OPUS-Refine: A Fast Sampling-Based Framework for Refining Protein Backbone Torsion Angles and Global Conformation

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.