scholarly journals Molecular Docking and Fragment-Based QSAR Modeling for In Silico Screening of Approved Drugs and Candidate Compounds Against COVID-19

2020 ◽  
Vol 8 (2) ◽  
pp. 83-88
Author(s):  
Saeid Afshar ◽  
Asrin Bahmani ◽  
Massoud Saidijam
Keyword(s):  
Molecular Docking ◽  
Autodock Vina ◽  
Qsar Modeling ◽  
Health Crisis ◽  
Mortality And Morbidity ◽  
Main Protease ◽  
Docking Calculations ◽  
Approved Drugs ◽  
Top 40 ◽  
Potential Inhibitors

Background: Coronavirus disease 2019 (COVID-19) as a serious global health crisis leads to high mortality and morbidity. However, currently, there are no effective vaccines and treatments for COVID-19. Main protease (Mpro) and angiotensin-converting enzyme 2 (ACE2) are the best therapeutic targets of COVID-19. Objectives: The main purpose of this study is to investigate the most appropriate drug and candidate compound for proper interaction with Mpro and ACE2 to inhibit the activity of COVID-19. Methods: In this study, repurposing of approved drugs and screening of candidate compounds using molecular docking and fragment-based QSAR method were performed to discover the potential inhibitors of Mpro and ACE2. QSAR and docking calculations were performed based on the prediction of the inhibitory activities of 5-hydroxy indanone derivatives. Based on the results, an optimal structure was proposed to inhibit the activity of COVID-19. Results: Among 2629 DrugBank approved drugs, 118 were selected considering the LibDock score and absolute energy for possible drug-Mpro interactions. Furthermore, the top 40 drugs were selected based on screening the results for possible drug- Mpro interactions with AutoDock Vina. Conclusion: Finally, evaluation of the top 40 selected drugs for possible drug-ACE2 interactions with AutoDock Vina indicated that deslanoside (DB01078) can interact effectively with both Mpro and ACE2. However, prior to conducting clinical trials, further experimental validation is needed.

scholarly journals Rapid Prediction of Possible Inhibitors for SARS-CoV-2 Main Protease using Docking and FPL Simulations

2020 ◽  
Author(s):  
Pham Minh Quan ◽  
Khanh B. Vu ◽  
T. Ngoc Han Pham ◽  
Le Thi Thuy Huong ◽  
Linh Hoang Tran ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Global Health ◽  
Effective Treatment ◽  
Correlation Coefficients ◽  
Autodock Vina ◽  
Main Protease ◽  
Rapid Prediction ◽  
Global Health Issue ◽  
Potential Inhibitors ◽  
First Time

Appearance for the first time from Wuhan, China, the SARS-CoV-2 rapidly outbreaks worldwide and causes a serious global health issue. The effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this work, we have tried to rapidly predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations adopted good consistent results with the respective experiment with correlation coefficients of R_Dock=0.72 ± 0.14 and R_W = -0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors, which were selected from a ZINC15 sub-database, for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. The obtained results probably lead to enhance COVID-19 therapy.

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 Molecular Docking and Virtual Screening based prediction of drugs for COVID-19

2020 ◽  
Vol 23 ◽  
Author(s):  
Sekhar Talluri
Keyword(s):  
Clinical Trials ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Genomic Sequence ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
X Ray Diffraction ◽  
Main Protease ◽  
Docking Calculations ◽  
Approved Drugs

Aims: To predict potential drugs for COVID-19 by using molecular docking for virtual screening of drugs approved for other clinical applications. <p> Background: SARS-CoV-2 is the betacoronavirus responsible for the COVID-19 pandemic. It was listed as a potential global health threat by WHO due to high mortality, high basic reproduction number and lack of clinically approved drugs and vaccines for COVID-19. The genomic sequence of the virus responsible for COVID-19, as well as the experimentally determined three dimensional structure of the Main protease are available. <p> </p> Objective: To identify potential drugs that can be repurposed for treatment of COVID-19 by using molecular docking based virtual screening of all approved drugs. <p> </p> Methods: List of drugs approved for clinical use was obtained from SuperDRUG2 database. The structure of the target in the apo form, as well as structures of several target-ligand complexes, were obtained from RCSB PDB. The structure of SARS-CoV-2 Mpro determined from X-ray diffraction data was used as the target. Data regarding drugs in clinical trials for COVID-19 was obtained from clinicaltrials.org. Input for molecular docking based virtual screening was prepared by using Obabel and customized python, bash and awk scripts. Molecular docking calculations were carried out with Vina and SMINA, and the docked conformations were analyzed and visualized with PLIP, Pymol and Rasmol. <p> </p> Results: Among the drugs that are being tested in clinical trials for COVID-19, Danoprevir and Darunavir have the highest binding affinity for the target main protease of SARS-CoV-2. Saquinavir and Beclabuvir were identified as the best novel candidates for COVID-19 therapy by using Virtual Screening of drugs approved for other clinical indications. <p> </p> Conclusion: Protease inhibitors approved for treatment of other viral diseases have the potential to be repurposed for treatment of COVID-19. </p>

scholarly journals Rapid Prediction of Possible Inhibitors for SARS-CoV-2 Main Protease using Docking and FPL Simulations

