The world is facing a serious global pandemic of HIV/AIDS, with more than 35 million people infected. Controlling and eventually eradicating HIV will require an improved vaccine design strategy complete with a better tool set for epidemic surveillance.
An effective vaccine must induce immune responses that recognize as many HIV strains as possible and suppress viral escapes to protect against the rapidly-mutating virus. The surface morphology of peptide-MHC complexes is one of the key factors in controlling the scope of T cell responses. Our computational design for predicting the peptide-MHC complex surface morphology along with high resolution X-ray crystallography informs the identification of novel HIV vaccine candidates.
Once a functional HIV vaccine is implemented, the ability to accurately monitor HIV incidence --the number of newly infected people-- is crucial to evaluate the vaccine's efficacy. We are focusing on developing HIV genomic incidence assays utilizing signatures embedded in an individual’s HIV sequence population. Integrating high-throughput next-generation sequencing, bioinformatics pipeline, and statistical analysis permits us to quantify the amount of viral evolution as a fingerprint of infection duration.
An effective vaccine must induce immune responses that recognize as many HIV strains as possible and suppress viral escapes to protect against the rapidly-mutating virus. The surface morphology of peptide-MHC complexes is one of the key factors in controlling the scope of T cell responses. Our computational design for predicting the peptide-MHC complex surface morphology along with high resolution X-ray crystallography informs the identification of novel HIV vaccine candidates.
Once a functional HIV vaccine is implemented, the ability to accurately monitor HIV incidence --the number of newly infected people-- is crucial to evaluate the vaccine's efficacy. We are focusing on developing HIV genomic incidence assays utilizing signatures embedded in an individual’s HIV sequence population. Integrating high-throughput next-generation sequencing, bioinformatics pipeline, and statistical analysis permits us to quantify the amount of viral evolution as a fingerprint of infection duration.