CoRSeqV3-C: a novel HIV-1 subtype C specific V3 sequence based coreceptor usage prediction algorithm

Kieran Cashin1, Lachlan R Gray, Martin R Jakobsen

  • 1Center for Virology, Burnet Institute, 85 Commercial Rd, Melbourne 3004VIC, Australia.

Retrovirology
|March 1, 2013
PubMed

Insights

A new algorithm, CoRSeqV3-C, accurately predicts HIV-1 subtype C coreceptor usage. This tool helps clinicians choose optimal treatments for HIV-1 subtype C infections.

Area of Science:

  • Virology
  • Immunology
  • Computational Biology

Background:

  • HIV-1 subtype C (C-HIV) is the predominant strain globally, increasingly found in developed nations.
  • Accurate determination of C-HIV coreceptor usage is vital for effective treatment selection, including CCR5 antagonist maraviroc (MVC).
  • In silico prediction algorithms offer a rapid and cost-effective method for assessing HIV-1 coreceptor tropism.

Purpose of the Study:

  • To elucidate the V3 sequence determinants of C-HIV coreceptor usage.
  • To develop and validate a novel, sensitive, and user-friendly C-HIV specific coreceptor usage prediction algorithm.

Main Methods:

  • Characterization of phenotypically-verified C-HIV gp120 V3 sequences from the Los Alamos HIV Database.
  • Comparative sequence analyses of R5 and CXCR4-using C-HIV V3 sequences.
  • Development and validation of the CoRSeqV3-C prediction algorithm.

Main Results:

  • CXCR4-using C-HIV V3 sequences exhibit greater amino acid variability, net charge, and length compared to R5 C-HIV V3 sequences.
  • Significant differences were observed in the GPGQ crown motif and glycosylation sites between CXCR4-using and R5 C-HIV strains.
  • The developed CoRSeqV3-C algorithm demonstrated superior sensitivity in predicting CXCR4 usage for C-HIV strains compared to existing algorithms.

Conclusions:

  • CoRSeqV3-C is a highly sensitive V3 sequence-based algorithm for predicting CXCR4 usage in C-HIV strains, maintaining specificity.
  • The algorithm is openly available for public use.
  • CoRSeqV3-C can aid clinicians in selecting appropriate treatments for C-HIV infections and support pathogenesis research.
Abstract

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