Abstract
An optimal HIV vaccine should induce broadly neutralizing antibodies (bnAbs) that neutralize diverse viral strains and subtypes. However, potent bnAbs develop in only a small fraction of HIV-infected individuals, all contain rare features such as extensive mutation, insertions, deletions, and/or long complementarity-determining regions, and some are polyreactive, casting doubt on whether bnAbs to HIV can be reliably induced by vaccination. We engineered two potent VRC01-class bnAbs that minimized rare features. According to a quantitative features frequency analysis, the set of features for one of these minimally mutated bnAbs compared favorably with all 68 HIV bnAbs analyzed and was similar to antibodies elicited by common vaccines. This same minimally mutated bnAb lacked polyreactivity in four different assays. We then divided the minimal mutations into spatial clusters and dissected the epitope components interacting with those clusters, by mutational and crystallographic analyses coupled with neutralization assays. Finally, by synthesizing available data, we developed a working-concept boosting strategy to select the mutation clusters in a logical order following a germline-targeting prime. We have thus developed potent HIV bnAbs that may be more tractable vaccine goals compared to existing bnAbs, and we have proposed a strategy to elicit them. This reductionist approach to vaccine design, guided by antibody and antigen structure, could be applied to design candidate vaccines for other HIV bnAbs or protective Abs against other pathogens.
Highlights
Many antibodies capable of neutralizing a large fraction of circulating HIV isolates, broadly neutralizing antibodies, have been isolated from HIV-infected individuals [1,2,3,4,5,6,7,8,9,10,11,12]
The various features of bnAbs have not been weighed together on a single quantitative scale in order to measure the degree to which HIV bnAbs are unusual compared to other types of antibodies. Considering that such a scale would assist in ranking and prioritization of HIV bnAb epitopes as targets for vaccine design—with the idea that vaccine efforts should focus on the epitopes targeted by the most "normal" or least "unusual" potent bnAbs—here we developed a computational method, termed the Antibody Features Frequency (AFF) method, to estimate the "features frequency" of any antibody sequence
To test the AFF method, we compared the features frequencies for 388 "normal" memory antibodies induced by vaccines [51,52,53,54,55] or found in the human memory B cell repertoire [56] with the features frequencies for 300,000 antibody sequences computationally generated by the Monte Carlo method to be consistent with the frequency distributions of the individual features (S1 Fig)
Summary
Many antibodies capable of neutralizing a large fraction of circulating HIV isolates, broadly neutralizing antibodies (bnAbs), have been isolated from HIV-infected individuals [1,2,3,4,5,6,7,8,9,10,11,12]. Combinations of bnAbs targeting different epitopes are able to neutralize the great majority of HIV strains, even at low concentrations [4, 13] These bnAbs can provide sterilizing immunity against challenge by simian-human immunodeficiency virus (SHIV) in macaques [14, 15], and can reduce viral load to undetectable levels when administered to chronically infected animals [16, 17]. For these reasons, it is thought that an optimally protective vaccine will induce sustained titers of potent bnAbs targeting different epitopes. A bnAb-based HIV vaccine should induce bnAbs much more reliably—in a majority of vaccine recipients—and should achieve this feat using a small number of immunizations
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