Journal
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 16, Issue 2, Pages 1359-1366Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.9b01054
Keywords
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Funding
- National Basic Research Program of China [2019YFC1711600]
- Shanghai Municipal Science and Technology Major Project [2018SHZDZX01]
- National Institutes of Health [R01-GM127628, R01-GM116280]
- Welch Foundation [Q-1826, Q-1512]
- Gillson-Longenbaugh Foundation
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Protein backbone torsion angles (Phi and Psi) are crucial for protein local conformation description. In this paper, we propose a general postprocessing method for all prediction methods, namely, OPUS-Refine, which may contribute to the field in a different way. OPUS-Refine is a sampling-based method, therefore, the results of other prediction methods can be used as its constraints. After OPUS-Refine refinement, for instance, the accuracy of Phi/Psi predicted by SPIDER3 and SPOT-1D are both increased. In addition, to facilitate the sampling efficiency, we construct a neighbor-dependent statistical torsion angles sampling database, namely, OPUS-TA, which may be useful for other sampling-based methods. Furthermore, we also introduce the contact map predicted by RaptorX to OPUS-Refine as a global structural constraint. After refinement, compared to the predicted structures obtained from RaptorX online server, the accuracy of both global structural configurations (measured by TM-score and RMSD) and local structural configurations (measured by Phi/Psi) results are improved. OPUS-Refine is a highly efficient framework, it takes only about 4 s to refine the torsion angles and 30 s to refine the global structure of a protein with 100 residues in length on a typical desktop personal computer. Therefore, the sampling-based feature and the efficiency of OPUS-Refine offer greater potentiality for it to take advantage of any other method to achieve better performance.
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