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Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage.

ABSTRACT: BACKGROUND: HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-receptors, which interact primarily with the third hypervariable loop (V3 loop) of gp120. Determination of HIV-1 affinity for either the R5 or X4 co-receptor on host cells facilitates the inclusion of co-receptor antagonists as a part of patient treatment strategies. A dataset of 1193 distinct gp120 V3 loop peptide sequences (989 R5-utilizing, 204 X4-capable) is utilized to train predictive classifiers based on implementations of random forest, support vector machine, boosted decision tree, and neural network machine learning algorithms. An in silico mutagenesis procedure employing multibody statistical potentials, computational geometry, and threading of variant V3 sequences onto an experimental structure, is used to generate a feature vector representation for each variant whose components measure environmental perturbations at corresponding structural positions. RESULTS: Classifier performance is evaluated based on stratified 10-fold cross-validation, stratified dataset splits (2/3 training, 1/3 validation), and leave-one-out cross-validation. Best reported values of sensitivity (85%), specificity (100%), and precision (98%) for predicting X4-capable HIV-1 virus, overall accuracy (97%), Matthew's correlation coefficient (89%), balanced error rate (0.08), and ROC area (0.97) all reach critical thresholds, suggesting that the models outperform six other state-of-the-art methods and come closer to competing with phenotype assays. CONCLUSIONS: The trained classifiers provide instantaneous and reliable predictions regarding HIV-1 co-receptor usage, requiring only translated V3 loop genotypes as input. Furthermore, the novelty of these computational mutagenesis based predictor attributes distinguishes the models as orthogonal and complementary to previous methods that utilize sequence, structure, and/or evolutionary information. The classifiers are available online at http://proteins.gmu.edu/automute.

SUBMITTER: Masso M

PROVIDER: S-EPMC2976756 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage.

Masso Majid M Vaisman Iosif I II

BMC bioinformatics 20101005

<h4>Background</h4>HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-receptors, which interact primarily with the third hypervariable loop (V3 loop) of gp120. Determination of HIV-1 affinity for either the R5 or X4 co-receptor on host cells facilitates the inclusion of co-receptor antagonists as a part of patient treatment strategies. A dataset of 1193 distinct gp120 V3 loop peptide sequ ...[more]

PMID: 20923564

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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:BackgroundThe V3 loop of the glycoprotein gp120 of HIV-1 plays an important role in viral entry into cells by utilizing as coreceptor CCR5 or CXCR4, and is implicated in the phenotypic tropisms of HIV viruses. It has been hypothesized that the interaction between the V3 loop and CCR5 or CXCR4 is mediated by electrostatics. We have performed hierarchical clustering analysis of the spatial distributions of electrostatic potentials and charges of V3 loop structures containing consensus sequences of HIV-1 subtypes.ResultsAlthough the majority of consensus sequences have a net charge of +3, the spatial distribution of their electrostatic potentials and charges may be a discriminating factor for binding and infectivity. This is demonstrated by the formation of several small subclusters, within major clusters, which indicates common origin but distinct spatial details of electrostatic properties. Some of this information may be present, in a coarse manner, in clustering of sequences, but the spatial details are largely lost. We show the effect of ionic strength on clustering of electrostatic potentials, information that is not present in clustering of charges or sequences. We also make correlations between clustering of electrostatic potentials and net charge, coreceptor selectivity, global prevalence, and geographic distribution. Finally, we interpret coreceptor selectivity based on the N6X7T8|S8X9 sequence glycosylation motif, the specific positive charge location according to the 11/24/25 rule, and the overall charge and electrostatic potential distribution.ConclusionsWe propose that in addition to the sequence and the net charge of the V3 loop of each subtype, the spatial distributions of electrostatic potentials and charges may also be important factors for receptor recognition and binding and subsequent viral entry into cells. This implies that the overall electrostatic potential is responsible for long-range recognition of the V3 loop with coreceptors CCR5/CXCR4, whereas the charge distribution contributes to the specific short-range interactions responsible for the formation of the bound complex. We also propose a scheme for coreceptor selectivity based on the sequence glycosylation motif, the 11/24/25 rule, and net charge.

Project description:In clinical trials, HIV-1 broadly neutralizing antibodies (bnAbs) effectively lower plasma viremia and delay virus reemergence. The presence of less neutralization-susceptible strains prior to treatment decreases the efficacy of these antibody-based treatments, but neutralization sensitivity often cannot be predicted by sequence analysis alone. We found that phenotypically confirmed CXCR4-utilizing strains are less neutralization sensitive, especially to variable loop 3 (V3 loop)-directed bnAbs, than exclusively CCR5-utilizing strains in some, but not all, cases. Homology modeling suggested that the primary V3 loop bnAb epitope is equally accessible among CCR5- and CXCR4-using strains, although variants that exclusively use CXCR4 have V3 loop protrusions that interfere with CCR5 receptor interactions. Homology modeling also showed that among some, but not all, envelopes with decreased neutralization sensitivity, V1 loop orientation interfered with V3 loop-directed bnAb binding. Thus, there are likely different structural reasons for the coreceptor usage restriction and the different bnAb susceptibilities. Importantly, we show that individuals harboring envelopes with higher likelihood of using CXCR4 or greater predicted V1 loop interference have faster virus rebound and a lower maximum decrease in plasma viremia, respectively, after treatment with a V3 loop bnAb. Knowledge of receptor usage and homology models may be useful in developing future algorithms that predict treatment efficacy with V3 loop bnAbs.IMPORTANCE The efficacy of HIV-1 broadly neutralizing antibody (bnAb) therapies may be compromised by the preexistence of less susceptible variants. Sequence-based methods are needed to predict pretreatment variants' neutralization sensitivities. HIV-1 strains that exclusively use the CXCR4 receptor rather than the CCR5 receptor are less neutralization susceptible, especially to variable loop 3 (V3 loop) bnAbs in some, but not all, instances. While the inability to utilize the CCR5 receptor maps to a predicted protrusion in the envelope V3 loop, this viral determinant does not directly influence V3 loop bnAb sensitivity. Homology modeling predicts that contact between the envelope V1 loop and the antibody impacts V3 loop bnAb susceptibility in some cases. Among pretreatment envelopes, increased probability of using CXCR4 and greater predicted V1 interference are associated with faster virus rebound and a smaller decrease in the plasma virus level, respectively, after V3 loop bnAb treatment. Receptor usage information and homology models may be useful for predicting V3 loop bnAb therapy efficacy.

Dataset Information

Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage.

Publications

Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage.

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