Density functional theory calculations on entire proteins for free energies of binding: application to a model polar binding site
Density functional theory calculations on entire proteins for free energies of binding: application to a model polar binding site
In drug optimization calculations, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method can be used to compute free energies of binding of ligands to proteins. The method involves the evaluation of the energy of configurations in an implicit solvent model. One source of errors is the force field used, which can potentially lead to large errors due to the restrictions in accuracy imposed by its empirical nature. To assess the effect of the force field on the calculation of binding energies, in this article we use large-scale density functional theory (DFT) calculations as an alternative method to evaluate the energies of the configurations in a “QM-PBSA” approach. Our DFT calculations are performed with a near-complete basis set and a minimal parameter implicit solvent model, within the self-consistent calculation, using the ONETEP program on protein–ligand complexes containing more than 2600 atoms. We apply this approach to the T4-lysozyme double mutant L99A/M102Q protein, which is a well-studied model of a polar binding site, using a set of eight small aromatic ligands. We observe that there is very good correlation between the MM and QM binding energies in vacuum but less so in the solvent. The relative binding free energies from DFT are more accurate than the ones from the MM calculations, and give markedly better agreement with experiment for six of the eight ligands. Furthermore, in contrast to MM-PBSA, QM-PBSA is able to correctly predict a nonbinder. Proteins 2014; 82:3335–3346. © 2014 Wiley Periodicals, Inc.
3335-3346
Fox, Stephen
e7aa2bff-d251-42cc-b6d8-965f10c8cc5f
Dziedzic, Jacek
8e2fdb55-dade-4ae4-bf1f-a148a89e4383
Fox, Thomas
04c97900-df28-4af0-a7ca-62e5efcfcaba
Tautermann, Christofer S.
f35b4fb9-df35-4e57-8d68-8e20b5a177fd
Skylaris, Chris-Kriton
8f593d13-3ace-4558-ba08-04e48211af61
21 October 2014
Fox, Stephen
e7aa2bff-d251-42cc-b6d8-965f10c8cc5f
Dziedzic, Jacek
8e2fdb55-dade-4ae4-bf1f-a148a89e4383
Fox, Thomas
04c97900-df28-4af0-a7ca-62e5efcfcaba
Tautermann, Christofer S.
f35b4fb9-df35-4e57-8d68-8e20b5a177fd
Skylaris, Chris-Kriton
8f593d13-3ace-4558-ba08-04e48211af61
Fox, Stephen, Dziedzic, Jacek, Fox, Thomas, Tautermann, Christofer S. and Skylaris, Chris-Kriton
(2014)
Density functional theory calculations on entire proteins for free energies of binding: application to a model polar binding site.
Proteins: Structure, Function, and Bioinformatics, 82 (12), .
(doi:10.1002/prot.24686).
(PMID:25212393)
Abstract
In drug optimization calculations, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method can be used to compute free energies of binding of ligands to proteins. The method involves the evaluation of the energy of configurations in an implicit solvent model. One source of errors is the force field used, which can potentially lead to large errors due to the restrictions in accuracy imposed by its empirical nature. To assess the effect of the force field on the calculation of binding energies, in this article we use large-scale density functional theory (DFT) calculations as an alternative method to evaluate the energies of the configurations in a “QM-PBSA” approach. Our DFT calculations are performed with a near-complete basis set and a minimal parameter implicit solvent model, within the self-consistent calculation, using the ONETEP program on protein–ligand complexes containing more than 2600 atoms. We apply this approach to the T4-lysozyme double mutant L99A/M102Q protein, which is a well-studied model of a polar binding site, using a set of eight small aromatic ligands. We observe that there is very good correlation between the MM and QM binding energies in vacuum but less so in the solvent. The relative binding free energies from DFT are more accurate than the ones from the MM calculations, and give markedly better agreement with experiment for six of the eight ligands. Furthermore, in contrast to MM-PBSA, QM-PBSA is able to correctly predict a nonbinder. Proteins 2014; 82:3335–3346. © 2014 Wiley Periodicals, Inc.
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Accepted/In Press date: 31 August 2014
e-pub ahead of print date: 11 September 2014
Published date: 21 October 2014
Organisations:
Computational Systems Chemistry
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Local EPrints ID: 396121
URI: http://eprints.soton.ac.uk/id/eprint/396121
ISSN: 0887-3585
PURE UUID: 0f50d218-3406-489a-b3db-04bb29935110
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Date deposited: 02 Jun 2016 13:27
Last modified: 15 Mar 2024 03:35
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Author:
Stephen Fox
Author:
Thomas Fox
Author:
Christofer S. Tautermann
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