Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps

التفاصيل البيبلوغرافية
العنوان: Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps
المؤلفون: Soumya G, Remesh, Gregory E, Merz, Axel F, Brilot, Un Seng, Chio, Alexandrea N, Rizo, Thomas H, Pospiech, Irene, Lui, Mathew T, Laurie, Jeff, Glasgow, Chau Q, Le, Yun, Zhang, Devan, Diwanji, Evelyn, Hernandez, Jocelyne, Lopez, Komal Ishwar, Pawar, Sergei, Pourmal, Amber M, Smith, Fengbo, Zhou, Joseph, DeRisi, Tanja, Kortemme, Oren S, Rosenberg, Anum, Glasgow, Kevin K, Leung, James A, Wells, Kliment A, Verba
المصدر: bioRxiv
سنة النشر: 2022
مصطلحات موضوعية: Article
الوصف: SummaryThe SARS-CoV-2 Omicron variant, with 15 mutations in Spike receptor binding domain (Spike-RBD), renders virtually all clinical monoclonal antibodies against WT SARS-CoV-2 ineffective. We recently engineered the SARS-CoV-2 host entry receptor, ACE2, to tightly bind WT-Spike-RBD and prevent viral entry into host cells (“receptor traps”). Here we determine cryo-EM structures of our receptor traps in complex with full length Spike. We develop a multi-model pipeline combining Rosetta protein modeling software and cryo-EM to allow interface energy calculations even at limited resolution and identify interface side chains that allow for high affinity interactions between our ACE2 receptor traps and Spike-RBD. Our structural analysis provides a mechanistic rationale for the high affinity (0.53 - 4.2nM) binding of our ACE2 receptor traps to Omicron-RBD confirmed with biolayer interferometry measurements. Finally, we show that ACE2 receptor traps potently neutralize Omicron- and Delta-pseudotyped viruses, providing alternative therapeutic routes to combat this evolving virus.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1536ff3a69d8411a0c8b110ffb81d62
https://pubmed.ncbi.nlm.nih.gov/35982665
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....d1536ff3a69d8411a0c8b110ffb81d62
قاعدة البيانات: OpenAIRE