing the probe sphere into many cubic lattices and labelling the cubic lattices inside the atoms or not, respectively. The results indicated that the CCI algorithm improved the accuracy of CX, and not increased the computing complexity. The proposed CCI is a fast and simple method that can accurately describe the exposure degree of atoms in protein and reveal protein functional sites, such as active sites and ubiquitination sites.

Keywords: structural parameter; convex-and-concave index; CCI; degree of exposure; protein surface; active site; ubiquitination site.

DOI: 10.1504/IJCBDD.2017.088135

International Journal of Computational Biology and Drug Design, 2017 Vol.10 No.4, pp.331 - 342

Received: 12 May 2017
Accepted: 30 May 2017
Published online: 24 Nov 2017 *

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