Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes

Karthik Shekhar, Claire F. Ruberman, Andrew L. Ferguson, John P. Barton, Mehran Kardar, Arup K. Chakraborty

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.

Original languageEnglish
Article number062705
JournalPhysical Review E
Volume88
Issue number6
DOIs
StatePublished - 4 Dec 2013
Externally publishedYes

Funding

FundersFunder number
NIH Office of the DirectorDP1OD001022

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