Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations

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Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations. / Bastys, Tomas; Gapsys, Vytautas; Doncheva, Nadezhda T.; Kaiser, Rolf; De Groot, Bert L.; Kalinina, Olga V.

In: Journal of Chemical Theory and Computation, Vol. 14, No. 7, 10.07.2018, p. 3397-3408.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Bastys, T, Gapsys, V, Doncheva, NT, Kaiser, R, De Groot, BL & Kalinina, OV 2018, 'Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations', Journal of Chemical Theory and Computation, vol. 14, no. 7, pp. 3397-3408. https://doi.org/10.1021/acs.jctc.7b01109

APA

Bastys, T., Gapsys, V., Doncheva, N. T., Kaiser, R., De Groot, B. L., & Kalinina, O. V. (2018). Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations. Journal of Chemical Theory and Computation, 14(7), 3397-3408. https://doi.org/10.1021/acs.jctc.7b01109

Vancouver

Bastys T, Gapsys V, Doncheva NT, Kaiser R, De Groot BL, Kalinina OV. Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations. Journal of Chemical Theory and Computation. 2018 Jul 10;14(7):3397-3408. https://doi.org/10.1021/acs.jctc.7b01109

Author

Bastys, Tomas ; Gapsys, Vytautas ; Doncheva, Nadezhda T. ; Kaiser, Rolf ; De Groot, Bert L. ; Kalinina, Olga V. / Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations. In: Journal of Chemical Theory and Computation. 2018 ; Vol. 14, No. 7. pp. 3397-3408.

Bibtex

@article{f43293bd93154e6aa652d81e9ed0e7c3,
title = "Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations",
abstract = "Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy ΔG, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease.",
author = "Tomas Bastys and Vytautas Gapsys and Doncheva, {Nadezhda T.} and Rolf Kaiser and {De Groot}, {Bert L.} and Kalinina, {Olga V.}",
year = "2018",
month = jul,
day = "10",
doi = "10.1021/acs.jctc.7b01109",
language = "English",
volume = "14",
pages = "3397--3408",
journal = "Journal of Chemical Theory and Computation",
issn = "1549-9618",
publisher = "American Chemical Society",
number = "7",

}

RIS

TY - JOUR

T1 - Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations

AU - Bastys, Tomas

AU - Gapsys, Vytautas

AU - Doncheva, Nadezhda T.

AU - Kaiser, Rolf

AU - De Groot, Bert L.

AU - Kalinina, Olga V.

PY - 2018/7/10

Y1 - 2018/7/10

N2 - Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy ΔG, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease.

AB - Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy ΔG, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease.

U2 - 10.1021/acs.jctc.7b01109

DO - 10.1021/acs.jctc.7b01109

M3 - Journal article

C2 - 29847122

AN - SCOPUS:85047996801

VL - 14

SP - 3397

EP - 3408

JO - Journal of Chemical Theory and Computation

JF - Journal of Chemical Theory and Computation

SN - 1549-9618

IS - 7

ER -

ID: 225833255