Achieving reliability and high accuracy in automated protein docking: ClusPro, PIPER, SDU, and stability analysis in CAPRI rounds 13-19.
Achieving reliability and high accuracy in automated protein docking: ClusPro, PIPER, SDU, and stability analysis in CAPRI rounds 13-19.
复制标题
DOI:
10.1002/prot.22835
复制
发表时间:
2010-11-15
影响因子:
2.9
通讯作者:
Vajda, Sandor
中科院分区:
文献类型:
--
作者:
Kozakov, Dima;Hall, David R.;Beglov, Dmitri;Brenke, Ryan;Comeau, Stephen R.;Shen, Yang;Li, Keyong;Zheng, Jiefu;Vakili, Pirooz;Paschalidis, Ioannis Ch.;Vajda, Sandor
关键词:
Our approach to protein-protein docking includes three main steps. First we run PIPER, a rigid body docking program based on the Fast Fourier Transform (FFT) correlation approach, extended to use pairwise interactions potentials. Next, the 1000 best energy conformations are clustered, and the 30 largest clusters are retained for refinement. Third, the stability of the clusters is analyzed by short Monte Carlo simulations, and the structures are refined by the medium-range optimization method SDU. The first two steps of this approach are implemented in the ClusPro 2.0 protein-protein docking server. Despite being fully automated, the last step is computationally too expensive to be included in the server. Comparing the models obtained in CAPRI rounds 13–19 by ClusPro, by the refinement of the ClusPro predictions, and by all predictor groups, we arrived at three conclusions. First, for the first time in the CAPRI history, our automated ClusPro server was able to compete with the best human predictor groups. Second, selecting the top ranked models, our current protocol reliably generates high quality structures of protein-protein complexes from the structures of separately crystallized proteins, even in the absence of biological information, provided that there is limited backbone conformational change. Third, despite occasional successes, homology modeling requires further improvement to achieve reliable docking results.
登录
查看更多内容
影响因子:
2.9
作者:
Kozakov, Dima;Schueler-Furman, Ora;Vajda, Sandor
通讯作者:
Vajda, Sandor
影响因子:
3
作者:
Zhang, Yang
通讯作者:
Zhang, Yang
影响因子:
3.4
作者:
Lu, H;Lu, L;Skolnick, J
通讯作者:
Skolnick, J
影响因子:
2.9
作者:
Liu, S;Zhang, C;Zhou, YQ
通讯作者:
Zhou, YQ
影响因子:
3.4
作者:
Chuang, Gwo-Yu;Kozakov, Dima;Vajda, Sandor
通讯作者:
Vajda, Sandor