2020 ◽  
Author(s):  
Son Tung Ngo ◽  
Khanh B. Vu ◽  
T. Ngoc Han Pham ◽  
Le Thi Thuy Huong ◽  
Pham Minh Quan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Global Health ◽  
Effective Treatment ◽  
Correlation Coefficients ◽  
Autodock Vina ◽  
Main Protease ◽  
Rapid Prediction ◽  
Global Health Issue ◽  
Potential Inhibitors ◽  
First Time

Appearance for the first time from Wuhan, China, the SARS-CoV-2 rapidly outbreaks worldwide and causes a serious global health issue. The effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this work, we have tried to rapidly predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations adopted good consistent results with the respective experiment with correlation coefficients of R_Dock=0.72 ± 0.14 and R_W = -0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors, which were selected from a ZINC15 sub-database, for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. The obtained results probably lead to enhance COVID-19 therapy.

scholarly journals Rapid Prediction of Possible Inhibitors for SARS-CoV-2 Main Protease using Docking and FPL Simulations

2020 ◽  
Author(s):  
Pham Minh Quan ◽  
Khanh B. Vu ◽  
T. Ngoc Han Pham ◽  
Le Thi Thuy Huong ◽  
Linh Hoang Tran ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Global Health ◽  
Effective Treatment ◽  
Correlation Coefficients ◽  
Autodock Vina ◽  
Main Protease ◽  
Rapid Prediction ◽  
Global Health Issue ◽  
Potential Inhibitors ◽  
First Time

Appearance for the first time from Wuhan, China, the SARS-CoV-2 rapidly outbreaks worldwide and causes a serious global health issue. The effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this work, we have tried to rapidly predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations adopted good consistent results with the respective experiment with correlation coefficients of R_Dock=0.72 ± 0.14 and R_W = -0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors, which were selected from a ZINC15 sub-database, for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. The obtained results probably lead to enhance COVID-19 therapy.

scholarly journals Novel 1,2,3‐Triazole Derivatives as Potential Inhibitors against Covid‐19 Main Protease: Synthesis, Characterization, Molecular Docking and DFT Studies

2021 ◽  
Vol 6 (14) ◽  
pp. 3468-3486
Author(s):  
Mohamed Reda Aouad ◽  
Daoud J. O. Khan ◽  
Musa A. Said ◽  
Nadia S. Al‐Kaff ◽  
Nadjet Rezki ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Dft Studies ◽  
Triazole Derivatives ◽  
Main Protease ◽  
Potential Inhibitors

scholarly journals Molecular Docking Senyawa Gingerol dan Zingiberol pada Tanaman Jahe sebagai Penanganan COVID-19

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Belinda D. P. M. Ratu ◽  
Widdhi Bodhi ◽  
Fona Budiarso ◽  
Billy J. Kepel ◽  
. Fatimawali ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Amino Acid Residues ◽  
Autodock Vina ◽  
Discovery Studio ◽  
Main Protease ◽  
Docking Method ◽  
Pubmed Database ◽  
Almost All ◽  
The Impact

Abstract: COVID-19 is a new disease. Many people feel the impact of this disease. There is no definite cure for COVID-19, so many people use traditional medicine to ward off COVID-19, including ginger. This study aims to determine whether there is an interaction between compounds in ginger (gingerol and zingiberol) and the COVID-19’s main protease (6LU7). This study uses a molecular docking method using 4 main applications, namely Autodock Tools, Autodock Vina, Biovia Discovery Studio 2020, and Open Babel GUI. The samples used were gingerol and zingiberol compounds in ginger plants downloaded from Pubchem. The data used in this study used Mendeley, Clinical Key, and PubMed database. The study showed that almost all of the amino acid residues in the gingerol compound acted on the 6LU7 active site, whereas the zingiberol did not. The results of the binding affinity of ginger compounds, both gingerol and zingiberol, do not exceed the binding affinity of remdesivir, a drug that is widely researched as a COVID-19 handling drug. In conclusion, gingerol and zingiberol compounds in ginger can’t be considered as COVID-19’s treatment.Keywords: molecular docking, gingerol, zingiberol Abstrak: COVID-19 merupakan sebuah penyakit yang baru. Banyak masyarakat yang merasakan dampak dari penyakit ini. Belum ada pengobatan pasti untuk menyembuhkan COVID-19, sehingga banyak masyarakat yang menggunakan pengobatan tradisional untuk menangkal COVID-19, termasuk jahe. Penelitian ini bertujuan untuk mengetahui apakah ada interaksi antara senyawa pada jahe (gingerol dan zingiberol) dengan main protease COVID-19 (6LU7). Penelitian ini menggunakan metode molecular docking dengan menggunakan 4 aplikasi utama, yaitu Autodock Tools, Autodock Vina, Biovia Discovery Studio 2020, dan Open Babel GUI. Sampel yang digunakan yaitu senyawa gingerol dan zingiberol pada tanaman jahe yang diunduh di Pubchem. Data yang digunakan dalam penelitian ini menggunakan database Mendeley, Clinical Key, dan PubMed. Penelitian menunjukkan bahwa hampir semua residu asam amino pada senyawa gingerol bekerja pada sisi aktif 6LU7, sedangkan tidak demikian pada zingiberol. Hasil binding affinity senyawa jahe, baik gingerol maupun zingiberol tidak  melebihi binding affinity remdesivir, obat yang banyak diteliti sebagai obat penanganan COVID-19. Sebagai simpulan, senyawa gingerol dan zingiberol pada tanaman jahe tidak dapat dipertimbangkan sebagai penanganan COVID-19Kata Kunci: molecular docking, gingerol, zingiberol

