8R16
Structure of compound 12 bound to SARS-CoV-2 main protease
Summary for 8R16
Entry DOI | 10.2210/pdb8r16/pdb |
Descriptor | 3C-like proteinase, 1-[6,7-bis(chloranyl)-3,4-dihydro-1H-isoquinolin-2-yl]-2-(5-methylpyridin-3-yl)ethanone, CHLORIDE ION, ... (7 entities in total) |
Functional Keywords | fragment, inhibitor, protease, hydrolase |
Biological source | Severe acute respiratory syndrome coronavirus 2 |
Total number of polymer chains | 2 |
Total formula weight | 68894.43 |
Authors | Mac Sweeney, A.,Hazemann, J. (deposition date: 2023-11-01, release date: 2024-02-07, Last modification date: 2024-07-03) |
Primary citation | Hazemann, J.,Kimmerlin, T.,Lange, R.,Sweeney, A.M.,Bourquin, G.,Ritz, D.,Czodrowski, P. Identification of SARS-CoV-2 Mpro inhibitors through deep reinforcement learning for de novo drug design and computational chemistry approaches. Rsc Med Chem, 15:2146-2159, 2024 Cited by PubMed Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of coronavirus disease (COVID-19) since its emergence in December 2019. As of January 2024, there has been over 774 million reported cases and 7 million deaths worldwide. While vaccination efforts have been successful in reducing the severity of the disease and decreasing the transmission rate, the development of effective therapeutics against SARS-CoV-2 remains a critical need. The main protease (Mpro) of SARS-CoV-2 is an essential enzyme required for viral replication and has been identified as a promising target for drug development. In this study, we report the identification of novel Mpro inhibitors, using a combination of deep reinforcement learning for drug design with 3D pharmacophore/shape-based alignment and privileged fragment match count scoring components followed by hit expansions and molecular docking approaches. Our experimentally validated results show that 3 novel series exhibit potent inhibitory activity against SARS-CoV-2 Mpro, with IC values ranging from 1.3 μM to 2.3 μM and a high degree of selectivity. These findings represent promising starting points for the development of new antiviral therapies against COVID-19. PubMed: 38911172DOI: 10.1039/d4md00106k PDB entries with the same primary citation |
Experimental method | X-RAY DIFFRACTION (1.3 Å) |
Structure validation
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