Computational Design of Centralized HIV-1 Genes

The extreme genetic diversity of the HIV-1 remains as a daunting challenge for the development of an effective AIDS vaccine. One strategy for creating a single vaccine that protects against the HIV-1 expanding population is to reconstruct centralized immunogenic sequences that minimize the genetic distance to circulating strains that the vaccine is targeting. Such centralized genes can be estimated with inferred consensus, ancestral and center-of-tree sequences. Although the increased breadth of antibody and T-cell responses induced by the centralized vaccines to date are encouraging, they are modest and may only be partly effective in combating HIV-1. One of the reasons of this limited success might be that several features of HIV-1 molecular evolution have not been yet taken into account in the design of these centralized vaccines, the most important likely being its high recombination rate and complex nucleotide substitution process. Here we describe evolutionary methodologies for the inference of centralized HIV-1 genes, with particular focus on the sources of error introduced by recombination and the model of evolution, in order to foster the development of more effective immunogens before synthesis and assessment in the lab, and final testing in AIDS vaccine trials.