scholarly journals Quinoline and Quinazoline Alkaloids against COVID-19: An In Silico Multitarget Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Esraa M. O. A. Ismail ◽  
Shaza W. Shantier ◽  
Mona S. Mohammed ◽  
Hassan H. Musa ◽  
Wadah Osman ◽  
...  
Keyword(s):  
Antimalarial Activity ◽  
The Novel ◽  
Socioeconomic Impacts ◽  
Health Crisis ◽  
Natural Sources ◽  
Angiotensin Converting Enzyme 2 ◽  
Main Protease ◽  
Recent Outbreak ◽  
Novel Coronavirus ◽  
Potential Inhibitors

The recent outbreak of the highly contagious coronavirus disease 2019 (COVID-19) caused by the novel coronavirus SARS-CoV-2 has created a global health crisis with socioeconomic impacts. Although, recently, vaccines have been approved for the prevention of COVID-19, there is still an urgent need for the discovery of more efficacious and safer drugs especially from natural sources. In this study, a number of quinoline and quinazoline alkaloids with antiviral and/or antimalarial activity were virtually screened against three potential targets for the development of drugs against COVID-19. Among seventy-one tested compounds, twenty-three were selected for molecular docking based on their pharmacokinetic and toxicity profiles. The results identified a number of potential inhibitors. Three of them, namely, norquinadoline A, deoxytryptoquivaline, and deoxynortryptoquivaline, showed strong binding to the three targets, SARS-CoV-2 main protease, spike glycoprotein, and human angiotensin-converting enzyme 2. These alkaloids therefore have promise for being further investigated as possible multitarget drugs against COVID-19.

scholarly journals MOLECULAR DOCKING STUDIES ON SCREENING AND ASSESSMENT OF SELECTED BIOFLAVONOIDS AS POTENTIAL INHIBITORS OF COVID-19 MAIN PROTEASE

2020 ◽  
pp. 174-178
Author(s):  
SHAILENDRA SANJAY SURYAWANSHI ◽  
POOJA BHAVAKANA JAYANNACHE ◽  
RAJKUMAR SANJAY PATIL ◽  
PALLED MS ◽  
ALEGAON SG
Keyword(s):  
Molecular Docking ◽  
Treatment Options ◽  
Docking Studies ◽  
Binding Energies ◽  
Molecular Docking Studies ◽  
Discovery Studio ◽  
Main Protease ◽  
Potential Inhibitors ◽  
Binding Energy Calculations ◽  
Native Ligand

Objectives: The objective of the study was to screen and assess the selected bioactive bioflavonoids in medicinal plants as potential coronaviruses (CoV) main protease (Mpro) inhibitors using molecular docking studies. Methods: We have investigated several bioflavonoids which include apigenin, galangin, glycitein, luteolin, morin, naringin, resveratrol, and rutin. Nelfinavir and lopinavir were used as standard antiviral drugs for comparison. Mpro was docked with selected compounds using PyRx 0.8 and docking was analyzed by PyRx 0.8 and Biovia Discovery Studio 2019. Results: The binding energies obtained from the docking of 6LU7 with native ligand, nelfinavir, lopinavir, apigenin, galangin, glycitein, luteolin, morin, naringin, resveratrol, and rutin were found to be −7.4, −8.3, −8.0, −7.8, −7.3, −7, −7.4, −7.6, −7.8, −6.9, and −9 kcal/mol, respectively. Conclusion: From the binding energy calculations, we can conclude that nelfinavir and lopinavir may represent potential treatment options and apigenin, galangin, glycitein, luteolin, morin, naringin, resveratrol, and rutin found to possess the best inhibitors of CoV disease-19 main protease.

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.

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