Coronavirus disease 2019 (COVID-19) was an epidemic that effected human health caused by SARS-CoV-2 infection. All-trans retinoic acid (ATRA) has anti-inflammatory capability. In this article, we evaluated the effectiveness and revealed the molecular mechanism of ATRA for treating SARS-CoV-2 using deep learning, in vitro studies, multi-scale molecular modeling, and network pharmacology. The DeepDTA model suggested that ATRA would be effective against COVID-19. In vitro studies confirmed the antiviral activity of ATRA. Subsequently, multi-scale molecular modeling indicated that ATRA could binding to angiotensin converting enzyme 2 (ACE2), 3C-like protease (3CLpro), RNA dependent RNA polymerase (RdRp), helicase, and 3'-to-5' exonuclease by non-covalent interactions. Additionally, network pharmacology suggested that ATRA alleviated inflammatory response by regulating the IL-17 signaling pathway and binding with TNF, PTGS2, and MAPK1 directly. In summary, our findings provide the first evidence that ATRA suppresses the entry and replication of SARS-CoV-2, and regulates inflammatory response of host cells.
Keywords: ATRA; Deep learning; Molecular docking; Molecular dynamic simulation; Network pharmacology; SARS-CoV-2.
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