Abstract
Drug repositioning represents a cost- and time-efficient strategy for drug development. Here, we present a workflow of in silico screening of ACE2 enzymatic activators to treat COVID-19-induced metabolic complications. By using structure-based virtual screening and signature-based off-target effect identification via the Connectivity Map database, we provide a ranked list of the repositioning candidates as potential ACE2 enzymatic activators to ameliorate COVID-19-induced metabolic complications. The workflow can also be applied to other diseases with ACE2 as a potential target. For complete details on the use and execution of this protocol, please refer to Li et al. (2022).
Keywords: Bioinformatics; High throughput ccreening; Immunology; Structural biology.
【저자키워드】 immunology, bioinformatics, Structural Biology., High throughput ccreening, 【초록키워드】 ACE2, protocol, structural biology, Virtual screening, drug, in silico, database, complications, candidate, treat, connectivity, Complete, Map, other disease, 【제목키워드】 ACE2, Complication, treat,