Literature DB >> 28745501

Free Energy Methods in Drug Design: Prospects of "Alchemical Perturbation" in Medicinal Chemistry.

Billy J Williams-Noonan1, Elizabeth Yuriev1, David K Chalmers1.   

Abstract

Underpinning all drug discovery projects is the interaction between a drug and its target, usually a protein. Thus, improved methods for predicting the magnitude of protein-ligand interactions have the potential to improve the efficiency of drug development. In this review, we describe the principles of free energy methods used for the calculation of protein-ligand binding free energies, the challenges associated with these methods, and recent advances developed to address these difficulties. We then present case studies from 2005 to 2017, each demonstrating that alchemical free energy methods can assist rational drug design projects. We conclude that alchemical methods are becoming a feasible reality in medicinal chemistry research due to improved computational resources and algorithms and that alchemical free energy predictions methods are close to becoming a mainstream tool for medicinal chemists.

Mesh:

Year:  2017        PMID: 28745501     DOI: 10.1021/acs.jmedchem.7b00681

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  28 in total

1.  Computation of protein-ligand binding free energies using quantum mechanical bespoke force fields.

Authors:  Daniel J Cole; Israel Cabeza de Vaca; William L Jorgensen
Journal:  Medchemcomm       Date:  2019-02-27       Impact factor: 3.597

2.  Molecular dynamics simulations of an engineered T4 lysozyme exclude helix to sheet transition, and provide insights into long distance, intra-protein switchable motion.

Authors:  Laurence Biggers; Hadeer Elhabashy; Edward Ackad; Mohammad S Yousef
Journal:  Protein Sci       Date:  2019-11-21       Impact factor: 6.725

3.  Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization.

Authors:  Vincent D Ustach; Sirish Kaushik Lakkaraju; Sunhwan Jo; Wenbo Yu; Wenjuan Jiang; Alexander D MacKerell
Journal:  J Chem Inf Model       Date:  2019-05-08       Impact factor: 4.956

4.  Sampling Conformational Changes of Bound Ligands Using Nonequilibrium Candidate Monte Carlo and Molecular Dynamics.

Authors:  Sukanya Sasmal; Samuel C Gill; Nathan M Lim; David L Mobley
Journal:  J Chem Theory Comput       Date:  2020-02-24       Impact factor: 6.006

5.  Absolute binding free energies for the SAMPL6 cucurbit[8]uril host-guest challenge via the AMOEBA polarizable force field.

Authors:  Marie L Laury; Zhi Wang; Aaron S Gordon; Jay W Ponder
Journal:  J Comput Aided Mol Des       Date:  2018-10-15       Impact factor: 3.686

6.  Conformational Changes in Tyrosine 11 of Neurotensin Are Required to Activate the Neurotensin Receptor 1.

Authors:  Fabian Bumbak; Trayder Thomas; Billy J Noonan-Williams; Tasneem M Vaid; Fei Yan; Alice R Whitehead; Shoni Bruell; Martina Kocan; Xuan Tan; Margaret A Johnson; Ross A D Bathgate; David K Chalmers; Paul R Gooley; Daniel J Scott
Journal:  ACS Pharmacol Transl Sci       Date:  2020-04-29

7.  SAMPL6 host-guest challenge: binding free energies via a multistep approach.

Authors:  Yiğitcan Eken; Prajay Patel; Thomas Díaz; Michael R Jones; Angela K Wilson
Journal:  J Comput Aided Mol Des       Date:  2018-09-17       Impact factor: 3.686

8.  Multi-phase Boltzmann weighting: accounting for local inhomogeneity in molecular simulations of water-octanol partition coefficients in the SAMPL6 challenge.

Authors:  Andreas Krämer; Phillip S Hudson; Michael R Jones; Bernard R Brooks
Journal:  J Comput Aided Mol Des       Date:  2020-02-14       Impact factor: 3.686

9.  Challenges Encountered Applying Equilibrium and Nonequilibrium Binding Free Energy Calculations.

Authors:  Hannah M Baumann; Vytautas Gapsys; Bert L de Groot; David L Mobley
Journal:  J Phys Chem B       Date:  2021-04-27       Impact factor: 2.991

10.  AMOEBA binding free energies for the SAMPL7 TrimerTrip host-guest challenge.

Authors:  Yuanjun Shi; Marie L Laury; Zhi Wang; Jay W Ponder
Journal:  J Comput Aided Mol Des       Date:  2020-11-03       Impact factor: 3.686

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.