Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, Maryland, United States of America.
PLoS Comput Biol. 2022 Jun 3;18(6):e1010124. doi: 10.1371/journal.pcbi.1010124. eCollection 2022 Jun.
Despite the progress in prediction of protein complexes over the last decade, recent blind protein complex structure prediction challenges revealed limited success rates (less than 20% models with DockQ score > 0.4) on targets that exhibit significant conformational change upon binding. To overcome limitations in capturing backbone motions, we developed a new, aggressive sampling method that incorporates temperature replica exchange Monte Carlo (T-REMC) and conformational sampling techniques within docking protocols in Rosetta. Our method, ReplicaDock 2.0, mimics induced-fit mechanism of protein binding to sample backbone motions across putative interface residues on-the-fly, thereby recapitulating binding-partner induced conformational changes. Furthermore, ReplicaDock 2.0 clocks in at 150-500 CPU hours per target (protein-size dependent); a runtime that is significantly faster than Molecular Dynamics based approaches. For a benchmark set of 88 proteins with moderate to high flexibility (unbound-to-bound iRMSD over 1.2 Å), ReplicaDock 2.0 successfully docks 61% of moderately flexible complexes and 35% of highly flexible complexes. Additionally, we demonstrate that by biasing backbone sampling particularly towards residues comprising flexible loops or hinge domains, highly flexible targets can be predicted to under 2 Å accuracy. This indicates that additional gains are possible when mobile protein segments are known.
尽管在过去十年中,蛋白质复合物的预测取得了进展,但最近的盲蛋白质复合物结构预测挑战表明,在结合时表现出显著构象变化的靶标上,成功率有限(DockQ 得分>0.4 的模型不到 20%)。为了克服捕捉骨架运动的局限性,我们开发了一种新的激进采样方法,该方法在 Rosetta 中的对接协议中结合了温度复制交换蒙特卡罗(T-REMC)和构象采样技术。我们的方法 ReplicaDock 2.0 模拟了蛋白质结合的诱导契合机制,可在假定的界面残基上实时采样骨架运动,从而再现结合伴侣引起的构象变化。此外,ReplicaDock 2.0 针对每个目标(取决于蛋白质大小)的时钟速度为 150-500 CPU 小时;运行时间明显快于基于分子动力学的方法。对于一组具有中等至高度灵活性的 88 个蛋白质的基准集(无约束至约束 iRMSD 超过 1.2 Å),ReplicaDock 2.0 成功对接了 61%的中等灵活性复合物和 35%的高灵活性复合物。此外,我们证明,通过特别偏向于包含柔性环或铰链结构域的残基进行骨架采样,可以将高度灵活的靶标预测到低于 2 Å 的精度。这表明当已知可移动的蛋白质片段时,还可以获得更多的收益。