Article
HIV-V3Augur: A Novel Machine Learning Model for Predicting HIV-1 Tropism in Sub-Subtype A6 and CRF63_02A6, Predominant Variants in Russia and Countries of the Former Soviet Union.
Viruses - 25 Jun 2026
Elfimov Kirill, Gotfrid Ludmila, Nokhova Alina, Gashnikova Mariya, Ekushov Vasiliy, Halikov Maksim, Osipova Irina, Baboshko Dmitriy, Murzin Andrey, Kondeikin Ivan, Kiryakina Arina, Totmenin Aleksey, Agaphonov Aleksandr, Gashnikova Natalya
Abstract excerpt
Determining HIV-1 tropism provides the prognosis of HIV infection and is required before prescribing maraviroc, an entry inhibitor that blocks the interaction between the viral gp120 and the CCR5 coreceptor. However, existing prediction algorithms have been developed primarily for the globally most prevalent subtypes (B, C, and CRF01_AE) and often show reduced performance for other HIV-1 genetic variants....
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