Computational Screening of Molecules Approved in Phase-I Clinical Trials to Identify 3CL Protease Inhibitors to Treat COVID-19

Sahu, Kamlesh Kumar; Noskov, Sergei Y.; Tuszyński, Jack A.; Houghton, Michael; Tyrrell, D. Lorne

doi:10.20944/preprints202004.0015.v2

Cited by 2 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Currently, darunavir, lopinavir, and ritonavir are being used as a supportive medication against SARS-CoV-2 . Sahu et al performed molecular docking calculations to identify various protease inhibitors from a pool of 2827 molecules under clinical trials (Sahu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Peptide-like and small-molecule inhibitors against Covid-19

Pant

Singh

Ravichandiran

et al. 2020

Journal of Biomolecular Structure and Dynamics

269

225

View full text Add to dashboard Cite

Coronavirus disease strain (SARS-CoV-2) was discovered in 2019, and it is spreading very fast around the world causing the disease Covid-19. Currently, more than 1.6 million individuals are infected, and several thousand are dead across the globe because of Covid-19. Here, we utilized the in-silico approaches to identify possible protease inhibitors against SARS-CoV-2. Potential compounds were screened from the CHEMBL database, ZINC database, FDA approved drugs and molecules under clinical trials. Our study is based on 6Y2F and 6W63 co-crystallized structures available in the protein data bank (PDB). Seven hundred compounds from ZINC/CHEMBL databases and fourteen hundred compounds from drug-bank were selected based on positive interactions with the reported binding site. All the selected compounds were subjected to standard-precision (SP) and extra-precision (XP) mode of docking. Generated docked poses were carefully visualized for known interactions within the binding site. Molecular mechanics-generalized born surface area (MM-GBSA) calculations were performed to screen the best compounds based on docking scores and binding energy values. Molecular dynamics (MD) simulations were carried out on four selected compounds from the CHEMBL database to validate the stability and interactions. MD simulations were also performed on the PDB structure 6YF2F to understand the differences between screened molecules and co-crystallized ligand. We screened 300 potential compounds from various databases, and 66 potential compounds from FDA approved drugs. Cobicistat, ritonavir, lopinavir, and darunavir are in the top screened molecules from FDA approved drugs. The screened drugs and molecules may be helpful in fighting with SARS-CoV-2 after further studies. ARTICLE HISTORY

show abstract

Section: Introductionmentioning

confidence: 99%

Peptide-like and small-molecule inhibitors against Covid-19

Pant

Singh

Ravichandiran

et al. 2020

Journal of Biomolecular Structure and Dynamics

269

225

View full text Add to dashboard Cite

show abstract

“…Results have shown that some of the drug moieties have better stability and binding a nity towards SARS-CoV-2 RdRp. Sahu et al 2020, have worked by taking SARS-CoV-2 3CL pro as a drug target in COVID-19 [10]. In our earlier attempts we found out that penicillin's had the potential to bind to M pro consistently, while phenoxymethylpenicillin and carbenicillin had high potential to act as an anti-COVID-19 agent which can be used alongside with anti-viral agents [11].…”

Section: Introductionmentioning

confidence: 90%

Multi-Targeting Approach in Selection of Potential Molecule for COVID-19 Treatment

Velagacherla

Suresh

Mehta

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is now a pandemic which began in Wuhan province of China. Drug discovery teams around the globe are in a race to develop a medicine for its management. For a novel molecule to enter into the market it takes time and the ideal way is to exploit the already approved drugs and repurpose them to use therapeutically.Methods: In this work, we have attempted to screen selected molecules that have shown an affinity towards multiple protein targets of COVID-19 using Schrödinger suit. Molecules were selected from approved antiviral, anti-inflammatory or immunomodulatory classes. The viral proteins selected were angiotensin-converting enzyme 2 (ACE2), main protease (Mpro) and spike protein. Computational tools such as molecular docking, prime MM-GBSA, induced-fit docking (IFD) and molecular dynamics (MD) simulations were used to identify the most suitable molecule that forms a stable interaction with the selected viral proteins.Results: The ligand-binding stability for the viral proteins PDB-IDs 1ZV8 (spike protein), 5R82 (Mpro) and 6M1D (ACE2), was in the order of Nintedanib>Quercetin, Nintedanib>Darunavir, Nintedanib> Baricitinib respectively. The MM-GBSA, IFD, and MD simulation studies infer that the drug nintedanib has the highest binding stability among the shortlisted molecules towards the selected viral target proteins. Conclusion: Nintedanib, which is primarily used for idiopathic pulmonary fibrosis, can be considered for repurposing and used in the management of COVID-19.

show abstract

Computational Screening of Molecules Approved in Phase-I Clinical Trials to Identify 3CL Protease Inhibitors to Treat COVID-19

Cited by 2 publications

References 9 publications

Peptide-like and small-molecule inhibitors against Covid-19

Peptide-like and small-molecule inhibitors against Covid-19

Multi-Targeting Approach in Selection of Potential Molecule for COVID-19 Treatment

Contact Info

Product

Resources

About