1
|
Xiong P, Hu X, Huang B, Zhang J, Chen Q, Liu H. Increasing the efficiency and accuracy of the ABACUS protein sequence design method. Bioinformatics 2019; 36:136-144. [DOI: 10.1093/bioinformatics/btz515] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 05/29/2019] [Accepted: 06/21/2019] [Indexed: 11/13/2022] Open
Abstract
Abstract
Motivation
The ABACUS (a backbone-based amino acid usage survey) method uses unique statistical energy functions to carry out protein sequence design. Although some of its results have been experimentally verified, its accuracy remains improvable because several important components of the method have not been specifically optimized for sequence design or in contexts of other parts of the method. The computational efficiency also needs to be improved to support interactive online applications or the consideration of a large number of alternative backbone structures.
Results
We derived a model to measure solvent accessibility with larger mutual information with residue types than previous models, optimized a set of rotamers which can approximate the sidechain atomic positions more accurately, and devised an empirical function to treat inter-atomic packing with parameters fitted to native structures and optimized in consistence with the rotamer set. Energy calculations have been accelerated by interpolation between pre-determined representative points in high-dimensional structural feature spaces. Sidechain repacking tests showed that ABACUS2 can accurately reproduce the conformation of native sidechains. In sequence design tests, the native residue type recovery rate reached 37.7%, exceeding the value of 32.7% for ABACUS1. Applying ABACUS2 to designed sequences on three native backbones produced proteins shown to be well-folded by experiments.
Availability and implementation
The ABACUS2 sequence design server can be visited at http://biocomp.ustc.edu.cn/servers/abacus-design.php.
Supplementary information
Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Peng Xiong
- School of Life Sciences, Hefei, Anhui 230026, China
| | - Xiuhong Hu
- School of Life Sciences, Hefei, Anhui 230026, China
| | - Bin Huang
- School of Life Sciences, Hefei, Anhui 230026, China
| | - Jiahai Zhang
- School of Life Sciences, Hefei, Anhui 230026, China
| | - Quan Chen
- School of Life Sciences, Hefei, Anhui 230026, China
| | - Haiyan Liu
- School of Life Sciences, Hefei, Anhui 230026, China
- Hefei National Laboratory for Physical Sciences at the Microscale, Hefei, Anhui 230026, China
- School of Data Science, University of Sciences and Technology of China, Hefei, Anhui 230026, China
| |
Collapse
|
2
|
Wang X, Huang SY. Integrating Bonded and Nonbonded Potentials in the Knowledge-Based Scoring Function for Protein Structure Prediction. J Chem Inf Model 2019; 59:3080-3090. [DOI: 10.1021/acs.jcim.9b00057] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Xinxiang Wang
- Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China
| | - Sheng-You Huang
- Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China
| |
Collapse
|