Andrusier Nelly, Nussinov Ruth, Wolfson Haim J
School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel.
Proteins. 2007 Oct 1;69(1):139-59. doi: 10.1002/prot.21495.
Here, we present FireDock, an efficient method for the refinement and rescoring of rigid-body docking solutions. The refinement process consists of two main steps: (1) rearrangement of the interface side-chains and (2) adjustment of the relative orientation of the molecules. Our method accounts for the observation that most interface residues that are important in recognition and binding do not change their conformation significantly upon complexation. Allowing full side-chain flexibility, a common procedure in refinement methods, often causes excessive conformational changes. These changes may distort preformed structural signatures, which have been shown to be important for binding recognition. Here, we restrict side-chain movements, and thus manage to reduce the false-positive rate noticeably. In the later stages of our procedure (orientation adjustments and scoring), we smooth the atomic radii. This allows for the minor backbone and side-chain movements and increases the sensitivity of our algorithm. FireDock succeeds in ranking a near-native structure within the top 15 predictions for 83% of the 30 enzyme-inhibitor test cases, and for 78% of the 18 semiunbound antibody-antigen complexes. Our refinement procedure significantly improves the ranking of the rigid-body PatchDock algorithm for these cases. The FireDock program is fully automated. In particular, to our knowledge, FireDock's prediction results are comparable to current state-of-the-art refinement methods while its running time is significantly lower. The method is available at http://bioinfo3d.cs.tau.ac.il/FireDock/.
在此,我们展示了FireDock,一种用于刚体对接解决方案优化和重新评分的高效方法。优化过程包括两个主要步骤:(1) 界面侧链的重排,以及 (2) 分子相对取向的调整。我们的方法考虑到这样一个观察结果:大多数在识别和结合中起重要作用的界面残基在形成复合物时其构象不会发生显著变化。允许完全的侧链灵活性,这是优化方法中的常见步骤,通常会导致过度的构象变化。这些变化可能会扭曲预先形成的结构特征,而这些特征已被证明对结合识别很重要。在此,我们限制侧链运动,从而成功显著降低假阳性率。在我们方法的后期阶段(取向调整和评分),我们平滑原子半径。这允许主链和侧链有微小的运动,并提高了我们算法的灵敏度。对于30个酶 - 抑制剂测试案例中的83%,以及18个半结合抗体 - 抗原复合物中的78%,FireDock成功地将近天然结构排在前15个预测结果之中。对于这些案例,我们的优化过程显著提高了刚体PatchDock算法的排名。FireDock程序是完全自动化的。特别是,据我们所知,FireDock的预测结果可与当前最先进的优化方法相媲美,而其运行时间则显著更低。该方法可在http://bioinfo3d.cs.tau.ac.il/FireDock/获取。