Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200433, China.
Verna and Marrs Mclean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, One Baylor Plaza, BCM-125, Houston, Texas 77030, United States.
J Chem Theory Comput. 2020 Jun 9;16(6):3970-3976. doi: 10.1021/acs.jctc.0c00186. Epub 2020 May 6.
In this article, we propose a protein folding framework, named OPUS-Fold, which can integrate various methods for subproblems in protein structure prediction to contribute to folding. OPUS-Fold is based on torsion-angle sampling. After each sampling step, it reconstructs the structure and estimates the model quality with an energy function that is formed by combining many different constraining terms designed either by ourselves or by others in the literature. OPUS-Fold balances accuracy and efficiency, delivers good results in a short time, and leaves more space for including the results of other subproblem methods. Moreover, OPUS-Fold also contains a fast side-chain modeling method OPUS-Rota2 ( , (9), 5154-5160), which enables a speedy construction of all-atom atomic models during the folding process that allows the usage of all-atom-required subproblem methods. In summary, OPUS-Fold provides a protein folding platform for incorporating the results from various subproblem methods, including those containing nondifferentiable information such as partial experimental data. The source code of OPUS-Fold can be downloaded from https://github.com/thuxugang/opus_fold.
在本文中，我们提出了一个名为 OPUS-Fold 的蛋白质折叠框架，它可以整合蛋白质结构预测中各种子问题的方法，以促进折叠。OPUS-Fold 基于扭转角采样。在每次采样步骤后，它使用能量函数重建结构，并估计模型质量，该能量函数由我们自己或文献中其他人设计的许多不同约束项组合而成。OPUS-Fold 平衡了准确性和效率，在短时间内取得了良好的效果，并为包括其他子问题方法的结果留出了更多空间。此外，OPUS-Fold 还包含一种快速侧链建模方法 OPUS-Rota2 (, (9), 5154-5160)，它在折叠过程中能够快速构建全原子原子模型，从而允许使用需要全原子的子问题方法。总之，OPUS-Fold 为整合来自各种子问题方法的结果提供了一个蛋白质折叠平台，包括包含非可微信息（如部分实验数据）的方法。OPUS-Fold 的源代码可以从 https://github.com/thuxugang/opus_fold 下载。
