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Monte Carlo refinement of rigid-body protein docking structures with backbone displacement and side-chain optimization

机译:刚体蛋白质对接结构的Monte Carlo改进与主链位移和侧链优化

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摘要

Structures of hitherto unknown protein complexes can be predicted by docking the solved protein monomers. Here, we present a method to refine initial docking estimates of protein complex structures by a Monte Carlo approach including rigid-body moves and side-chain optimization. The energy function used is comprised of van der Waals, Coulomb, and atomic contact energy terms. During the simulation, we gradually shift from a novel smoothed van der Waals potential, which prevents trapping in local energy minima, to the standard Lennard-Jones potential. Following the simulation, the conformations are clustered to obtain the final predictions. Using only the first 100 decoys generated by a fast Fourier transform (FFT)-based rigid-body docking method, our refinement procedure is able to generate near-native structures (interface RMSD <2.5 Å) as first model in 14 of 59 cases in a benchmark set. In most cases, clear binding funnels around the native structure can be observed. The results show the potential of Monte Carlo refinement methods and emphasize their applicability for protein–protein docking.
机译:迄今未知的蛋白质复合物的结构可以通过对接已溶解的蛋白质单体来预测。在这里,我们提出了一种通过蒙特卡洛方法(包括刚体移动和侧链优化)来优化蛋白质复杂结构的初始对接估计的方法。使用的能量函数包括范德华力,库仑和原子接触能级。在模拟过程中,我们逐渐从一种新的平滑范德华势(该标准避免了局部能量最小值的陷阱)转移到标准Lennard-Jones势。在模拟之后,将构象聚类以获得最终预测。仅使用通过基于快速傅里叶变换(FFT)的刚体对接方法生成的前100个诱饵,我们的细化程序就能够生成近自然结构(界面RMSD <2.5Å)作为第一个模型(在59个案例中有14个案例)基准设定。在大多数情况下,可以观察到天然结构周围清晰的结合漏斗。结果显示了蒙特卡罗改进方法的潜力,并强调了它们在蛋白质-蛋白质对接中的适用性。

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