ArticlePLoS computational biology2018
Co-evolution networks of HIV/HCV are modular with direct association to structure and function.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 23 citations in OpenAlex.
- Targeted barcoding of variable antibody domains and individual transcriptomes of the human B-cell repertoire using Link-Seq.PNAS nexus · 2025Article
- Direct-acting antiviral resistance of Hepatitis C virus is promoted by epistasis.Nature communications · 2023Article
- HCV E1 influences the fitness landscape of E2 and may enhance escape from E2-specific antibodies.Virus evolution · 2023Article
- Evolutionary modeling reveals enhanced mutational flexibility of HCV subtype 1b compared with 1a.iScience · 2022Article
- Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions.Nature communications · 2021Article
- In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives.Advanced drug delivery reviews · 2021Review
- Asymptotics of eigenstructure of sample correlation matrices for high-dimensional spiked models.Statistica Sinica · 2021Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mutational correlation patterns found in population-level sequence data for the Human Immunodeficiency Virus (HIV) and the Hepatitis C Virus (HCV) have been demonstrated to be informative of viral fitness. Such patterns can be seen as footprints of the intrinsic functional constraints placed on viral evolution under diverse selective pressures. Here, considering multiple HIV and HCV proteins, we demonstrate that these mutational correlations encode a modular co-evolutionary structure that is tightly linked to the structural and functional properties of the respective proteins. Specifically, by introducing a robust statistical method based on sparse principal component analysis, we identify near-disjoint sets of collectively-correlated residues (sectors) having mostly a one-to-one association to largely distinct structural or functional domains. This suggests that the distinct phenotypic properties of HIV/HCV proteins often give rise to quasi-independent modes of evolution, with each mode involving a sparse and localized network of mutational interactions. Moreover, individual inferred sectors of HIV are shown to carry immunological significance, providing insight for guiding targeted vaccine strategies.
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