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Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community
Introduction The spike (S) of SARS coronavirus 2 (SARS-CoV-2) engages angiotensin-converting enzyme 2 (ACE2) on a host cell to trigger viral-cell membrane fusion and infection. The extracellular region of ACE2 can be administered as a soluble decoy to compete for binding sites on the receptor-bindin...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Taylor & Francis
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594187/ https://www.ncbi.nlm.nih.gov/pubmed/33084449 http://dx.doi.org/10.1080/14789450.2020.1833721 |
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author | Procko, Erik |
author_facet | Procko, Erik |
author_sort | Procko, Erik |
collection | PubMed |
description | Introduction The spike (S) of SARS coronavirus 2 (SARS-CoV-2) engages angiotensin-converting enzyme 2 (ACE2) on a host cell to trigger viral-cell membrane fusion and infection. The extracellular region of ACE2 can be administered as a soluble decoy to compete for binding sites on the receptor-binding domain (RBD) of S, but it has only moderate affinity and efficacy. The RBD, which is targeted by neutralizing antibodies, may also change and adapt through mutation as SARS-CoV-2 becomes endemic, posing challenges for therapeutic and vaccine development. Areas Covered Deep mutagenesis is a Big Data approach to characterizing sequence variants. A deep mutational scan of ACE2 expressed on human cells identified mutations that increase S affinity and guided the engineering of a potent and broad soluble receptor decoy. A deep mutational scan of the RBD displayed on the surface of yeast has revealed residues tolerant of mutational changes that may act as a source for drug resistance and antigenic drift. Expert Opinion Deep mutagenesis requires a selection of diverse sequence variants; an in vitro evolution experiment that is tracked with next-generation sequencing. The choice of expression system, diversity of the variant library and selection strategy have important consequences for data quality and interpretation. |
format | Online Article Text |
id | pubmed-7594187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-75941872020-11-02 Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community Procko, Erik Expert Rev Proteomics Special Report Introduction The spike (S) of SARS coronavirus 2 (SARS-CoV-2) engages angiotensin-converting enzyme 2 (ACE2) on a host cell to trigger viral-cell membrane fusion and infection. The extracellular region of ACE2 can be administered as a soluble decoy to compete for binding sites on the receptor-binding domain (RBD) of S, but it has only moderate affinity and efficacy. The RBD, which is targeted by neutralizing antibodies, may also change and adapt through mutation as SARS-CoV-2 becomes endemic, posing challenges for therapeutic and vaccine development. Areas Covered Deep mutagenesis is a Big Data approach to characterizing sequence variants. A deep mutational scan of ACE2 expressed on human cells identified mutations that increase S affinity and guided the engineering of a potent and broad soluble receptor decoy. A deep mutational scan of the RBD displayed on the surface of yeast has revealed residues tolerant of mutational changes that may act as a source for drug resistance and antigenic drift. Expert Opinion Deep mutagenesis requires a selection of diverse sequence variants; an in vitro evolution experiment that is tracked with next-generation sequencing. The choice of expression system, diversity of the variant library and selection strategy have important consequences for data quality and interpretation. Taylor & Francis 2020-10-21 /pmc/articles/PMC7594187/ /pubmed/33084449 http://dx.doi.org/10.1080/14789450.2020.1833721 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
spellingShingle | Special Report Procko, Erik Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community |
title | Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community |
title_full | Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community |
title_fullStr | Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community |
title_full_unstemmed | Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community |
title_short | Deep mutagenesis in the study of COVID-19: a technical overview for the proteomics community |
title_sort | deep mutagenesis in the study of covid-19: a technical overview for the proteomics community |
topic | Special Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594187/ https://www.ncbi.nlm.nih.gov/pubmed/33084449 http://dx.doi.org/10.1080/14789450.2020.1833721 |
work_keys_str_mv | AT prockoerik deepmutagenesisinthestudyofcovid19atechnicaloverviewfortheproteomicscommunity |