biostudies-literatureOkimoto NJapan Society for the Promotion of Science4475-4485https://www.ebi.ac.uk/biostudies/studies/S-EPMC6641631biostudies-literatureUnknown3(4)In computational drug discovery, ranking a series of compound analogues in the order that is consistent with the experimental binding affinities remains a challenge. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics (MM)-based force fields, although they cannot completely describe protein-ligand interactions. By contrast, quantum mechanics (QM) calculations play an important role in understanding the protein-ligand interactions; however, their huge computational costs hinder their application in drug discovery. In this study, we have evaluated the ability to rank the binding affinities of tankyrase 2 ligands by combining both MM and QM calculations. Our computational approach uses the protein-ligand binding energies obtained fromACS omegaUse of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors.PMC6641631266101202279012216KT0168Taiji MOkimoto NOtsuka THirano YfalseUse of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein-Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors.In computational drug discovery, ranking a series of compound analogues in the order that is consistent with the experimental binding affinities remains a challenge. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics (MM)-based force fields, although they cannot completely describe protein-ligand interactions. By contrast, quantum mechanics (QM) calculations play an important role in understanding the protein-ligand interactions; however, their huge computational costs hinder their application in drug discovery. In this study, we have evaluated the ability to rank the binding affinities of tankyrase 2 ligands by combining both MM and QM calculations. Our computational approach uses the protein-ligand binding energies obtained from2018-01-01T00:00:00Z2018 Apr2026-05-07T05:28:20.167Z2025-05-18T13:15:33.962ZS-EPMC66416313145867310.1021/acsomega.8b00175