ArticleScientific reports2016
Genotypic Prediction of Co-receptor Tropism of HIV-1 Subtypes A and C.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- HIV-1 subtype C predicted co-receptor tropism in Africa: an individual sequence level meta-analysis.AIDS research and therapy · 2020Pooled it
- Co-receptor usage in distinct phylogenetic clusters of HIV-1 CRF01_AE is associated with differential immune reconstitution after antiretroviral therapy.Microbiology spectrum · 2026Article
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- Detection of HIV-1 Resistance Mutations to Antiretroviral Therapy and Cell Tropism in Russian Patients Using Next-Generation Sequencing.Pathogens (Basel, Switzerland) · 2026Article
- Single-cell delineation of strain-specific HIV-1 Vif activities using dual reporter sensor cells and live cell imaging.Journal of virology · 2025Article
- Prediction of the Co-receptor usage of the main worldwide HIV-1 subtypes, CRF, and CRF35-AD in Iranian patients via the five genotypic tools.Biochemistry and biophysics reports · 2025Article
- Article
- Consequences of HIV infection in the bone marrow niche.Frontiers in immunology · 2023Review
- AI-based multi-PRS models outperform classical single-PRS models.Frontiers in genetics · 2023Article
- Guideline for software life cycle in health informatics.iScience · 2022Review
- Article
- Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.Molecular diversity · 2021Article
- Article
- Editorial: Artificial Intelligence Bioinformatics: Development and Application of Tools for Omics and Inter-Omics Studies.Frontiers in genetics · 2020Article
- HIV-1 tropism prediction by the XGboost and HMM methods.Scientific reports · 2019Article
- Next generation sequencing reveals a high frequency of CXCR4 utilizing viruses in HIV-1 chronically infected drug experienced individuals in South Africa.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2018Article
- Molecular Epidemiology of HIV-1 Virus in Puerto Rico: Novel Cases of HIV-1 Subtype C, D, and CRF-24BG.AIDS research and human retroviruses · 2018Article
- Phenotypic co-receptor tropism and Maraviroc sensitivity in HIV-1 subtype C from East Africa.Scientific reports · 2018Article
- Improving fold resistance prediction of HIV-1 against protease and reverse transcriptase inhibitors using artificial neural networks.BMC bioinformatics · 2017Article
- Partial HIV C2V3 envelope sequence analysis reveals association of coreceptor tropism, envelope glycosylation and viral genotypic variability among Kenyan patients on HAART.Virology journal · 2017Article
Corrections and comments
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Authors and funding
9 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antiretroviral treatment of Human Immunodeficiency Virus type-1 (HIV-1) infections with CCR5-antagonists requires the co-receptor usage prediction of viral strains. Currently available tools are mostly designed based on subtype B strains and thus are in general not applicable to non-B subtypes. However, HIV-1 infections caused by subtype B only account for approximately 11% of infections worldwide. We evaluated the performance of several sequence-based algorithms for co-receptor usage prediction employed on subtype A V3 sequences including circulating recombinant forms (CRFs) and subtype C strains. We further analysed sequence profiles of gp120 regions of subtype A, B and C to explore functional relationships to entry phenotypes. Our analyses clearly demonstrate that state-of-the-art algorithms are not useful for predicting co-receptor tropism of subtype A and its CRFs. Sequence profile analysis of gp120 revealed molecular variability in subtype A viruses. Especially, the V2 loop region could be associated with co-receptor tropism, which might indicate a unique pattern that determines co-receptor tropism in subtype A strains compared to subtype B and C strains. Thus, our study demonstrates that there is a need for the development of novel algorithms facilitating tropism prediction of HIV-1 subtype A to improve effective antiretroviral treatment in patients.
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Registered trials
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.