Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model.

• Type of Material: Article
• Authors: Bo R Beck, Deargen, Inc., Daejeon, Republic of Korea.; Bonggun Shin, Emory University; Yoonjung Choi, Deargen, Inc., Daejeon, Republic of Korea.; Sungsoo Park, Deargen, Inc., Daejeon, Republic of Korea.; Keunsoo Kang, Department of Microbiology, College of Science & Technology, Dankook University, Cheonan, Republic of Korea.
• Language: English
• Date: 2020
• Publisher: Elsevier Inc
• Publication Version: Final Published Version
• Copyright Statement: © 2020 The Authors
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.csbj.2020.03.025
• Title of Journal or Parent Work: Comput Struct Biotechnol J
• Volume: 18
• Start Page: 784
• End Page: 790
• Keywords: COVID-19; SARS-CoV-2; Coronavirus; MT-DTI; Deep learning; Atazanavir; Drug repurposing
• Research Categories: Computer Science; Biology, Microbiology

Abstract

The infection of a novel coronavirus found in Wuhan of China (SARS-CoV-2) is rapidly spreading, and the incidence rate is increasing worldwide. Due to the lack of effective treatment options for SARS-CoV-2, various strategies are being tested in China, including drug repurposing. In this study, we used our pre-trained deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI) to identify commercially available drugs that could act on viral proteins of SARS-CoV-2. The result showed that atazanavir, an antiretroviral medication used to treat and prevent the human immunodeficiency virus (HIV), is the best chemical compound, showing an inhibitory potency with Kd of 94.94 nM against the SARS-CoV-2 3C-like proteinase, followed by remdesivir (113.13 nM), efavirenz (199.17 nM), ritonavir (204.05 nM), and dolutegravir (336.91 nM). Interestingly, lopinavir, ritonavir, and darunavir are all designed to target viral proteinases. However, in our prediction, they may also bind to the replication complex components of SARS-CoV-2 with an inhibitory potency with Kd  < 1000 nM. In addition, we also found that several antiviral agents, such as Kaletra (lopinavir/ritonavir), could be used for the treatment of SARS-CoV-2. Overall, we suggest that the list of antiviral drugs identified by the MT-DTI model should be considered, when establishing effective treatment strategies for SARS-CoV-2.