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Generation of Thermally Stable Affinity Pairs for Sensitive, Specific Immunoassays.
Corless, Elliot; Hao, Yining; Jia, Huan; Kongsuphol, Patthara; Tay, Dousabel M Y; Ng, Say Yong; Sikes, Hadley D.
Afiliação
  • Corless E; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Hao Y; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Jia H; Antimicrobial Resistance Interdisciplinary Research Group (AMR-IRG), Singapore-MIT Alliance in Research and Technology (SMART), Singapore, Singapore.
  • Kongsuphol P; Antimicrobial Resistance Interdisciplinary Research Group (AMR-IRG), Singapore-MIT Alliance in Research and Technology (SMART), Singapore, Singapore.
  • Tay DMY; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Ng SY; Antimicrobial Resistance Interdisciplinary Research Group (AMR-IRG), Singapore-MIT Alliance in Research and Technology (SMART), Singapore, Singapore.
  • Sikes HD; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. sikes@mit.edu.
Methods Mol Biol ; 2491: 417-469, 2022.
Article em En | MEDLINE | ID: mdl-35482202
ABSTRACT
Many point-of-care diagnostic tests rely on a pair of monoclonal antibodies that bind to two distinct epitopes of a molecule of interest. This protocol describes the identification and generation of such affinity pairs based on an easily produced small protein scaffold rcSso7d which can substitute monoclonal antibodies. These strong binding variants are identified from a large yeast display library. The approach described can be significantly faster than antibody generation and epitope binning, yielding affinity pairs synthesized in common bacterial protein synthesis strains, enabling the rapid generation of novel diagnostic tools.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Anticorpos Monoclonais Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Anticorpos Monoclonais Idioma: En Ano de publicação: 2022 Tipo de documento: Article