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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
immunology and microbiology
Translating HIV Sequences into Quantitative Fitness Landscapes Predicts Viral Vulnerabilities for Rational Immunogen Design
Immunity, Volume 38, No. 3, Year 2013
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Description
A prophylactic or therapeutic vaccine offers the best hope to curb the HIV-AIDS epidemic gripping sub-Saharan Africa, but it remains elusive. A major challenge is the extreme viral sequence variability among strains. Systematic means to guide immunogen design for highly variable pathogens like HIV are not available. Using computational models, we have developed an approach to translate available viral sequence data into quantitative landscapes of viral fitness as a function of the amino acid sequences of its constituent proteins. Predictions emerging from our computationally defined landscapes for the proteins of HIV-1 clade B Gag were positively tested against new in vitro fitness measurements and were consistent with previously defined in vitro measurements and clinical observations. These landscapes chart the peaks and valleys of viral fitness as protein sequences change and inform the design of immunogens and therapies that can target regions of the virus most vulnerable to selection pressure. © 2013 Elsevier Inc.
Authors & Co-Authors
Ferguson, Andrew L.
United States, Cambridge
Massachusetts Institute of Technology
United States, Cambridge
Harvard University
United States, Urbana
University of Illinois Urbana-champaign
Mann, Jaclyn Kelly
South Africa, Durban
University of Kwazulu-natal
Omarjee, Saleha
South Africa, Durban
University of Kwazulu-natal
Ndung'u, Thumbi P.
United States, Cambridge
Harvard University
South Africa, Durban
University of Kwazulu-natal
Walker, Bruce D.
United States, Cambridge
Harvard University
United States, Chevy Chase
Howard Hughes Medical Institute
Chakraborty, Arup K.
United States, Cambridge
Massachusetts Institute of Technology
United States, Cambridge
Harvard University
Statistics
Citations: 217
Authors: 6
Affiliations: 5
Identifiers
Doi:
10.1016/j.immuni.2012.11.022
ISSN:
10747613
Research Areas
Infectious Diseases
Study Approach
Quantitative