Contemporary HIV-1 consensus Env with AI-assisted redesigned hypervariable loops promote antibody binding

具有 AI 辅助重新设计的高变环的当代 HIV-1 共识 Env 可促进抗体结合

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作者:Hongjun Bai, Eric Lewitus, Yifan Li, Paul V Thomas, Michelle Zemil, Mélanie Merbah, Caroline E Peterson, Thujitha Thuraisamy, Phyllis A Rees, Agnes Hajduczki, Vincent Dussupt, Bonnie Slike, Letzibeth Mendez-Rivera, Annika Schmid, Erin Kavusak, Mekhala Rao, Gabriel Smith, Jessica Frey, Alicea Sims, L

Abstract

An effective HIV-1 vaccine must elicit broadly neutralizing antibodies (bnAbs) against highly diverse Envelope glycoproteins (Env). Since Env with the longest hypervariable (HV) loops is more resistant to the cognate bnAbs than Env with shorter HV loops, we redesigned hypervariable loops for updated Env consensus sequences of subtypes B and C and CRF01_AE. Using modeling with AlphaFold2, we reduced the length of V1, V2, and V5 HV loops while maintaining the integrity of the Env structure and glycan shield, and modified the V4 HV loop. Spacers are designed to limit strain-specific targeting. All updated Env are infectious as pseudoviruses. Preliminary structural characterization suggests that the modified HV loops have a limited impact on Env's conformation. Binding assays show improved binding to modified subtype B and CRF01_AE Env but not to subtype C Env. Neutralization assays show increases in sensitivity to bnAbs, although not always consistently across clades. Strikingly, the HV loop modification renders the resistant CRF01_AE Env sensitive to 10-1074 despite the absence of a glycan at N332.

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