Free energy calculations in drug discovery

蛋白质-配体结合自由能是发现和优化新药的一个重要性质。在计算机辅助药物设计的背景下，能够准确、精确和可重复地计算电子计算机中的结合自由能对于减少开发候选药物所需的反复尝试的合成工作量是至关重要的。更有效和更有选择性的化合物将与所需的靶点结合得更强，而与相关蛋白质的结合则更弱。最近的商业软件产品已经将结合自由能计算的使用推向了制药行业的主流开发管道。然而，即使预先筛选合适的靶系统，也只在大约一半的情况下达到所需的1千卡·摩尔~(-1)的预测精度。在这个项目中，我们将在制药行业的背景下探讨这些自由能计算的精确度。我们将根据已公布的数据开发测试系统的大型数据集，并确定计算的自由能对模拟软件、参数、自由能计算方法和系统设置的选择的敏感性。基于这种敏感性分析，该项目的目标有两个：1.确定蛋白质-配体结合自由能计算不准确的主要原因。通过这一点，我们将能够先验地确定这些方法将在哪些系统上取得成功。这些信息将是非常有价值的，可以在不需要广泛和昂贵的实验验证的情况下确定那些方法将有用的情况。改进自由能计算方法以解决这些敏感性问题。

Protein-ligand binding free energy is a crucial property used in the discovery and optimisation of novel drugs. In the context of computer-aided drug design, being able to calculate accurate, precise and reproducible binding free energies in silico is essential in terms of reducing the amount of trial-and-error synthetic effort required to develop a candidate drug. More potent and selective compounds will bind strongly to the desired target, and show weak binding to related proteins. Recent commercial software products have pushed the use of binding free energy calculations into mainstream development pipelines within the pharmaceutical industry. Even with pre-screening of suitable target systems, however, the required predictive accuracy of 1 kcal mol-1 is only attained in around half of cases. Determining whether sufficient accuracy has been achieved for a particular system is currently not possible a priori and requires expensive and time-consuming experimental validation.In this project the accuracy of these free energy calculations in the context of the pharmaceutical industry will be explored. We will develop a large dataset of test systems based on published data and determine the sensitivity of the calculated free energies to the choice of simulation software, parameters, free energy calculation method and system setup. Based on this sensitivity analysis, the project objectives are twofold:1. To identify the primary causes of inaccuracy in protein-ligand binding free energy calculations. Through this we will be able to identify a priori on which systems these approaches will be successful. This information will be extremely valuable, allowing those cases where the methods will be useful to be identified without requiring extensive and expensive experimental validation.2. To improve free energy calculation methodology to address these sensitivities.