Absolute binding free energies for virtual screening: A novel implementation of quantum mechanics/molecular mechanics (QM/MM) for FEP that allows substantial sampling and a significant quantum region

项目摘要 计算化学已经给药物发现带来了革命性的变化，使药物的数量减少了几个月甚至几年 发现和提炼一位领先候选人需要时间。计算化学的贡献无处不在 比虚拟筛选(VS)领域更大，以识别对药物靶标受体的初始命中。它是 现在例行公事地通过分子对接来筛选106-108个虚拟化合物以识别潜在的结合剂。一小块 其中一些将被购买和筛选，这是一个更慢和更昂贵的过程。而当 对接显然对暴力分类很有用，但对排序通常也不可靠。 在分类中幸存下来的化合物。存在着对计算方法的大量和未得到满足的需求 更好地进行排序，可以进一步减少幸存到购买/筛选的化合物数量。 人们对一种名为ABFE的方法越来越感兴趣，在这种方法中，不同分子的绝对结合自由能 配体可以被评估为一个共同的蛋白质受体靶标。这种方法是Relative的自然产物 结合自由能(RBFE)方法，其中最著名的是自由能微扰(FEP)。在……里面 资源和自动化工作流。 通过可靠的ABFE方法，进一步丰富来自码头的潜在粘结剂 可以获得筛选，提高了昂贵的筛选实验尾部的成本/命中率 竞选活动。 在FEP的基础上，使筛分内的ABFE计算成为可能的计算形式 已经描述了范型，一些出版物已经证明，它确实能够进一步 丰富在分子对接屏幕上幸存下来的化合物。这些计算仍然是有限的 通过两个问题：1)计算吞吐量；2)分子力学(MM)力场的局限性 在这些ABFE/FEP模拟中独家使用。计算吞吐量的限制是 通过云资源可用性的扩展越来越多地得到解决，因此MM部队的限制 字段是主要问题。 我们提出了一种ABFE/FEP方法，该方法将有限MM表示替换为基于 结合量子力学(QM)+MM的方法：QM/MM-其中处理配基结合区域 使用QM。与MM相比，QM对分子能量学的描述要精确得多，并且具有广泛的适用性 对于所有类别的分子配体，不像MM，它具有大量已知的限制/不足。 虚拟筛选，并演示QM/MM相对于传统MM方法的改进。

Project Summary Computational chemistry has revolutionized drug discovery, reducing by months or even years the amount of time it takes to discover and refine a lead candidate. Nowhere has the contribution of computational chemistry been greater than in the realm of virtual screening (VS) to identify an initial hit to a drug target receptor. It is now routine to screen 106-108 virtual compounds via molecular docking to identify potential binders. A small number of these will be purchased and screened, which is a slower and more expensive process. While docking is demonstrably useful for brute force triage, it is also generally unreliable for rank-ordering the compounds that survive the triage. There is a substantial and unmet need for computational methods that are better at rank ordering that can further reduce the number of compounds that survive to purchase/screening. Interest is growing in an approach termed ABFE, in which the Absolute Binding Free Energies of diverse ligands can be evaluated for a common protein receptor target. This approach is a natural outgrowth of relative binding free energy (RBFE) methods, the most well-known of which is Free Energy Perturbation (FEP). In recent years, the application of FEP for hit-to-lead optimization has exploded, thanks to increasing computer resources and automized workflows. With a reliable ABFE approach, further enrichment of the potential binders that come from dock-based screening can be obtained, improving the cost/hit ratio for the expensive experimental tail of the screening campaign. Based on FEP, the computational formalism that would make ABFE calculations possible within the screening paradigm has been described, and a few publications have demonstrated that it is, indeed, capable of further enriching the compounds that survive the molecular docking screen. These calculations have still been limited by two issues: 1) Computational throughput; 2) Limitations of the Molecular Mechanics (MM) force field that has been exclusively used in these ABFE/FEP simulations. The limitations of computational throughput are increasingly addressed by expansion in the availability of cloud resources, so the limitations of the MM force field are the primary issue. We propose an ABFE/FEP approach that replaces the limited MM representation with one based on a combined quantum mechanics (QM) +MM approach: QM/MM—where the region of ligand binding is treated using QM. In contrast to MM, QM describes molecular energetics much more exactly, and is broadly appliable to all classes of molecular ligands, unlike MM, which has a large number of known limitations/deficiencies. We will apply ABFE/FEP calculations to a variety of systems to validate the approach within the context of virtual screening, and to demonstrate the improvements that QM/MM allows versus traditional MM approaches.