Optimal designs for pairwise calculation: An application to free energy perturbation in minimizing prediction variability-Reference-Cited by-同舟云学术

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Optimal designs for pairwise calculation: An application to free energy perturbation in minimizing prediction variability

Published:2019-11-13 Issue:3 Volume:41 Page:247-257
ISSN:0192-8651
Container-title:Journal of Computational Chemistry
language:en
Short-container-title:J Comput Chem

Author:

Yang Qingyi¹^ORCID,Burchett Woodrow²,Steeno Gregory S.²,Liu Shuai³,Yang Mingjun³,Mobley David L.⁴,Hou Xinjun¹

Affiliation:

1. Medicine Design, Worldwide Research & Development Pfizer Inc. 1 Portland St Cambridge Massachusetts 02139

2. Early Clinical Development, Worldwide Research & Development Pfizer Inc. 445 Eastern Point Rd Groton Connecticut 06340

3. XtalPi Inc. One Broadway Cambridge Massachusetts 02142

4. Department of Pharmaceutical Sciences and Department of ChemistryUniversity of California 3134B Natural Sciences I Irvine California 92697

Publisher

Wiley

Subject

Computational Mathematics,General Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.26095

Reference35 articles.

1. Free energy calculations: Applications to chemical and biochemical phenomena

2. Towards Accurate Free Energy Calculations in Ligand Protein-Binding Studies

3. What determines the strength of noncovalent association of ligands to proteins in aqueous solution?

4. Perspective on Free-Energy Perturbation Calculations for Chemical Equilibria

5. Computations of Standard Binding Free Energies with Molecular Dynamics Simulations

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3. Development and Comprehensive Benchmark of a High-Quality AMBER-Consistent Small Molecule Force Field with Broad Chemical Space Coverage for Molecular Modeling and Free Energy Calculation;Journal of Chemical Theory and Computation;2023-12-29

4. Fast free energy estimates from λ-dynamics with bias-updated Gibbs sampling;Nature Communications;2023-12-21

5. Free Energy Estimation for Drug Discovery: Background and Perspectives;Applied Computer-Aided Drug Design: Models and Methods;2023-12-07

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