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Hit identification and binding mode predictions by rigorous free energy simulations

Hit identification and binding mode predictions by rigorous free energy simulations
Hit identification and binding mode predictions by rigorous free energy simulations
The identification of lead molecules using computational modeling often relies on approximate, high-throughput approaches, of limited accuracy. We show here that, with a methodology we recently developed, it is possible to predict the relative binding free energies of structurally diverse ligands of the estrogen receptor-? using a rigorous statistical thermodynamics approach. Predictions obtained from the simulations with an explicit solvation model are in good qualitative agreement with experimental data, while simulations with implicit solvent models or rank ordering by empirical scoring functions yield predictions of lower quality. In addition, it is shown that free energy techniques can be used to select the most likely binding mode from a set of possible orientations generated by a docking program. It is suggested that the free energy techniques outlined in this study can be used to rank-order, by potency, structurally diverse compounds identified by virtual screening, de novo design or scaffold hopping programs.
0022-2623
6654-6664
Michel, Julien
3dfda20a-a6fa-4214-8c7d-578f550b9ad7
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Michel, Julien
3dfda20a-a6fa-4214-8c7d-578f550b9ad7
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5

Michel, Julien and Essex, Jonathan W. (2008) Hit identification and binding mode predictions by rigorous free energy simulations. Journal of Medicinal Chemistry, 51 (21), 6654-6664. (doi:10.1021/jm800524s). (PMID:18834104)

Record type: Article

Abstract

The identification of lead molecules using computational modeling often relies on approximate, high-throughput approaches, of limited accuracy. We show here that, with a methodology we recently developed, it is possible to predict the relative binding free energies of structurally diverse ligands of the estrogen receptor-? using a rigorous statistical thermodynamics approach. Predictions obtained from the simulations with an explicit solvation model are in good qualitative agreement with experimental data, while simulations with implicit solvent models or rank ordering by empirical scoring functions yield predictions of lower quality. In addition, it is shown that free energy techniques can be used to select the most likely binding mode from a set of possible orientations generated by a docking program. It is suggested that the free energy techniques outlined in this study can be used to rank-order, by potency, structurally diverse compounds identified by virtual screening, de novo design or scaffold hopping programs.

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e-pub ahead of print date: 4 October 2008
Published date: 13 November 2008
Organisations: Chemistry

Identifiers

Local EPrints ID: 149199
URI: http://eprints.soton.ac.uk/id/eprint/149199
ISSN: 0022-2623
PURE UUID: 56f45aff-744b-4a56-85c6-6185375fb32a
ORCID for Jonathan W. Essex: ORCID iD orcid.org/0000-0003-2639-2746

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Date deposited: 30 Apr 2010 08:42
Last modified: 26 Nov 2019 02:02

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