Background: COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Although there are a large number of candidate drug compounds that may be useful for treating COVID-19, the evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary. Method: In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE. Results: Numerous drugs were successfully screened, including many known antiviral drug compounds such as C646, chelerythrine chloride, canertinib, BX-795, sorafenib, sorafenib, QL-X-138, radicicol, A-443654, CGP-60474, alvocidib, mitoxantrone, QL-XII-47, geldanamycin, fluticasone, atorvastatin, quercetin, motexafin gadolinium, trovafloxacin, doxycycline, meloxicam, gentamicin, and dibromochloromethane. The screen also identified ivermectin, which was first identified as an anti-parasite drug and recently the drug was included in clinical trials for SARS-CoV-2. Conclusions: The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.
【초록키워드】 COVID-19, Ivermectin, SARS-CoV-2, coronavirus, clinical trial, pandemic, clinical trials, quercetin, drug, lung cancer, severe acute respiratory syndrome Coronavirus, antiviral drug, effective drugs, Screen, Community, doxycycline, atorvastatin, respiratory, expression, Critical, Gene expression profiles, sorafenib, gentamicin, chloride, mitoxantrone, canertinib, meloxicam, trovafloxacin, gadolinium, fluticasone, acute respiratory syndrome, motexafin gadolinium, alvocidib, acute respiratory syndrome coronavirus, acute respiratory syndrome coronavirus 2, dibromochloromethane, experimental validation, geldanamycin, radicicol, Compound, candidate, treating COVID-19, drug candidate, cell line, gene expression profile, effective, Tensor, selected, identify, affected, develop, significantly, applied, screened, costly, Numerous, time-consuming, effective drug, patients with COVID-19, 【제목키워드】 SARS-CoV-2, Drug discovery, in silico, Novel coronavirus, Tensor,