抗体
领域(数学分析)
计算机科学
计算生物学
生物
免疫学
数学
数学分析
作者
Nathaniel R. Bennett,Joseph L. Watson,Robert J. Ragotte,Andrew J. Borst,DéJenaé L. See,Connor Weidle,Riti Biswas,Ellen Shrock,Philip J. Y. Leung,Buwei Huang,Inna Goreshnik,Russell Ault,Kenneth D. Carr,Benedikt Singer,Cameron Criswell,Dionne Vafeados,M. SANCHEZ,Ho Min Kim,Susana Vázquez Torres,Sidney Chan
标识
DOI:10.1101/2024.03.14.585103
摘要
Abstract Despite the central role that antibodies play in modern medicine, there is currently no method to design novel antibodies that bind a specific epitope entirely in silico . Instead, antibody discovery currently relies on animal immunization or random library screening approaches. Here, we demonstrate that combining computational protein design using a fine-tuned RFdiffusion network alongside yeast display screening enables the generation of antibody variable heavy chains (VHHs) and single chain variable fragments (scFvs) that bind user-specified epitopes with atomic-level precision. To verify this, we experimentally characterized VHH binders to four disease-relevant epitopes using multiple orthogonal biophysical methods, including cryo-EM, which confirmed the proper Ig fold and binding pose of designed VHHs targeting influenza hemagglutinin and Clostridium difficile toxin B (TcdB). For the influenza-targeting VHH, high-resolution structural data further confirmed the accuracy of CDR loop conformations. While initial computational designs exhibit modest affinity, affinity maturation using OrthoRep enables production of single-digit nanomolar binders that maintain the intended epitope selectivity. We further demonstrate the de novo design of single-chain variable fragments (scFvs), creating binders to TcdB and a Phox2b peptide-MHC complex by combining designed heavy and light chain CDRs. Cryo-EM structural data confirmed the proper Ig fold and binding pose for two distinct TcdB scFvs, with high-resolution data for one design additionally verifying the atomically accurate conformations of all six CDR loops. Our approach establishes a framework for the rational computational design, screening, isolation, and characterization of fully de novo antibodies with atomic-level precision in both structure and epitope targeting.
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