Incorporation of Solvent Effect into Multi-Objective Evolutionary Algorithm for Improved Protein Structure Prediction
Document Type
Article
Publication Date
7-1-2018
Abstract
The problem of predicting the three-dimensional (3-D) structure of a protein from its one-dimensional sequence has been called the 'holy grail of molecular biology', and it has become an important part of structural genomics projects. Despite the rapid developments in computer technology and computational intelligence, it remains challenging and fascinating. In this paper, to solve it we propose a multi-objective evolutionary algorithm. We decompose the protein energy function Chemistry at HARvard Macromolecular Mechanics force fields into bond and non-bond energies as the first and second objectives. Considering the effect of solvent, we innovatively adopt a solvent-accessible surface area as the third objective. We use 66 benchmark proteins to verify the proposed method and obtain better or competitive results in comparison with the existing methods. The results suggest the necessity to incorporate the effect of solvent into a multi-objective evolutionary algorithm to improve protein structure prediction in terms of accuracy and efficiency.
Identifier
85029187836 (Scopus)
Publication Title
IEEE ACM Transactions on Computational Biology and Bioinformatics
External Full Text Location
https://doi.org/10.1109/TCBB.2017.2705094
ISSN
15455963
PubMed ID
28534784
First Page
1365
Last Page
1378
Issue
4
Volume
15
Grant
17K12751
Fund Ref
Japan Society for the Promotion of Science
Recommended Citation
Gao, Shangce; Song, Shuangbao; Cheng, Jiujun; Todo, Yuki; and Zhou, Meng Chu, "Incorporation of Solvent Effect into Multi-Objective Evolutionary Algorithm for Improved Protein Structure Prediction" (2018). Faculty Publications. 8587.
https://digitalcommons.njit.edu/fac_pubs/8587
