PDF(Pubmed)
Abstract：
Polarization and charge-transfer interactions play an important role in ligand-receptor complexes containing metals, and only quantum mechanics methods can adequately describe their contribution to the binding energy. In this work, we selected a set of benzenesulfonamide ligands of human Carbonic Anhydrase II (hCA II)-an important druggable target containing a Zn2+ ion in the active site-as a case study to predict the binding free energy in metalloprotein-ligand complexes and designed specialized computational methods that combine the ab initio fragment molecular orbital (FMO) method and GRID approach. To reproduce the experimental binding free energy in these systems, we adopted a machine-learning approach, here named formula generator (FG), considering different FMO energy terms, the hydrophobic interaction energy (computed by GRID) and logP. The main advantage of the FG approach is that it can find nonlinear relations between the energy terms used to predict the binding free energy, explicitly showing their mathematical relation. This work showed the effectiveness of the FG approach, and therefore, it might represent an important tool for the development of new scoring functions. Indeed, our scoring function showed a high correlation with the experimental binding free energy (R2 = 0.76-0.95, RMSE = 0.34-0.18), revealing a nonlinear relation between energy terms and highlighting the relevant role played by hydrophobic contacts. These results, along with the FMO characterization of ligand-receptor interactions, represent important information to support the design of new and potent hCA II inhibitors.
摘要：
极化和电荷转移相互作用在含有金属的配体-受体复合物中起重要作用，只有量子力学方法才能充分描述它们对结合能的贡献。在这项工作中,我们选择了一组人类碳酸酐酶II（hCAII）的苯磺酰胺配体-一种重要的药物靶标，在活性位点包含Zn2离子-作为案例研究，以预测金属蛋白-配体复合物中的结合自由能，并设计了结合从头算片段分子轨道（FMO）方法和GRID方法的专门计算方法。为了重现这些系统中的实验结合自由能，我们采用了机器学习的方法，这里命名为公式生成器(FG)，考虑到不同的FMO能源术语，疏水相互作用能(由GRID计算)和logP。FG方法的主要优点是它可以找到用于预测结合自由能的能量项之间的非线性关系，明确显示他们的数学关系。这项工作表明了FG方法的有效性，因此,它可能是开发新评分函数的重要工具。的确,我们的评分函数显示与实验结合自由能高度相关（R2=0.76-0.95，RMSE=0.34-0.18），揭示了能量项之间的非线性关系，并强调了疏水接触所起的相关作用。这些结果,随着配体-受体相互作用的FMO表征，代表支持设计新的和有效的hCAII抑制剂的重要信息。
