scholarly journals Repurposing approved drugs as potential inhibitors of 3CL-protease of SARS-CoV-2: Virtual screening and structure based drug design

2020 ◽  
Vol 88 ◽  
pp. 107351 ◽  
Author(s):  
Franz-Josef Meyer-Almes
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Structure Based Drug Design ◽  
Approved Drugs ◽  
Potential Inhibitors ◽  
3Cl Protease

scholarly journals Identification of Potential Inhibitors of 3CL Protease of SARS-CoV-2 From ZINC Database by Molecular Docking-Based Virtual Screening

2020 ◽  
Vol 7 ◽  
Author(s):  
Ashraf Ahmed Ali Abdusalam ◽  
Vikneswaran Murugaiyah
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Binding Pocket ◽  
Effective Vaccine ◽  
Autodock Vina ◽  
Zinc Database ◽  
Docking Approach ◽  
Approved Drugs ◽  
Potential Inhibitors ◽  
3Cl Protease

The rapid outbreak of Coronavirus Disease 2019 (COVID-19) that was first identified in Wuhan, China is caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The 3CL protease (3CLpro) is the main protease of the SARS-CoV-2, which is responsible for the viral replication and therefore considered as an attractive drug target since to date there is no specific and effective vaccine available against this virus. In this paper, we reported molecular docking-based virtual screening (VS) of 2000 compounds obtained from the ZINC database and 10 FDA-approved (antiviral and anti-malaria) on 3CLpro using AutoDock Vina to find potential inhibitors. The screening results showed that the top four compounds, namely ZINC32960814, ZINC12006217, ZINC03231196, and ZINC33173588 exhibited high affinity at the 3CLpro binding pocket. Their free energy of binding (FEB) were −12.3, −11.9, −11.7, and −11.2 kcal/mol while AutoDock Vina scores were −12.61, −12.32, −12.01, and -11.92 kcal/mol, respectively. These results were better than the co-crystallized ligand N3, whereby its FEB was −7.5 kcal/mol and FDA-approved drugs. Different but stable interactions were obtained between the four identified compounds with the catalytic dyad residues of the 3CLpro. In conclusion, novel 3CLpro inhibitors from the ZINC database were successfully identified using VS and molecular docking approach, fulfilling the Lipinski rule of five, and having low FEB and functional molecular interactions with the target protein. The findings suggests that the identified compounds may serve as potential leads that act as COVID-19 3CLpro inhibitors, worthy for further evaluation and development.

scholarly journals Virtual Screening of Potential Inhibitors for SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Carlos Javier Alméciga-Díaz ◽  
Luisa N. Pimentel-Vera ◽  
Angela Caro ◽  
Angela Mosquera ◽  
Camilo Andrés Castellanos Moreno ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Clinical Information ◽  
Virus Genome ◽  
Pharmacological Agents ◽  
Main Protease ◽  
Novel Coronavirus ◽  
Approved Drugs ◽  
Potential Inhibitors

Coronavirus Disease 2019 (Covid-19) was first described in December 2019 in Wuhan, Hubei Province, China; and produced by a novel coronavirus designed as the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Covid-19 has become a pandemic reaching over 1.3 million confirmed cases and 73,000 deaths. Several efforts have been done to identify pharmacological agents that can be used to treat patients and protect healthcare professionals. The sequencing of the virus genome not only has offered the possibility to develop a vaccine, but also to identified and characterize the virus proteins. Among these proteins, main protease (Mpro) has been identified as a potential therapeutic target, since it is essential for the processing other viral proteins. Crystal structures of SARS-CoV-2 Mpro and inhibitors has been described during the last months. To describe additional compounds that can inhibit SARS-CoV-2 Mpro, in this study we performed a molecular docking-based virtual screening against a library of experimental and approved drugs. Top 10 hits included Pictilisib, Nimorazole, Ergoloid mesylates, Lumacaftor, Cefuroxime, Cepharanhine, and Nilotinib. These compounds were predicted to have higher binding affinity for SARS-CoV-2 Mpro than previously reported inhibitors for this protein, suggesting a higher potential to inhibit virus replication. Since the identified drugs have both pre-clinical and clinical information, we consider that these results may contribute to the identification of treatment alternative for Covid-19. Nevertheless, in vitro and in vivo confirmation should be performed before these compounds could be translated to the clinic.

scholarly journals COMPUTER AIDED DRUG DESIGN: AN OVERVIEW

2018 ◽  
Vol 8 (5) ◽  
pp. 504-509 ◽  
Author(s):  
Surabhi Surabhi ◽  
BK Singh
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Drug Design ◽  
Computer Aided Drug Design ◽  
Structure Based Drug Design ◽  
Drug Discovery And Development ◽  
Research Areas ◽  
Computer Aided ◽  
Pharmaceutical Industries

