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


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".

SUBMITTER: Cole DJ 

PROVIDER: S-EPMC4339369 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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

Cole Daniel J DJ   Tirado-Rives Julian J   Jorgensen William L WL  

Biochimica et biophysica acta 20140906 5


<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Re  ...[more]

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