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. 2015 May;1850(5):966-971.
doi: 10.1016/j.bbagen.2014.08.018. Epub 2014 Sep 6.

Molecular dynamics and Monte Carlo simulations for protein-ligand binding and inhibitor design

Daniel J Cole  1 , Julian Tirado-Rives  1 , William L Jorgensen  2
Affiliations

Molecular dynamics and Monte Carlo simulations for protein-ligand binding and inhibitor design

Daniel J Cole et al. Biochim Biophys Acta. 2015 May.

Abstract

Background: Non-nucleoside inhibitors of HIV reverse transcriptase are an important component of treatment against HIV infection. Novel inhibitors are sought that increase potency against variants that contain the Tyr181Cys mutation.

Methods: Molecular dynamics based free energy perturbation simulations have been run to study factors that contribute to protein-ligand binding, and the results are compared with those from previous Monte Carlo based simulations and activity data.

Results: Predictions of protein-ligand binding modes are very consistent for the two simulation methods; the accord is attributed to the use of an enhanced sampling protocol. The Tyr181Cys binding pocket supports large, hydrophobic substituents, which is in good agreement with experiment.

Conclusions: Although some discrepancies exist between the results of the two simulation methods and experiment, free energy perturbation simulations can be used to rapidly test small molecules for gains in binding affinity.

General significance: Free energy perturbation methods show promise in providing fast, reliable and accurate data that can be used to complement experiment in lead optimization projects. This article is part of a Special Issue entitled "Recent developments of molecular dynamics".

Keywords: Enhanced sampling; Free energy perturbation; Non-nucleoside inhibitors of HIV-1 reverse transcriptase; Replica exchange with solute tempering.

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Figures

Fig. 1
Fig. 1
The benzyloxazole molecule.
Fig. 2
Fig. 2
Dihedral angle distributions along the R = i-Pr to Et transformation inWT HIV-RT from (a) MCPRO [8] and (b) Desmond FEP/REST simulations.
Fig. 3
Fig. 3
Snapshots from the Desmond FEP/REST simulation showing R = i-Pr at (a) φ = 180° and (b) φ = 330°.
Fig. 4
Fig. 4
Sampling of dihedral angle distributions from MCPRO and Desmond FEP/REST simulations of the inhibitor bound to the wild-type HIV-RT protein for R = Pr, OEt and CH2OMe.
Fig. 5
Fig. 5
Snapshots from the Desmond FEP/REST simulations showing (a) R = i-Pr and (b) R = CH2OMe with the Y181C variant of HIV-RT.
See this image and copyright information in PMC

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