Communications in Information and Systems

Volume 19 (2019)

Number 1

Comparison of two algorithms of direct coupling analysis of protein

Pages: 1 – 15

DOI: https://dx.doi.org/10.4310/CIS.2019.v19.n1.a1

Authors

Xiaoling He (Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China)

Kangkun Mao (Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China)

Jun Wang (Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China)

Chen Zeng (Department of Physics, George Washington University, Washington, District of Columbia, U.S.A.; and School of Life Sciences, Jianghan University, Wuhan, China)

Yi Xiao (Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China)

Abstract

It has been shown that the residue-residue contacts in protein tertiary structures can be inferred from sequence coevolution information by using direct coupling analysis (DCA). This has greatly advanced protein structure prediction. However, current DCA algorithms still give many false positives and need further improvements. Here we analyze two popular algorithms of DCA: mean-field approximation (mfDCA) and pseudo-likelihood maximization (plmDCA). We compare their performances and suggest a simple method to reduce the false positives.

Published 18 April 2019