The development of advanced simulation methodology to address challenges in the calculation of protein-ligand binding affinities

研究方向：计算化学和理论化学。尽管严格的自由能计算在工业和学术界越来越广泛地使用，但仍有许多情况下，它们与实验结合自由能的一致性很差，以至于没有用。这些失败的原因几乎总是与分子动力学或Monte Carlo模拟过程中的构型采样不足或力场不足有关。在本项目中，这两个领域都将得到解决。首先，将开发一个混合蒙特卡罗（HMC）框架，以评估一系列新的移动类型。混合蒙特卡罗结合传统的分子动力学和蒙特卡罗到一个单一的方法，从而分子动力学是用来采样的配置空间的系统，但有一些偏见的介绍，和偏见的影响是由相关的蒙特卡罗测试删除。在第一种情况下，我们将采用我们的巨正则蒙特卡罗方法，并通过HMC将其与分子动力学耦合，但从长远来看，我们将引入新的偏置移动，包括从偏置速度分布或配体质子化变化中采样。通过这种方式，我们希望能够更有效地探索蛋白质-配体复合物的构型空间，从而产生更准确的结合affinity.Second，为了解决力场的缺陷，我们的混合QM/MM方法将从计算简单的水合自由能扩展到蛋白质-配体结合自由能。虽然我们在计算水合自由能方面取得了相当大的成功，但初步研究表明，蛋白质-配体结合是一个更困难的问题，尽管其确切原因尚不清楚。作为一个原型系统，我们将开始计算结合沃茨的结合自由能的神经氨酸酶蛋白质配体系统，因为获得一个QM/MM系综的配置是可能的，这样一个小的QM区域（一个水分子）。从这项研究中吸取的教训，我们将扩展到真实的蛋白质配体系统的药物相关性的模拟。

Research area:computational and theoretical chemistry.Despite rigorous free energy calculations becoming increasingly widely used in industry and academia, there are still many situations where their agreement with experimental binding free energies is so poor as to be useless. The reasons for these failures are almost invariably associated with either inadequate configurational sampling during the molecular dynamics or Monte Carlo simulation, or an inadequate force field. In this project, both areas will be addressed. First, a hybrid Monte Carlo (HMC) framework will be developed allowing a range of novel move types to be assessed. Hybrid Monte Carlo combines conventional molecular dynamics and Monte Carlo into a single approach, whereby molecular dynamics is used to sample the configuration space of a system, but with some bias introduced, and the effect of the bias is removed by the associated Monte Carlo test. In the first instance, we will take our grand canonical Monte Carlo method and couple it to molecular dynamics through HMC, but in the longer term we will look to introduce novel biasing moves including sampling from a biased velocity distribution or changes in ligand protonation. In this way we hope to be able to explore the configuration space of the protein-ligand complex more efficiently and hence yield more accurate binding affinities.Second, to address force field deficiencies, our hybrid QM/MM methodology will be extended from calculating simple hydration free energies to protein-ligand binding free energies. While we have had considerable success with calculating hydration free energies, preliminary studies suggest that protein-ligand binding is a much harder problem, although the precise reasons for this are unclear. As a prototypical system, we will start by calculating the binding free energies of bound waters in the neuraminidase protein-ligand system, since obtaining a QM/MM ensemble of configurations is possible for such a small QM region (a single water molecule). Taking the lessons learned from this study, we will extend the simulations to real protein-ligand systems of pharmaceutical relevance.