<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Ramos KE</submitter><funding>HHS | NIH | National Institute of General Medical Sciences</funding><funding>NIAID NIH HHS</funding><funding>HHS | NIH | National Institute of Allergy and Infectious Diseases</funding><funding>HHS | NIH | National Institute of General Medical Sciences (NIGMS)</funding><funding>NIGMS NIH HHS</funding><funding>HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID)</funding><pagination>e2426438122</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12280912</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>122(28)</volume><pubmed_abstract>Single-domain antibodies, such as variable heavy domain of heavy chain (VHH) domains from camelids, are an attractive platform for therapeutic purposes. VHHs have a smaller size than traditional antibodies, which harbors certain advantages such as tissue penetration or accessing epitopes that may be shielded by protein domains. However, the smaller size of VHHs typically involves a smaller binding site, which can limit the scope of related antigens they are able to bind and, in the specific case of antiviral VHHs, render them susceptible to escape by a single point mutation. Here, we present a combined computational and experimental protein engineering approach to broaden the reactivity of SARS-CoV-1 receptorbinding domain (RBD)-specific VHH-72 for SARS-CoV-2 and Delta. Our strategy focuse</pubmed_abstract><journal>Proceedings of the National Academy of Sciences of the United States of America</journal><pubmed_title>Optimization of a sarbecovirus llama nanobody-antigen binding interface via a combined computational and phage display protein engineering approach.</pubmed_title><pmcid>PMC12280912</pmcid><funding_grant_id>T32-AI070117</funding_grant_id><funding_grant_id>R35 GM136357</funding_grant_id><funding_grant_id>AI141816</funding_grant_id><funding_grant_id>T32 AI070117</funding_grant_id><funding_grant_id>R01 AI141816</funding_grant_id><funding_grant_id>GM136357</funding_grant_id><pubmed_authors>Najafian A</pubmed_authors><pubmed_authors>Nandigrami P</pubmed_authors><pubmed_authors>Lai JR</pubmed_authors><pubmed_authors>Ramos KE</pubmed_authors><pubmed_authors>Fiser A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Optimization of a sarbecovirus llama nanobody-antigen binding interface via a combined computational and phage display protein engineering approach.</name><description>Single-domain antibodies, such as variable heavy domain of heavy chain (VHH) domains from camelids, are an attractive platform for therapeutic purposes. VHHs have a smaller size than traditional antibodies, which harbors certain advantages such as tissue penetration or accessing epitopes that may be shielded by protein domains. However, the smaller size of VHHs typically involves a smaller binding site, which can limit the scope of related antigens they are able to bind and, in the specific case of antiviral VHHs, render them susceptible to escape by a single point mutation. Here, we present a combined computational and experimental protein engineering approach to broaden the reactivity of SARS-CoV-1 receptorbinding domain (RBD)-specific VHH-72 for SARS-CoV-2 and Delta. Our strategy focuse</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Jul</publication><modification>2026-06-06T19:34:13.347Z</modification><creation>2026-06-04T03:10:49.413Z</creation></dates><accession>S-EPMC12280912</accession><cross_references><pubmed>40627384</pubmed><doi>10.1073/pnas.2426438122</doi></cross_references></HashMap>