Alchemical binding free energy calculations in AMBER20: Advances and best practices for drug discovery

Tai Sung Lee, Bryce K. Allen, Timothy J. Giese, Zhenyu Guo, Pengfei Li, Charles Lin, T. Dwight McGee, David A. Pearlman, Brian K. Radak, Yujun Tao, Hsu Chun Tsai, Huafeng Xu, Woody Sherman, Darrin M. York

Research output: Contribution to journalArticlepeer-review

138 Scopus citations


Predicting protein-ligand binding affinities and the associated thermodynamics of biomolecular recognition is a primary objective of structure-based drug design. Alchemical free energy simulations offer a highly accurate and computationally efficient route to achieving this goal. While the AMBER molecular dynamics package has successfully been used for alchemical free energy simulations in academic research groups for decades, widespread impact in industrial drug discovery settings has been minimal because of the previous limitations within the AMBER alchemical code, coupled with challenges in system setup and postprocessing workflows. Through a close academia-industry collaboration we have addressed many of the previous limitations with an aim to improve accuracy, efficiency, and robustness of alchemical binding free energy simulations in industrial drug discovery applications. Here, we highlight some of the recent advances in AMBER20 with a focus on alchemical binding free energy (BFE) calculations, which are less computationally intensive than alternative binding free energy methods where full binding/ unbinding paths are explored. In addition to scientific and technical advances in AMBER20, we also describe the essential practical aspects associated with running relative alchemical BFE calculations, along with recommendations for best practices, highlighting the importance not only of the alchemical simulation code but also the auxiliary functionalities and expertise required to obtain accurate and reliable results. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative BFE simulations in AMBER20, with a focus on real-world drug discovery applications.

Original languageEnglish (US)
Pages (from-to)5595-5623
Number of pages29
JournalJournal of Chemical Information and Modeling
Issue number11
StatePublished - Nov 23 2020

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences


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