Literature DB >> 34888724

Computational Tools for Accurate Binding Free-Energy Prediction.

Maria M Reif1, Martin Zacharias2.   

Abstract

A quantitative thermodynamic understanding of the noncovalent association of (bio)molecules is of central importance in molecular life sciences. An important quantity characterizing (bio)molecular association is the binding affinity or absolute binding free energy. In recent years, the computational prediction of absolute binding free energies has evolved considerably in terms of accuracy, computational speed, and user-friendliness. In this chapter, we first give an overview of how absolute free energies are defined and how they can be determined with computational means. We proceed with an outline of the theoretical basis of the two most reliable methods, potential of mean force, and double decoupling calculations. In particular, we describe how the sampling problem can be alleviated by application of restraints. Finally, we provide step-by-step instructions of how to set up corresponding molecular simulations with a commonly employed molecular dynamics simulation engine.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Binding free energy; Double decoupling; Free-energy calculation; Molecular dynamics simulations; Potential of mean force

Mesh:

Substances:

Year:  2022        PMID: 34888724     DOI: 10.1007/978-1-0716-1767-0_12

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  55 in total

Review 1.  Molecular recognition and docking algorithms.

Authors:  Natasja Brooijmans; Irwin D Kuntz
Journal:  Annu Rev Biophys Biomol Struct       Date:  2003-01-28

2.  Sampling protein motion and solvent effect during ligand binding.

Authors:  Vittorio Limongelli; Luciana Marinelli; Sandro Cosconati; Concettina La Motta; Stefania Sartini; Laura Mugnaini; Federico Da Settimo; Ettore Novellino; Michele Parrinello
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-11       Impact factor: 11.205

3.  Ligand binding affinity prediction by linear interaction energy methods.

Authors:  T Hansson; J Marelius; J Aqvist
Journal:  J Comput Aided Mol Des       Date:  1998-01       Impact factor: 3.686

4.  The statistical-thermodynamic basis for computation of binding affinities: a critical review.

Authors:  M K Gilson; J A Given; B L Bush; J A McCammon
Journal:  Biophys J       Date:  1997-03       Impact factor: 4.033

5.  Protein-ligand docking using hamiltonian replica exchange simulations with soft core potentials.

Authors:  Manuel P Luitz; Martin Zacharias
Journal:  J Chem Inf Model       Date:  2014-06-09       Impact factor: 4.956

Review 6.  Advances in the calculation of binding free energies.

Authors:  Anita de Ruiter; Chris Oostenbrink
Journal:  Curr Opin Struct Biol       Date:  2020-02-20       Impact factor: 6.809

7.  A new method for predicting binding affinity in computer-aided drug design.

Authors:  J Aqvist; C Medina; J E Samuelsson
Journal:  Protein Eng       Date:  1994-03

Review 8.  Predicting Binding Free Energies: Frontiers and Benchmarks.

Authors:  David L Mobley; Michael K Gilson
Journal:  Annu Rev Biophys       Date:  2017-04-07       Impact factor: 12.981

9.  Recent development and application of constant pH molecular dynamics.

Authors:  Wei Chen; Brian H Morrow; Chuanyin Shi; Jana K Shen
Journal:  Mol Simul       Date:  2014-01-01       Impact factor: 2.178

Review 10.  Molecular docking and structure-based drug design strategies.

Authors:  Leonardo G Ferreira; Ricardo N Dos Santos; Glaucius Oliva; Adriano D Andricopulo
Journal:  Molecules       Date:  2015-07-22       Impact factor: 4.411

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