Discovery and development of a new drug is generally known as a very complex process which takes a lot of time and resources. So now a day’s computer aided drug design approaches are used very widely to increase the efficiency of the drug discovery and development course. Various approaches of CADD are evaluated as promising techniques according to their need, in between all these structure-based drug design and ligand-based drug design approaches are known as very efficient and powerful techniques in drug discovery and development. These both methods can be applied with molecular docking to virtual screening for lead identification and optimization. In the recent times computational tools are widely used in pharmaceutical industries and research areas to improve effectiveness and efficacy of drug discovery and development pipeline. In this article we give an overview of computational approaches, which is inventive process of finding novel leads and aid in the process of drug discovery and development research. Keywords: computer aided drug discovery, structure-based drug design, ligand-based drug design, virtual screening and molecular docking

scholarly journals Repurposing of FDA Approved Drugs for the Identification of Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Abhik Kumar Ray ◽  
Parth Sarthi Sen Gupta ◽  
Saroj Kumar Panda ◽  
Satyaranjan Biswal ◽  
Malay Kumar Rana
Keyword(s):  
Virtual Screening ◽  
Binding Energies ◽  
Great Promise ◽  
Main Protease ◽  
Promising Target ◽  
Inhibitory Potential ◽  
Novel Coronavirus ◽  
Approved Drugs ◽  
Potential Inhibitors ◽  
Fda Approved Drugs

<p>COVID-19, responsible for several deaths, demands a cumulative effort of scientists worldwide to curb the pandemic. The main protease, responsible for the cleavage of the polyprotein and formation of replication complex in virus, is considered as a promising target for the development of potential inhibitors to treat the novel coronavirus. The effectiveness of FDA approved drugs targeting the main protease in previous SARS-COV (s) reported earlier indicates the chances of success for the repurposing of FDA drugs against SARS-COV-2. Therefore, in this study, molecular docking and virtual screening of FDA approved drugs, primarily of three categories: antiviral, antimalarial, and peptide, are carried out to investigate their inhibitory potential against the main protease. Virtual screening has identified 53 FDA drugs on the basis of their binding energies (< -7.0 kcal/mol), out of which the top two drugs Velpatasvir (-9.1 kcal/mol) and Glecaprevir (-9.0 kcal/mol) seem to have great promise. These drugs have a stronger affinity to the SARS-CoV-2 main protease than the crystal bound inhibitor α-ketoamide 13B (-6.7 kcal/mol) or Indinavir (-7.5 kcal/mol) that has been proposed in a recent study as one of the best drugs for SARS-CoV-2. The <i>in-silico</i> efficacies of the screened drugs could be instructive for further biochemical and structural investigation for repurposing. The molecular dynamics studies on the shortlisted drugs are underway. </p>

scholarly journals Computational Molecular Docking and Virtual Screening Revealed Promising SARS-CoV-2 Drugs

2020 ◽  
Author(s):  
Maryam Hosseini ◽  
Wanqiu Chen ◽  
Charles Wang
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Virtual Screening ◽  
Clinical Studies ◽  
Inhibitory Effect ◽  
Docking Approach ◽  
Novel Coronavirus ◽  
Approved Drugs ◽  
Potential Inhibitors ◽  
Computational Molecular Docking

The pandemic of novel coronavirus disease 2019 (COVID-19) is rampaging the world with more than 1.4 million of confirmed cases and more than 85,000 of deaths across world by April 9th, 2020. There is an urgent need to identify effective drugs 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-structured proteins. Three non-structural proteins such as main protease, papain like protease, and RNA-dependent RNA polymerase are believed to play a crucial role in the virus replication. We applied a computational ligand-receptor binding modeling and performed a comprehensive virtual screening on the FDA-approved drugs against these three SARS-CoV-2 proteins using AutoDock Vina. Our computational studies indicated that Simeprevir, Ledipasvir, Idarubicin, Saquinavir, Ledipasivir, Partitaprevir, Glecaprevir, and Velpatasvir are all promising inhibitors, which displayed a lower binding energy (higher inhibitory effect) than Remdesivir, Lopinavir, and Ritonavir. However, we found that chloroquine and hydroxychloroquine, which showed efficacy in treating the COVID-19 in recent clinical studies, had high binding energy with all three proteins, suggesting they may work through a different mechanism. We also identified several novel drugs as potential inhibitors against SARS-CoV-2, including antiviral Raltegravir; antidiabetic Amaryl; antibiotics Retapamulin, Rifimixin, and Rifabutin; antiemetic Fosaprepitant and Netupitant. In summary, our computational molecular docking approach and virtual screening identified some promising candidate SARS-CoV-2 drugs that may be considered for further clinical studies.

Virtual Screening and Its Applications in Drug Discovery Process

2019 ◽  
pp. 101-126
Author(s):  
Gurusamy Mariappan ◽  
Anju Kumari
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Drug Design ◽  
Screening Tool ◽  
Log P ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Financial Loss ◽  
Structure Based Drug Design ◽  
Modern Drug

Virtual screening plays an important role in the modern drug discovery process. The pharma companies invest huge amounts of money and time in drug discovery and screening. However, at the final stage of clinical trials, several molecules fail, which results in a large financial loss. To overcome this, a virtual screening tool was developed with super predictive power. The virtual screening tool is not only restricted tool small molecules but also to macromolecules such as protein, enzyme, receptors, etc. This gives an insight into structure-based and Ligand-based drug design. VS gives reliable information to direct the process of drug discovery (e.g., when the 3D image of the receptor is known, structure-based drug design is recommended). The pharmacophore-based model is advisable when the information about the receptor or any macromolecule is unknown. In this ADME, parameters such as Log P, bioavailability, and QSAR can be used as filters. This chapter shows both models with various representative examples that facilitate the scientist to use computational screening tools in modern drug discovery processes.

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