Antiviral activity of curcumin and its analogs selected by an artificial intelligence-supported activity prediction system in SARS-CoV-2-infected VeroE6 cells.

Curcumin has been reported to exert its anti-SARS-CoV-2 activity by inhibiting the binding of spike receptor-binding domain (RBD) to angiotensin-converting enzyme-2 (ACE2). To identify more potent compounds, we evaluated the antiviral activities of curcumin and its analogs in SARS-CoV-2-infected cells. An artificial intelligence-supported activity prediction system was used to select the compounds, and 116 of the 334 curcumin analogs were proposed to have spike RBD-ACE2 binding inhibitory activity. These compounds were narrowed down to eight compounds for confirmatory studies. Six out of the eight compounds showed antiviral activity with EC50 values of less than 30 µM and binding inhibitory activity with IC20 values of less than 30 µM. Structure-activity relationship analyses revealed that the double bonds in the carbon chain connecting the two phenolic groups were essential for both activities. X-ray co-crystallography studies are needed to clarify the true binding pose and design more potent derivatives.

Identification of SARS-CoV-2 main protease inhibitors from FDA-approved drugs by artificial intelligence-supported activity prediction system.

Although a certain level of efficacy and safety of several vaccine products against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have been established, unmet medical needs for orally active small molecule therapeutic drugs are still very high. As a key drug target molecule, SARS-CoV-2 main protease (Mpro) is focused and large number of in-silico screenings, a part of which were supported by artificial intelligence (AI), have been conducted to identify Mpro inhibitors both through drug repurposing and drug discovery approaches. In the many drug-repurposing studies, docking simulation-based technologies have been mainly employed and contributed to the identification of several Mpro binders. On the other hand, because AI-guided INTerprotein's Engine for New Drug Design (AI-guided INTENDD), an AI-supported activity prediction system for small molecules, enables to propose the potential binders by proprietary AI scores but not docking scores, it was expected to identify novel potential Mpro binders from FDA-approved drugs. As a result, we selected 20 potential Mpro binders using AI-guided INTENDD, of which 13 drugs showed Mpro-binding signal by surface plasmon resonance (SPR) method. Six (6) compounds among the 13 positive drugs were identified for the first time by the present study. Furthermore, it was verified that vorapaxar bound to Mpro with a Kd value of 27 µM by SPR method and inhibited virus replication in SARS-CoV-2 infected cells with an EC50 value of 11 µM.Communicated by Ramaswamy H. Sarma.