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

ABSTRACT: 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/.

SUBMITTER: Kieslich CA

PROVIDER: S-EPMC4747591 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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

Kieslich Chris A CA Tamamis Phanourios P Guzman Yannis A YA Onel Melis M Floudas Christodoulos A CA

PloS one 20160209 2

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 p ...[more]

PMID: 26859389

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Project description:HIV-1 cell entry commonly uses, in addition to CD4, one of the chemokine receptors CCR5 or CXCR4 as coreceptor. Knowledge of coreceptor usage is critical for monitoring disease progression as well as for supporting therapy with the novel drug class of coreceptor antagonists. Predictive methods for inferring coreceptor usage based on the third hypervariable (V3) loop region of the viral gene coding for the envelope protein gp120 can provide us with these monitoring facilities while avoiding expensive phenotypic tests. All simple heuristics (such as the 11/25 rule) as well as statistical learning methods proposed to date predict coreceptor usage based on sequence features of the V3 loop exclusively. Here, we show, based on a recently resolved structure of gp120 with an untruncated V3 loop, that using structural information on the V3 loop in combination with sequence features of V3 variants improves prediction of coreceptor usage. In particular, we propose a distance-based descriptor of the spatial arrangement of physicochemical properties that increases discriminative performance. For a fixed specificity of 0.95, a sensitivity of 0.77 was achieved, improving further to 0.80 when combined with a sequence-based representation using amino acid indicators. This compares favorably with the sensitivities of 0.62 for the traditional 11/25 rule and 0.73 for a prediction based on sequence information as input to a support vector machine and constitutes a statistically significant improvement. A detailed analysis and interpretation of structural features important for classification shows the relevance of several specific hydrogen-bond donor sites and aliphatic side chains to coreceptor specificity towards CCR5 or CXCR4. Furthermore, an analysis of side chain orientation of the specificity-determining residues suggests a major role of one side of the V3 loop in the selection of the coreceptor. The proposed method constitutes the first approach to an improved prediction of coreceptor usage based on an original integration of structural bioinformatics methods with statistical learning.

Project description:BackgroundIn human immunodeficiency virus type 1 (HIV-1) infection, transmitted viruses generally use the CCR5 chemokine receptor as a coreceptor for host cell entry. In more than 50% of subtype B infections, a switch in coreceptor tropism from CCR5- to CXCR4-use occurs during disease progression. Phenotypic or genotypic approaches can be used to test for the presence of CXCR4-using viral variants in an individual's viral population that would result in resistance to treatment with CCR5-antagonists. While genotyping approaches for coreceptor-tropism prediction in subtype B are well established and verified, they are less so for subtype C.MethodsHere, using a dataset comprising V3 loop sequences from 349 CCR5-using and 56 CXCR4-using HIV-1 subtype C viruses we perform a comparative analysis of the predictive ability of 11 genotypic algorithms in their prediction of coreceptor tropism in subtype C. We calculate the sensitivity and specificity of each of the approaches as well as determining their overall accuracy. By separating the CXCR4-using viruses into CXCR4-exclusive (25 sequences) and dual-tropic (31 sequences) we evaluate the effect of the possible conflicting signal from dual-tropic viruses on the ability of a of the approaches to correctly predict coreceptor phenotype.ResultsWe determined that geno2pheno with a false positive rate of 5% is the best approach for predicting CXCR4-usage in subtype C sequences with an accuracy of 94% (89% sensitivity and 99% specificity). Contrary to what has been reported for subtype B, the optimal approaches for prediction of CXCR4-usage in sequence from viruses that use CXCR4 exclusively, also perform best at predicting CXCR4-use in dual-tropic viral variants.ConclusionsThe accuracy of genotyping approaches at correctly predicting the coreceptor usage of V3 sequences from subtype C viruses is very high. We suggest that genotyping approaches can be used to test for coreceptor tropism in HIV-1 group M subtype C with a high degree of confidence that they will identify CXCR4-usage in both CXCR4-exclusive and dual tropic variants.

Dataset Information

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

Publications

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

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