COVID-19, caused by a novel coronavirus, SARS-CoV-2 has emerged to be a global pandemic affecting over 33 million people worldwide by the end of September 2020 (https://covid19.who.int/). The pandemic is especially critical since no specific drugs or vaccines are available so far. The urgent need to find a treatment for the COVID-19 pandemic has led researchers worldwide to develop effective therapies in a short time. The best bet for the scientists is to either find an effective vaccine or to identify approved or investigational drugs (used for other medical conditions), that potentially could cure COVID-19, thus bypassing the need for long clinical trials.
In this work, we propose to identify potential therapeutic monoclonal antibodies, which have the capability of neutralizing SARS-CoV-2 using the concept of “antibody repurposing”. We will generate a dataset for SARS-CoV-2 neutralizing antibodies and screen the therapeutic monoclonal antibodies based on sequence and structural similarity. The identified therapeutic antibodies will be refined using the information on experimentally known and predicted epitopes as well as binding energies. We will further validate the computationally identified antibodies with experimental data available in the literature to choose the potential antibodies for repurposing.
We will also develop a comprehensive database, which contains sequences and structures of neutralizing antibodies to SARS-CoV-2 as well as therapeutic monoclonal antibodies and the corresponding epitope and paratope information. The database will include both experimental data extracted from the literature (clinical case studies, in vivo, ex vivo and in vitro experiments) and computationally generated data using bioinformatics resources. We opine that such a database would serve as a unique and expedient resource for the development of therapeutic interventions against SARS-CoV-2.