Department of Chemistry, Gebze Technical University, 41400, Gebze, Kocaeli, Turkey.
Department of Molecular Biology and Genetics, Gebze Technical University, 41400, Gebze, Kocaeli, Turkey.
J Comput Aided Mol Des. 2024 Mar 27;38(1):15. doi: 10.1007/s10822-024-00554-4.
Here, we introduce the use of ANI-ML potentials as a rescoring function in the host-guest interaction in molecular docking. Our results show that the "docking power" of ANI potentials can compete with the current scoring functions at the same level of computational cost. Benchmarking studies on CASF-2016 dataset showed that ANI is ranked in the top 5 scoring functions among the other 34 tested. In particular, the ANI predicted interaction energies when used in conjunction with GOLD-PLP scoring function can boost the top ranked solution to be the closest to the x-ray structure. Rapid and accurate calculation of interaction energies between ligand and protein also enables screening of millions of drug candidates/docking poses. Using a unique protocol in which docking by GOLD-PLP, rescoring by ANI-ML potentials and extensive MD simulations along with end state free energy methods are combined, we have screened FDA approved drugs against the SARS-CoV-2 main protease (M). The top six drug molecules suggested by the consensus of these free energy methods have already been in clinical trials or proposed as potential drug molecules in previous theoretical and experimental studies, approving the validity and the power of accuracy in our screening method.
在这里，我们介绍了将ANI-ML 势能用作分子对接中主客体相互作用的重新评分函数。我们的结果表明，ANI 势能的“对接能力”可以在相同的计算成本下与当前的评分函数竞争。在 CASF-2016 数据集上的基准研究表明，ANI 在其他 34 种测试的评分函数中排名前 5。特别是，当将 ANI 预测的相互作用能与 GOLD-PLP 评分函数一起使用时，可以将排名最高的解决方案提升到最接近 X 射线结构的位置。配体和蛋白质之间相互作用能的快速准确计算也能够筛选出数百万种候选药物/对接构象。我们使用了一种独特的方案，该方案结合了 GOLD-PLP 的对接、ANI-ML 势能的重新评分以及广泛的 MD 模拟和末端状态自由能方法，对 FDA 批准的药物进行了针对 SARS-CoV-2 主蛋白酶 (M) 的筛选。这些自由能方法的共识建议的前六种药物分子已经在临床试验中或在之前的理论和实验研究中被提议作为潜在的药物分子，证明了我们筛选方法的有效性和准确性。
