Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism

• Published in: PloS one Vol. 11; no. 2; p. e0148974
• Main Authors: Kieslich, Chris A, Tamamis, Phanourios, Guzman, Yannis A, Onel, Melis, Floudas, Christodoulos A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09.02.2016; Public Library of Science (PLoS)
• Subjects: Artificial intelligence; Bioinformatics; Biology and Life Sciences; Care and treatment; CCR5 protein; Chemical engineering; Chemokine receptors; Chemokines; Complications and side effects; Crushing; CXCR4 protein; Development and progression; Drug resistance; Energy Metabolism; Glycoprotein gp120; Glycoproteins; HIV; HIV Envelope Protein gp120 - physiology; HIV infections; HIV-1 - growth & development; HIV-1 - physiology; Human immunodeficiency virus; Humans; Medicine and Health Sciences; Models, Biological; Physical Sciences; Predictions; Protein Interaction Domains and Motifs - physiology; Proteins; Receptors, CCR5 - physiology; Receptors, CXCR4 - physiology; Research and Analysis Methods; Structure-Activity Relationship; Studies; Support vector machines; Tropism; Viruses; United States; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0148974

HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/.