ABSTRACT
COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a new recently emerged sarbecovirus. This virus uses the human ACE2 enzyme as receptor for cell entry, recognizing it with the receptor binding domain (RBD) of the S1 subunit of the viral spike protein. We present the use of phage display to select anti-SARS-CoV-2 spike antibodies from the human naïve antibody gene libraries HAL9/10 and subsequent identification of 309 unique fully human antibodies against S1. 17 antibodies are binding to the RBD, showing inhibition of spike binding to cells expressing ACE2 as scFv-Fc and neutralize active SARS-CoV-2 virus infection of VeroE6 cells. The antibody STE73-2E9 is showing neutralization of active SARS-CoV-2 as IgG and is binding to the ACE2-RBD interface. Thus, universal libraries from healthy human donors offer the advantage that antibodies can be generated quickly and independent from the availability of material from recovering patients in a pandemic situation.
Subject(s)
Angiotensin-Converting Enzyme 2/immunology , Antibodies, Neutralizing/genetics , Antibodies, Viral/genetics , COVID-19/immunology , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/immunology , Angiotensin-Converting Enzyme 2/chemistry , Animals , Antibodies, Neutralizing/isolation & purification , Antibodies, Viral/isolation & purification , Antibody Affinity , COVID-19/epidemiology , Cell Line , Chlorocebus aethiops , Gene Library , Healthy Volunteers , Host Microbial Interactions/immunology , Humans , Immunoglobulin G/genetics , Immunoglobulin G/isolation & purification , Models, Molecular , Mutation , Neutralization Tests , Pandemics , Peptide Library , Protein Interaction Domains and Motifs , Recombinant Proteins/genetics , Recombinant Proteins/immunology , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/chemistry , Vero CellsABSTRACT
The kinetics of featured interactions (KOFFI) database is a novel tool and resource for binding kinetics data from biomolecular interactions. While binding kinetics data are abundant in literature, finding valuable information is a laborious task. We used text extraction methods to store binding rates (association, dissociation) as well as corresponding meta-information (e.g. methods, devices) in a novel database. To date, over 270 articles were manually curated and binding data on over 1705 interactions was collected and stored in the (KOFFI) database. Moreover, the KOFFI database application programming interface was implemented in Anabel (open-source software for the analysis of binding interactions), enabling users to directly compare their own binding data analyses with related experiments described in the database.
