Database : the journal of biological databases and curation · 2023
Coronavirus Immunotherapeutic Consortium Database.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Mahita Jarjapu, Ha Brendan, Gambiez Anais, Schendel Sharon L, Li Haoyang, Hastie Kathryn M, Dennison S Moses, Li Kan, Kuzmina Natalia, Periasamy Sivakumar, Bukreyev Alexander, Munt Jennifer E, Osei-Twum Mary, Atyeo Caroline, Overton James A, Vita Randi, Guzman-Orozco Hector, Mendes Marcus, Kojima Mari, Halfmann Peter J, Kawaoka Yoshihiro, Alter Galit, Gagnon Luc, Baric Ralph S, Tomaras Georgia D, Germann Tim, Bedinger Daniel, Greenbaum Jason A, Saphire Erica Ollmann, Peters Bjoern
Аннотация
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/.