Tzou, P.L.; Tao, K.; Nouhin, J.; Rhee, S.-Y.; Hu, B.D.; Pai, S.; Parkin, N.; Shafer, R.W. Coronavirus Antiviral Research Database (CoV-RDB): An Online Database Designed to Facilitate Comparisons between Candidate Anti-Coronavirus Compounds. Viruses2020, 12, 1006.
Tzou, P.L.; Tao, K.; Nouhin, J.; Rhee, S.-Y.; Hu, B.D.; Pai, S.; Parkin, N.; Shafer, R.W. Coronavirus Antiviral Research Database (CoV-RDB): An Online Database Designed to Facilitate Comparisons between Candidate Anti-Coronavirus Compounds. Viruses 2020, 12, 1006.
Background: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy. Methods: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database. Results: As of July 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained >2,400 cell culture, entry assay and biochemical experiments, 240 animal model studies, and 56 clinical studies from >300 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for approximately 85% of the data. Approximately 75% of experiments involved compounds with a known or likely mechanism of action, including receptor binding inhibitors and monoclonal antibodies (20%); viral protease inhibitors (18%); polymerase inhibitors (9%); interferons (8%); fusion inhibitors (8%); host endosomal trafficking inhibitors (7%); and host protease inhibitors (5%). For 724 compounds with a known or likely mechanism, 95 (13%) are licensed in the US for other indications, 72 (10%) are licensed outside the US or are in human trials, and 557 (77%) are pre-clinical investigational compounds. Conclusion: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.
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