Vukovic Sinisa, Brennan Paul E, Huggins David J
Department of Physics, Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge, CB3 0HE, UK.
J Phys Condens Matter. 2016 Sep 1;28(34):344007. doi: 10.1088/0953-8984/28/34/344007. Epub 2016 Jul 1.
The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.
任何两个生物分子之间的相互作用都必须与它们和水分子的相互作用相竞争。这使得水成为医学中最重要的分子，因为它控制着每种治疗药物与其靶点的相互作用。一个与蛋白质结合的小分子能够通过取代特定水化位点上结合的水分子，识别蛋白质上独特的结合位点。对这些水分子相互作用进行量化，能让我们估算蛋白质结合小分子的潜力。这被称为配体可结合性。在这项研究中，我们描述了一种通过搜索蛋白质表面水化位点的所有可能组合来预测配体可结合性的方法。我们将配体可结合性预测为每个组成水化位点的结合自由能总和，使用非均匀流体溶剂化理论进行计算。我们将预测的配体可结合性与人类溴结构域家族中20种蛋白质的最大观察结合亲和力进行了比较。基于这种比较，确定已针对大多数溴结构域开发出了有效的抑制剂，其浓度范围为10至100 nM。然而，我们预测相对容易为溴结构域BPTF和BRD7开发出更有效的抑制剂，但为ATAD2开发抑制剂的进一步努力将极具挑战性。我们还对14个未通过等温滴定量热法报告小分子Kd值的溴结构域进行了预测。计算预测PBRM1(1)将是一个具有挑战性的靶点，而其他如TAF1L(2)、PBRM1(4)和TAF1(2)应该具有高度的配体可结合性。作为这项工作的成果，我们汇编了一个实验性最大Kd的数据库，可作为协助专注于溴结构域的药物化学研究的社区资源。配体可结合性的有效预测将是药物发现过程中非常有用的工具。
