Analysis of physicochemical and structural properties determining HIV-1 coreceptor usage

Area of Science:

• Computational biology
• Virology
• Drug discovery

Background:

• Monitoring HIV coreceptor usage is crucial for disease progression and CCR5-blocking drug efficacy.
• Phenotypic assays for HIV tropism are costly; computational methods offer an alternative.
• Predicting tropism relies on analyzing the V3 loop of the HIV gp120 protein.

Purpose of the Study:

• To develop a novel numerical descriptor for the V3 loop encoding physicochemical and structural properties.
• To enable structure-based prediction of HIV tropism and identify key V3 loop determinants for coreceptor usage.
• To assess the predictive performance of the new method on clinical data and predict therapy outcomes.

Main Methods:

• Developed a numerical descriptor for the V3 loop based on its physicochemical and structural properties.
• Applied the descriptor for structure-based HIV tropism prediction.
• Validated the method on clinical 'bulk' sequence data and Maraviroc therapy patient samples.

Main Results:

• The descriptor significantly improved HIV tropism prediction accuracy (3% AUC, 7% sensitivity at 95% specificity) compared to sequence-only methods.
• The method showed statistically significant improvements in AUC on clinical sequence data.
• The approach successfully predicted therapy outcomes in patients undergoing Maraviroc treatment.

Conclusions:

• The new V3 loop descriptor enables accurate, structure-based HIV tropism prediction.
• Identified crucial V3 loop regions and physicochemical properties important for coreceptor binding.
• The method provides a valuable tool for predicting HIV tropism and therapy response, available online.