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Updated: May 13, 2026

Prediction of HIV-1 Coreceptor Usage (Tropism) by Sequence Analysis using a Genotypic Approach
Published on: December 1, 2011
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.
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.
Background:
The majority of HIV-1 subjects worldwide are infected with HIV-1 subtype C (C-HIV). Although C-HIV predominates in developing regions of the world such as Southern Africa and Central Asia, C-HIV is also spreading rapidly in countries with more developed economies and health care systems, whose populations are more likely to have access to wider treatment options, including the CCR5 antagonist maraviroc (MVC). The ability to reliably determine C-HIV coreceptor usage is therefore becoming increasingly more important. In silico V3 sequence based coreceptor usage prediction algorithms are a relatively rapid and cost effective method for determining HIV-1 coreceptor specificity. In this study, we elucidated the V3 sequence determinants of C-HIV coreceptor usage, and used this knowledge to develop and validate a novel, user friendly, and highly sensitive C-HIV specific coreceptor usage prediction algorithm.
Results:
We characterized every phenotypically-verified C-HIV gp120 V3 sequence available in the Los Alamos HIV Database. Sequence analyses revealed that compared to R5 C-HIV V3 sequences, CXCR4-using C-HIV V3 sequences have significantly greater amino acid variability, increased net charge, increased amino acid length, increased frequency of insertions and substitutions within the GPGQ crown motif, and reduced frequency of glycosylation sites. Based on these findings, we developed a novel C-HIV specific coreceptor usage prediction algorithm (CoRSeqV3-C), which we show has superior sensitivity for determining CXCR4 usage by C-HIV strains compared to all other available algorithms and prediction rules, including Geno2pheno[coreceptor] and WebPSSMSINSI-C, which has been designed specifically for C-HIV.
Conclusions:
CoRSeqV3-C is now openly available for public use at http://www.burnet.edu.au/coreceptor. Our results show that CoRSeqV3-C is the most sensitive V3 sequence based algorithm presently available for predicting CXCR4 usage of C-HIV strains, without compromising specificity. CoRSeqV3-C may be potentially useful for assisting clinicians to decide the best treatment options for patients with C-HIV infection, and will be helpful for basic studies of C-HIV pathogenesis.
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