Cresset, New Cambridge House , Bassingbourn Road , Litlington , Cambridgeshire SG8 0SS , U.K.
J Med Chem. 2019 Mar 28;62(6):3036-3050. doi: 10.1021/acs.jmedchem.8b01925. Epub 2019 Mar 13.
Electrostatic interactions between small molecules and their respective receptors are essential for molecular recognition and are also key contributors to the binding free energy. Assessing the electrostatic match of protein-ligand complexes therefore provides important insights into why ligands bind and what can be changed to improve binding. Ideally, the ligand and protein electrostatic potentials at the protein-ligand interaction interface should maximize their complementarity while minimizing desolvation penalties. In this work, we present a fast and efficient tool to calculate and visualize the electrostatic complementarity (EC) of protein-ligand complexes. We compiled benchmark sets demonstrating electrostatically driven structure-activity relationships (SAR) from literature data, including kinase, protein-protein interaction, and GPCR targets, and used these to demonstrate that the EC method can visualize, rationalize, and predict electrostatically driven ligand affinity changes and help to predict compound selectivity. The methodology presented here for the analysis of EC is a powerful and versatile tool for drug design.
小分子与其相应受体之间的静电相互作用对于分子识别至关重要,也是结合自由能的主要贡献者。因此,评估蛋白-配体复合物的静电匹配情况可以深入了解配体结合的原因以及可以改变哪些因素以提高结合能力。理想情况下,蛋白-配体相互作用界面处的配体和蛋白静电势应该最大限度地互补,同时最小化去溶剂化惩罚。在这项工作中,我们提出了一种快速有效的计算和可视化蛋白-配体复合物静电互补性(EC)的工具。我们编译了基准集,从文献数据中展示了静电驱动的结构活性关系(SAR),包括激酶、蛋白-蛋白相互作用和 GPCR 靶点,并利用这些基准集证明了 EC 方法可以可视化、合理化和预测静电驱动的配体亲和力变化,并有助于预测化合物的选择性。这里提出的用于分析 EC 的方法是一种强大而通用的药物设计工具。