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Title: De novo design and Rosetta‐based assessment of high‐affinity antibody variable regions (Fv) against the SARS‐CoV ‐2 spike receptor binding domain ( RBD )

The continued emergence of new SARS‐CoV‐2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high‐affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent‐exposed hACE2‐binding residues of the SARS‐CoV‐2 spike receptor binding domain (RBD) protein using the software toolOptMAVEn‐2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9‐mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade‐off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced byOptMAVEn‐2.0using a Rosetta‐based approach. We used RosettaSnugDockfor local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” withDeepAbto assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS‐CoV‐2 variants or other antigenic targets.

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Author(s) / Creator(s):
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Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Proteins: Structure, Function, and Bioinformatics
Page Range / eLocation ID:
p. 196-208
Medium: X
Sponsoring Org:
National Science Foundation
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