Free energy methods in drug discovery : current state and future directions

Author(s)

    • Armacost, Kira A.
    • Thompson, David C.

Bibliographic Information

Free energy methods in drug discovery : current state and future directions

Kira A. Armacost, GlaxoSmithKline plc, Collegeville, Pennsylvania, United States, David C. Thompson, Chemical Computing Group, ULC Montréal, Canada, editors

(ACS symposium series, 1397)

American Chemical Society, [2021]

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Content Type: text (rdacontent), Media Type: unmediated (rdamedia), Carrier Type: volume (rdacarrier)

Summary: "This book is about Free Energy Methods in Drug Discovery: Current State and Future Directions"-- Provided by publisher

"Sponsored by the ACS Division of Computers in Chemistry."

Includes bibliographical references and index

Description and Table of Contents

Description

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.

Table of Contents

Preface Preface Chapter 1: Free Energy Methods in Drug Discovery-Introduction, Zoe Cournia, Christophe Chipot, Benoit Roux, Darrin M. York, and Woody Sherman Chapter 2: Use of Free Energy Methods in the Drug Discovery Industry, Katharina Meier, Joseph P. Bluck, and Clara D. Christ Chapter 3: Perspective on the SAMPL and D3R Blind Prediction Challenges for Physics-Based Free Energy Methods, Nicolas Tielker, Lukas Eberlein, Oliver Beckstein, Stefan Gussregen, Bogdan I. Iorga, Stefan M. Kast, and Shuai Liu Chapter 4: On the Issues Impacting Reproducibility of Alchemical Free Energy Calculations, Miroslav Suruzhon, Marley L. Samways, and Jonathan W. Essex Chapter 5: Prospective Application of Free Energy Methods in Drug Discovery Programs, Aysegul OEzen, Emanuele Perola, Natasja Brooijmans, and Joseph Kim Chapter 6: Computational Approaches for Protein pKa Calculations, Dilek Coskun Chapter 7: Robust, Efficient and Automated Methods for Accurate Prediction of Protein-Ligand Binding Affinities in AMBER Drug Discovery Boost, Tai-Sung Lee, Hsu-Chun Tsai, Abir Ganguly, Timothy J. Giese, and Darrin M. York Chapter 8: Impacting Drug Discovery Projects with Large-Scale Enumerations, Machine Learning Strategies, and Free-Energy Predictions, Jennifer L. Knight, Karl Leswing, Pieter H. Bos, and Lingle Wang Chapter 9: Optimizing Simulations Protocols for Relative Free Energy Calculations, Paul Labute and Maximilian Ebert Chapter 10: Fast, Routine Free Energy of Binding Estimation Using Movable Type, Lance M. Westerhoff and Zheng Zheng Chapter 11: Free Energy Methods in Drug Discovery: Who We Are, Where We Are, and Where We Are Going, Kira A. Armacost, Eric C. Gladstone, and David C. Thompson Editors' Biographies Author Index Subject Index

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