Description

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Panoramic review of free energy methods

Continuous improvement in both hardware and software has resulted in the widespread use of rigorous free energy methodologies in the field of drug discovery. Given this, the practitioner, development, and commercial communities find themselves in ever closer collaboration working to apply these methodologies in the search for novel therapeutic agents. This work presents contributions from expert leaders across the free energy field and explores both the current and possible future states of method development, application, and utilization. Researchers engaged in computational, physical, and pharmaceutical research will find this collection valuable.

About the Author

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Kira A. Armacost received her undergraduate degree in chemistry at the University of Tampa, Ph.D. from Auburn University, and performed postdoctoral research at the University of Michigan. The focus of her doctoral and postdoctoral research was using free energy calculations in organic chemistry and drug discovery. After her postdoctoral fellowship, she accepted a position at Merck & Co., Inc. working on drug discovery projects for multiple therapeutic areas. Kira recently transitioned to GlaxoSmithKline Pharmaceuticals in the Computational Sciences group performing research in drug discovery. Kira has been actively involved in the ACS, serving as an alternate councilor for ACS COMP, previously chaired the Journal of Chemical Information and Modeling's Early Career Board (2017-2020) and is now on the Editorial Advisory board for JCIM. She also participates in STEM initiatives for middle and high school students, is a co-organizer for the Women Make COMP symposium at ACS meetings and is a mentor for girls and women in computational chemistry. David C. Thompson has an undergraduate degree in Chemical Physics from University College London, and a Ph.D. in Theoretical Chemistry from the University of Cambridge. Following a post-doctoral fellowship focused on numerical methods in electronic structure, David transitioned into the pharmaceutical industry and spent many years providing computational support and solutions to drug discovery programs. David's research spans foundational quantum mechanics through open innovation, crowd sourcing, and novel methods of organizational learning. Currently at Chemical Computing Group (CCG), David is a member of the support team helping CCG customers translate their scientific problems into actionable solutions.