Absolute Binding Free Energy Calculation and Design of a Subnanomolar Inhibitor of Phosphodiesterase-10

Zhe Li, Yiyou Huang, Yinuo Wu, Jingyi Chen, Deyan Wu, Chang Guo Zhan, Hai Bin Luo

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Accurate prediction of absolute protein-ligand binding free energy could considerably enhance the success rate of structure-based drug design but is extremely challenging and time-consuming. Free energy perturbation (FEP) has been proven reliable but is limited to prediction of relative binding free energies of similar ligands (with only minor structural differences) in binding with a same drug target in practical drug design applications. Herein, a Gaussian algorithm-enhanced FEP (GA-FEP) protocol has been developed to enhance the FEP simulation performance, enabling to efficiently carry out the FEP simulations on vanishing the whole ligand and, thus, predict the absolute binding free energies (ABFEs). Using the GA-FEP protocol, the FEP simulations for the ABFE calculation (denoted as GA-FEP/ABFE) can achieve a satisfactory accuracy for both structurally similar and diverse ligands in a dataset of more than 100 receptor-ligand systems. Further, our GA-FEP/ABFE-guided lead optimization against phosphodiesterase-10 led to the discovery of a subnanomolar inhibitor (IC 50 = 0.87 nM, ~2000-fold improvement in potency) with cocrystal confirmation.

Original languageEnglish
Pages (from-to)2099-2111
Number of pages13
JournalJournal of Medicinal Chemistry
Volume62
Issue number4
DOIs
StatePublished - Feb 28 2019

Bibliographical note

Publisher Copyright:
© 2019 American Chemical Society.

ASJC Scopus subject areas

  • Molecular Medicine
  • Drug Discovery

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