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

开发先进的模拟方法来解决蛋白质-配体结合亲和力计算中的挑战

• 批准号: 1938296
• 金额: --
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1938296
• 关键词: development; advanced; simulation; methodology; address

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.

研究方向：计算与理论化学。尽管严格的自由能计算在工业界和学术界的应用越来越广泛，但仍有许多情况下，它们与实验束缚自由能的一致性很差，以至于无用。这些失败的原因几乎总是与分子动力学或蒙特卡罗模拟过程中的构型采样不足或力场不足有关。在这个项目中，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，允许评估一系列新颖的移动类型。混合蒙特卡罗将传统的分子动力学和蒙特卡罗方法结合为一种方法，利用分子动力学对系统的构型空间进行采样，但引入了一些偏置，并通过相关的蒙特卡罗测试消除偏置的影响。首先，我们将采用我们的经典蒙特卡罗方法，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动作，包括从偏置速度分布或配体质子化的变化中采样。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，从而获得更准确的结合亲和力。其次，为了解决力场缺陷，我们的混合QM/MM方法将从计算简单的水合自由能扩展到计算蛋白质-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，蛋白质与配体的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，我们将从计算神经氨酸酶蛋白-配体系统中结合水的结合自由能开始，因为对于这样一个小的QM区域（单个水分子），获得QM/MM的构型集合是可能的。从这项研究中吸取教训，我们将把模拟扩展到真正的药物相关的蛋白质配体系统。