Evidence map›Paper›PMID 32430025›Full record

ArticleRetrovirology2020

Non-active site mutants of HIV-1 protease influence resistance and sensitisation towards protease inhibitors.

Tomas Bastys, Vytautas Gapsys, Hauke Walter, Eva Heger, Nadezhda T Doncheva, Rolf Kaiser, Bert L de Groot, Olga V Kalinina

Open access · goldAbstract read
In one paragraph

Article in Retrovirology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.3field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 25 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Tomas BastysDepartment for Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany.
Vytautas GapsysComputational Biomolecular Dynamics Group, Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.
Hauke WalterMedizinisches Labor Stendal, 39576, Stendal, Germany.
Eva HegerInstitute of Virology, University of Cologne, 50935, Cologne, Germany.
Nadezhda T DonchevaDepartment for Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany.
Rolf KaiserInstitute of Virology, University of Cologne, 50935, Cologne, Germany.
Bert L de GrootComputational Biomolecular Dynamics Group, Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany.
Olga V KalininaDepartment for Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, 66123, Saarbrücken, Germany. Olga.Kalinina@helmholtz-hips.de.ORCID 0000-0002-9445-477X
Max Planck Institute for Biophysical Chemistry · DEMax Planck Institute for Informatics · DEUniversity of Cologne · DELabor Pachmann · DEUniversity of Copenhagen · DK

Funding

H2020 European Research Council H2020- EINFRA-2015-1-675728H2020 European Research Council H2020-INFRAEDI-02-2018-823830
6 · The paper itself

Abstract

backgroundHIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease's active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts.

resultsUsing these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations' effect on [Formula: see text] values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively.

conclusionsWe demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured [Formula: see text] values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease's active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

Indexed as

MutationBinding SitesCatalytic DomainDrug Resistance, ViralHIV-1HIV ProteaseHIV Protease InhibitorsHumansHydrogen BondingInhibitory Concentration 50Molecular Dynamics SimulationHIV ProteaseHIV Protease Inhibitorsp16 protease, Human immunodeficiency virus 1Alchemical binding free energy change calculationDistant site mutationsHIV-1 protease inhibitorsHydrogen bond network perturbationResistance-associated mutations

Identifiers

PMID32430025
PMCPMC7236880
OpenAlexW3026635350

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.