TY - JOUR
T1 - Coronavirus Immunotherapeutic Consortium Database
AU - Mahita, Jarjapu
AU - Ha, Brendan
AU - Gambiez, Anais
AU - Schendel, Sharon L.
AU - Li, Haoyang
AU - Hastie, Kathryn M.
AU - Dennison, S. Moses
AU - Li, Kan
AU - Kuzmina, Natalia
AU - Periasamy, Sivakumar
AU - Bukreyev, Alexander
AU - Munt, Jennifer E.
AU - Osei-Twum, Mary
AU - Atyeo, Caroline
AU - Overton, James A.
AU - Vita, Randi
AU - Guzman-Orozco, Hector
AU - Mendes, Marcus
AU - Kojima, Mari
AU - Halfmann, Peter J.
AU - Kawaoka, Yoshihiro
AU - Alter, Galit
AU - Gagnon, Luc
AU - Baric, Ralph S.
AU - Tomaras, Georgia D.
AU - Germann, Tim
AU - Bedinger, Daniel
AU - Greenbaum, Jason A.
AU - Saphire, Erica Ollmann
AU - Peters, Bjoern
N1 - Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press.
PY - 2023/2/10
Y1 - 2023/2/10
N2 - The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL https://covicdb.lji.org/
AB - The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL https://covicdb.lji.org/
UR - http://www.scopus.com/inward/record.url?scp=85147895649&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147895649&partnerID=8YFLogxK
U2 - 10.1093/database/baac112
DO - 10.1093/database/baac112
M3 - Article
C2 - 36763096
AN - SCOPUS:85147895649
SN - 1758-0463
VL - 2023
JO - Database : the journal of biological databases and curation
JF - Database : the journal of biological databases and curation
M1 - baac112
ER -