Computational analysis of anti-HIV-1 antibody neutralization panel data to identify potential functional epitope residues

Abstract

Advances in single-cell antibody cloning methods have led to the identification of a variety of broadly neutralizing anti–HIV-1 antibodies. We developed a computational tool (Antibody Database) to help identify critical residues on the HIV-1 envelope protein whose natural variation affects antibody activity. Our simplifying assumption was that, for a given antibody, a significant portion of the dispersion of neutralization activity across a panel of HIV-1 strains is due to the amino acid identity or glycosylation state at a small number of specific sites, each acting independently. A model of an antibody's neutralization IC_(50) was developed in which each site contributes a term to the logarithm of the modeled IC_(50). The analysis program attempts to determine the set of rules that minimizes the sum of the residuals between observed and modeled IC_(50) values. The predictive quality of the identified rules may be assessed in part by whether there is support for rules within individual viral clades. As a test case, we analyzed antibody 8ANC195, an anti-glycoprotein gp120 antibody of unknown specificity. The model for this antibody indicated that several glycosylation sites were critical for neutralization. We evaluated this prediction by measuring neutralization potencies of 8ANC195 against HIV-1 in vitro and in an antibody therapy experiment in humanized mice. These experiments confirmed that 8ANC195 represents a distinct class of glycan-dependent anti–HIV-1 antibody and validated the utility of computational analysis of neutralization panel data.

Files

Additional details