JOURNAL ARTICLE

Evaluation of HIV-1 capsid genetic variability and lenacapavir (GS-6207) drug resistance-associated mutations according to viral clades among drug-naive individuals.

  • Published In: Journal of Antimicrobial Chemotherapy (JAC), 2023, v. 78, n. 1. P. 272 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nka, Alex Durand; Bouba, Yagai; Teto, Georges; Semengue, Ezéchiel Ngoufack Jagni; Takou, Désiré Komego; Ngueko, Aurelie Minelle Kengni; Fabeni, Lavinia; Carioti, Luca; Armenia, Daniele; Pabo, Willy; Dambaya, Béatrice; Sosso, Samuel Martin; Colizzi, Vittorio; Perno, Carlo-Federico; Ceccherini-Silberstein, Francesca; Santoro, Maria Mercedes; Fokam, Joseph; Ndjolo, Alexis 3 of 3

Abstract

This article focuses on the genetic variability of the HIV-1 capsid (CA) protein and the prevalence of lenacapavir (GS-6207) drug resistance-associated mutations (DRMs) among antiretroviral therapy (ART)-naive individuals across diverse HIV-1 clades. Analysis of 2,031 HIV-1 CA sequences revealed that 63% of amino acid positions were conserved, including key residues involved in binding cellular factors essential for viral replication, while lenacapavir binding sites were largely conserved except for position N183. The overall prevalence of lenacapavir DRMs was low (0.14%), with mutations M66I, Q67H, and T107N detected at very low frequencies in specific subtypes, supporting lenacapavir’s predicted effectiveness across HIV-1 clades. The study underscores the importance of conserved CA regions for monitoring emerging resistance mutations as lenacapavir advances in clinical use.

Additional Information

  • Source:Journal of Antimicrobial Chemotherapy (JAC). 2023/01, Vol. 78, Issue 1, p272
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:0305-7453
  • DOI:10.1093/jac/dkac388
  • Accession Number:160965872
  • Copyright Statement:Copyright of Journal of Antimicrobial Chemotherapy (JAC) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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