Perampanel for COVID-19

Deep learning-integrated lab-on-a-chip in designing oral [3.1.0] bi and [4.2.0] tricyclic interceptors inhibiting multiple SARS-CoV-2 protomers.

Abstract Coronaviruses constitute a significant threat to the human population. Severe acute respiratory syndrome coronavirus-2, SARS-CoV-2, is a highly pathogenic human coronavirus that has caused the coronavirus disease 2019 (COVID-19) pandemic. It has led to a global viral outbreak with an exceptional spread and a high death toll, highlighting the need for effective antiviral strategies. 3-Chymotrypsin-like protease (3CLpro), the main protease in SARS-CoV-2, plays an indispensable role in the SARS-CoV-2 viral life cycle by cleaving the viral polyprotein to produce 11 individual non-structural proteins necessary for viral replication. 3CLpro is one of two proteases that function to produce new viral particles. It is a highly conserved cysteine protease with identical structural folds in all known human coronaviruses. Inhibitors binding with high affinity to 3CLpro will prevent the cleavage of viral polyproteins, thus impeding viral replication. Multiple strategies have been implemented to screen for inhibitors against 3CLpro, including peptide-like and small molecule inhibitors that covalently and non-covalently bind the active site, respectively. In addition, allosteric sites of 3CLpro have been identified to screen for small molecules that could make non-competitive inhibitors of 3CLpro. In essence, this review serves as a comprehensive guide to understanding the structural intricacies and functional dynamics of 3CLpro, emphasizing key findings that elucidate its role as the main protease of SARS-CoV-2. Notably, the review is a critical resource in recognizing the advancements in identifying and developing 3CLpro inhibitors as effective antiviral strategies against COVID-19, some of which are already approved for clinical use in COVID-19 patients.

AbstractA consensus virtual screening protocol has been applied to ca. 2000 approved drugs to seek inhibitors of the main protease (Mpro) of SARS-CoV-2, the virus responsible for COVID-19. 42 drugs emerged as top candidates, and after visual analyses of the predicted structures of their complexes with Mpro, 17 were chosen for evaluation in a kinetic assay for Mpro inhibition. Remarkably 14 of the compounds at 100-μM concentration were found to reduce the enzymatic activity and 5 provided IC50 values below 40 μM: manidipine (4.8 μM), boceprevir (5.4 μM), lercanidipine (16.2 μM), bedaquiline (18.7 μM), and efonidipine (38.5 μM). Structural analyses reveal a common cloverleaf pattern for the binding of the active compounds to the P1, P1’, and P2 pockets of Mpro. Further study of the most active compounds in the context of COVID-19 therapy is warranted, while all of the active compounds may provide a foundation for lead optimization to deliver valuable chemotherapeutics to combat the pandemic.

AbstractThe pandemic of novel coronavirus disease 2019 (COVID-19) has rampaged the world, with more than 58.4 million confirmed cases and over 1.38 million deaths across the world by 23 November 2020. There is an urgent need to identify effective drugs and vaccines to fight against the virus. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to the family of coronaviruses consisting of four structural and 16 non-structural proteins (NSP). Three non-structural proteins, main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp), are believed to have a crucial role in replication of the virus. We applied computational ligand-receptor binding modeling and performed comprehensive virtual screening on FDA-approved drugs against these three SARS-CoV-2 proteins using AutoDock Vina, Glide, and rDock. Our computational studies identified six novel ligands as potential inhibitors against SARS-CoV-2, including antiemetics rolapitant and ondansetron for Mpro; labetalol and levomefolic acid for PLpro; and leucal and antifungal natamycin for RdRp. Molecular dynamics simulation confirmed the stability of the ligand-protein complexes. The results of our analysis with some other suggested drugs indicated that chloroquine and hydroxychloroquine had high binding energy (low inhibitory effect) with all three proteins—Mpro, PLpro, and RdRp. In summary, our computational molecular docking approach and virtual screening identified some promising candidate SARS-CoV-2 inhibitors that may be considered for further clinical studies.