Literature DB >> 16800513

Continuum solvation models in the linear interaction energy method.

Jens Carlsson1, Martin Andér, Martin Nervall, Johan Aqvist.   

Abstract

The linear interaction energy (LIE) method in combination with two different continuum solvent models has been applied to calculate protein-ligand binding free energies for a set of inhibitors against the malarial aspartic protease plasmepsin II. Ligand-water interaction energies are calculated from both Poisson-Boltzmann (PB) and Generalized Born (GB) continuum models using snapshots from explicit solvent simulations of the ligand and protein-ligand complex. These are compared to explicit solvent calculations, and we find close agreement between the explicit water and PB solvation models. The GB model overestimates the change in solvation energy, and this is caused by consistent underestimation of the effective Born radii in the protein-ligand complex. The explicit solvent LIE calculations and LIE-PB, with our standard parametrization, reproduce absolute experimental binding free energies with an average unsigned error of 0.5 and 0.7 kcal/mol, respectively. The LIE-GB method, however, requires a constant offset to approach the same level of accuracy.

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Year:  2006        PMID: 16800513     DOI: 10.1021/jp056929t

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  15 in total

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Journal:  J Comput Aided Mol Des       Date:  2011-12-25       Impact factor: 3.686

2.  Ligand binding to the voltage-gated Kv1.5 potassium channel in the open state--docking and computer simulations of a homology model.

Authors:  Martin Andér; Victor B Luzhkov; Johan Aqvist
Journal:  Biophys J       Date:  2007-09-28       Impact factor: 4.033

Review 3.  Biomolecular simulation and modelling: status, progress and prospects.

Authors:  Marc W van der Kamp; Katherine E Shaw; Christopher J Woods; Adrian J Mulholland
Journal:  J R Soc Interface       Date:  2008-12-06       Impact factor: 4.118

4.  Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands.

Authors:  Stefano Costanzi; Irina G Tikhonova; T Kendall Harden; Kenneth A Jacobson
Journal:  J Comput Aided Mol Des       Date:  2008-05-16       Impact factor: 3.686

5.  Computational Design of PDZ-Peptide Binding.

Authors:  Nicolas Panel; Francesco Villa; Vaitea Opuu; David Mignon; Thomas Simonson
Journal:  Methods Mol Biol       Date:  2021

6.  The linear interaction energy method for the prediction of protein stability changes upon mutation.

Authors:  Lauren Wickstrom; Emilio Gallicchio; Ronald M Levy
Journal:  Proteins       Date:  2011-10-31

7.  Assessment of free energy predictors for ligand binding to a methyllysine histone code reader.

Authors:  Cen Gao; J Martin Herold; Dmitri Kireev
Journal:  J Comput Chem       Date:  2011-12-20       Impact factor: 3.376

8.  Molecular dynamics simulations show that conformational selection governs the binding preferences of imatinib for several tyrosine kinases.

Authors:  Alexey Aleksandrov; Thomas Simonson
Journal:  J Biol Chem       Date:  2010-03-03       Impact factor: 5.157

9.  The Binding Energy Distribution Analysis Method (BEDAM) for the Estimation of Protein-Ligand Binding Affinities.

Authors:  Emilio Gallicchio; Mauro Lapelosa; Ronald M Levy
Journal:  J Chem Theory Comput       Date:  2010-09-14       Impact factor: 6.006

10.  Modeling Protein-Ligand Binding by Mining Minima.

Authors:  Wei Chen; Michael K Gilson; Simon P Webb; Michael J Potter
Journal:  J Chem Theory Comput       Date:  2010-10-08       Impact factor: 6.006

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