Literature DB >> 24256082

Accuracy assessment and automation of free energy calculations for drug design.

Clara D Christ1, Thomas Fox.   

Abstract

As the free energy of binding of a ligand to its target is one of the crucial optimization parameters in drug design, its accurate prediction is highly desirable. In the present study we have assessed the average accuracy of free energy calculations for a total of 92 ligands binding to five different targets. To make this study and future larger scale applications possible we automated the setup procedure. Starting from user defined binding modes, the procedure decides which ligands to connect via a perturbation based on maximum common substructure criteria and produces all necessary parameter files for free energy calculations in AMBER 11. For the systems investigated, errors due to insufficient sampling were found to be substantial in some cases whereas differences in estimators (thermodynamic integration (TI) versus multistate Bennett acceptance ratio (MBAR)) were found to be negligible. Analytical uncertainty estimates calculated from a single free energy calculation were found to be much smaller than the sample standard deviation obtained from two independent free energy calculations. Agreement with experiment was found to be system dependent ranging from excellent to mediocre (RMSE = [0.9, 8.2, 4.7, 5.7, 8.7] kJ/mol). When restricting analyses to free energy calculations with sample standard deviations below 1 kJ/mol agreement with experiment improved (RMSE = [0.8, 6.9, 1.8, 3.9, 5.6] kJ/mol).

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Year:  2013        PMID: 24256082     DOI: 10.1021/ci4004199

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  39 in total

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Authors:  Tai-Sung Lee; Yuan Hu; Brad Sherborne; Zhuyan Guo; Darrin M York
Journal:  J Chem Theory Comput       Date:  2017-06-23       Impact factor: 6.006

2.  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

Review 3.  Free Energy Calculations for Protein-Ligand Binding Prediction.

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Journal:  Methods Mol Biol       Date:  2021

4.  Docking-undocking combination applied to the D3R Grand Challenge 2015.

Authors:  Sergio Ruiz-Carmona; Xavier Barril
Journal:  J Comput Aided Mol Des       Date:  2016-10-05       Impact factor: 3.686

5.  Prediction of SAMPL4 host-guest binding affinities using funnel metadynamics.

Authors:  Ya-Wen Hsiao; Pär Söderhjelm
Journal:  J Comput Aided Mol Des       Date:  2014-02-18       Impact factor: 3.686

6.  Computer-aided drug design at Boehringer Ingelheim.

Authors:  Ingo Muegge; Andreas Bergner; Jan M Kriegl
Journal:  J Comput Aided Mol Des       Date:  2016-09-20       Impact factor: 3.686

7.  Multiple binding modes of ibuprofen in human serum albumin identified by absolute binding free energy calculations.

Authors:  Stefania Evoli; David L Mobley; Rita Guzzi; Bruno Rizzuti
Journal:  Phys Chem Chem Phys       Date:  2016-11-30       Impact factor: 3.676

8.  Structure-based predictions of activity cliffs.

Authors:  Jarmila Husby; Giovanni Bottegoni; Irina Kufareva; Ruben Abagyan; Andrea Cavalli
Journal:  J Chem Inf Model       Date:  2015-05-11       Impact factor: 4.956

9.  Escaping Atom Types in Force Fields Using Direct Chemical Perception.

Authors:  David L Mobley; Caitlin C Bannan; Andrea Rizzi; Christopher I Bayly; John D Chodera; Victoria T Lim; Nathan M Lim; Kyle A Beauchamp; David R Slochower; Michael R Shirts; Michael K Gilson; Peter K Eastman
Journal:  J Chem Theory Comput       Date:  2018-10-30       Impact factor: 6.006

10.  Estimation of Solvation Entropy and Enthalpy via Analysis of Water Oxygen-Hydrogen Correlations.

Authors:  Camilo Velez-Vega; Daniel J J McKay; Tom Kurtzman; Vibhas Aravamuthan; Robert A Pearlstein; José S Duca
Journal:  J Chem Theory Comput       Date:  2015-10-21       Impact factor: 6.006

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