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 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 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 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 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 COMPUTATIONAL SCREENING AND MOLECULAR DOCKING OF LICHEN SECONDARY METABOLITES AGAINST SEVERE ACUTE RESPIRATORY SYNDROME-COV-2 MAIN PROTEASE AND SPIKE PROTEIN

2021 ◽  
pp. 100-104
Author(s):  
SENTHIL PRABHU S ◽  
SATHISHKUMAR R ◽  
KIRUTHIKA B
Keyword(s):  
Molecular Docking ◽  
Severe Acute Respiratory Syndrome ◽  
Study Finding ◽  
Spike Protein ◽  
Protein Targets ◽  
Lipinski’S Rule ◽  
Computational Screening ◽  
Main Protease ◽  
Lichen Compounds ◽  
Potential Inhibitors

Objective: At present, the coronavirus disease (COVID)-19 pandemic is increasing global health concerns. This coronavirus outbreak is caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Since, no specific antiviral for treatment against COVID-19, so identification of new therapeutics is an urgent need. The objective of this study is to the analysis of lichen compounds against main protease and spike protein targets of SARS-CoV-2 using in silico approach. Methods: A total of 108 lichen compounds were subjected to ADMET analysis and 14 compounds were selected based on the ADMET properties and Lipinski’s rule of five. Molecular docking was performed for screening of selected individual lichen metabolites against the main protease and spike proteins of SARS-CoV-2 by Schrodinger Glide module software. Results: Among the lead compounds, fallacinol showed the highest binding energy value of −11.83 kcal/mol against spike protein, 4-O-Demethylbarbatic acid exhibited the highest dock score of −11.67 kcal/mol against main protease. Conclusion: This study finding suggests that lichen substances may be potential inhibitors of SARS-CoV-2.

scholarly journals Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Son Tung Ngo ◽  
Ngoc Quynh Anh Pham ◽  
Ly Le ◽  
Duc-Hung Pham ◽  
Van Vu
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Drug Targets ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Main Protease ◽  
Energy Perturbation ◽  
Novel Coronavirus ◽  
Potential Inhibitors ◽  
Hiv 1

<p>The novel coronavirus (SARS-CoV-2) has infected over 850,000 people and caused more than 42000 deaths worldwide as of April 1<sup>st</sup>, 2020. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. In this work, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro; and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a databases of ~4600 natural compounds found in Vietnamese plants, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including 3 natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, <i>cannabisin </i>A and <i>isoacteoside</i>, and an HIV-1 PR inhibitor, <i>darunavir</i>, exhibit large binding free energy to SARS-CoV-2 Mpro, which is larger than that of <b>13b</b>, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals (vdW) interaction. We also found that Glu166 form H-bonds to all the inhibitors. Replacing Glu166 by an alanine residue leads to ~ 2.0 kcal/mol decreases in the affinity of <i>darunavir </i>to SARS-CoV-2 Mpro. Our results could contribute to the development of potentials drugs inhibiting SARS-CoV-2. </p>

scholarly journals Computational Estimation of Potential Inhibitors from the Known Drugs against the Main Protease of SARS-CoV-2

2021 ◽  
Author(s):  
Nguyen Minh Tam ◽  
Pham Minh Quan ◽  
Nguyen Xuan Ha ◽  
Pham Cam Nam ◽  
Huong Thi Thu Phung
Keyword(s):  
Molecular Docking ◽  
Severe Acute Respiratory Syndrome ◽  
Potential Application ◽  
Drug Database ◽  
Computational Estimation ◽  
Main Protease ◽  
Potential Inhibitors

The coronavirus disease (COVID-19) pandemic caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide recently, leading to a global social and economic disruption. Although the emergently approved vaccine programs against SARS-CoV-2 have been rolled out globally, the number of COVID-19 daily cases and deaths has remained significantly high. Here, we attempted to computationally screen for possible medications for COVID-19 via rapidly estimate the highly potential inhibitors from an FDA-approved drug database against the main protease (Mpro) of SARS-CoV-2. The approach combined molecular docking and fast pulling of ligand (FPL) simulations that were demonstrated to be accurate and suitable for quick prediction of SARS-CoV-2 Mpro inhibitors. The results suggested that twentyseven compounds were capable of strongly associating with SARS-CoV-2 Mpro. Among them, the seven top leads are daclatasvir, teniposide, etoposide, levoleucovorin, naldemedine, cabozantinib, and irinotecan. The potential application of these drugs in COVID-19 therapy has thus been discussed.

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