scholarly journals Molecular docking and dynamics simulations reveal the potential of anti-HCV drugs to inhibit COVID-19 main protease

2021 ◽  
Author(s):  
Ahmed Ali Al-Karmalawy ◽  
Radwan Alnajjar ◽  
Mohammed Dahab ◽  
Ahmed Metwaly ◽  
Ibrahim Eissa
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Binding Free Energy ◽  
Solvent Accessibility ◽  
Genetic Material ◽  
New Drugs ◽  
Dynamics Simulation ◽  
Main Protease ◽  
Natural Inhibitor ◽  
Dynamics Simulations

Background: Drug repurposing is the fastest effective method to provide treatment for coronavirus disease (COVID-19). Drugs that targeting a closely related virus with similar genetic material such as hepatitis C virus (HCV) and more specifically targeting a similar viral protease would be an excellent choice. Methods: In this study, we carried out a virtual screening for fifteen anti HCV drugs against COVID-19 main protease using computational molecular docking techniques. Moreover, Velpatasvir (4) and Sofosbuvir (13) drugs were further evaluated through molecular dynamics simulations followed by calculating the binding free energy using the molecular mechanics generalised born/solvent accessibility (MM-GBSA) approach. Results: The binding affinity descending order was N3 natural inhibitor (1), Velpatasvir (4), Sofosbuvir (13), Ombitasvir (3), Glecaprevir (2), Asunaprevir (8), Paritaprevir (10), Grazoprevir (11), Elbasvir (6), Ledipasvir (5), Daclatasvir (7), Pibrentasvir (9), Simeprevir (12), Dasabuvir (14), Taribavirin (16) and finally Ribavirin (15). Molecular dynamics simulation reveals that Sofosbuvir (13) has exciting properties and it was stable within the active site; it also showed good MM-GBSA compared to the natural inhibitor N3. Conclusion: Our results could be auspicious for fast repurposing of the examined drugs either alone or in combinations with each other for the treatment of the COVID-19. Furthermore, this work provides a clear spot on the structure-activity relationship (SAR) for targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease and helps the design and synthesis of new drugs in the future targeting it as well.

scholarly journals Identification of Potential Binders of the SARS-Cov-2 Spike Protein via Molecular Docking, Dynamics Simulation and Binding Free Energy Calculation

2020 ◽  
Author(s):  
Dr. Chirag N. Patel ◽  
Dr. Prasanth Kumar S. ◽  
Dr. Himanshu A. Pandya ◽  
Dr. Rakesh M. Rawal
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Energy Calculations ◽  
Dynamics Simulations

<p>The pandemic outbreak of COVID-19 virus (SARS-CoV-2) has become critical global health issue. The biophysical and structural evidence shows that SARS-CoV-2 spike protein possesses higher binding affinity towards angiotensin-converting enzyme 2 (ACE2) and hemagglutinin-acetylesterase (HE) glycoprotein receptor. Hence, it was selected as a target to generate the potential candidates for the inhibition of HE glycoprotein. The present study focuses on extensive computational approaches which contains molecular docking, ADMET prediction followed by molecular dynamics simulations and free energy calculations. Furthermore, virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin were interact with high affinity. The ADMET prediction revealed pharmacokinetics and drug-likeness properties of top-ranked compounds. Molecular dynamics simulations and binding free energy calculations affirmed that these five NPACT compounds were robust HE inhibitor.</p>

Molecular Modeling Approach to Investigate the Intercalation of Phthalates and Their Metabolites in DNA Macromolecules

2019 ◽  
Vol 16 (2) ◽  
pp. 373-380 ◽  
Author(s):  
Tatiane P. Rodrigues ◽  
Jorddy N. Cruz ◽  
Tiago S. Arouche ◽  
Tais S. S. Pereira ◽  
Wanessa A. Costa ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Docking ◽  
Molecular Modeling ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Van Der Waals ◽  
Genetic Material ◽  
Ligand Interaction ◽  
Dynamics Simulations

Recent studies have reported that phthalates are capable of causing mutations and other changes in the genetic material. This study aimed to investigate the molecular interactions between phthalate di(2-ethylhexyl) phthalate (DEHP) and its metabolites monobutyl phthalate (MBP) and monoethyl phthalate (MEP), interacting with DNA. The research was conducted using molecular modeling techniques such as molecular docking and molecular dynamics simulations. Molecular docking revealed that the DEHP, MBP, and MEP are able to establish hydrogen interactions with various nucleotide bases. Molecular dynamics simulations revealed that these molecules interacted with the DNA, and the binding free energy results demonstrated that the DNA-ligand interaction has favorable free energy. The values for free binding energy were as follows: DNA–DEHP, –21.66 kcal/mol; DNA–MBP, –17.29 kcal/mol; and DNA–MEP, –20.13 kcal/mol. For these three systems, the contributions of van der Waals, electrostatic, and nonpolar solvation energy were favorable for the interaction. The van der Waals interactions contributed the major energy to the intercalation of the binders.

scholarly journals Exploring the Potency of Nigella sativa Seed in Inhibiting SARS-CoV-2 Main Protease Using Molecular Docking and Molecular Dynamics Simulations

2021 ◽  
Vol 21 (5) ◽  
pp. 1252
Author(s):  
Ari Hardianto ◽  
Muhammad Yusuf ◽  
Ika Wiani Hidayat ◽  
Safri Ishmayana ◽  
Ukun Mochammad Syukur Soedjanaatmadja
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Global Economy ◽  
Nigella Sativa ◽  
Scientific Information ◽  
Dynamics Simulation ◽  
Lipinski’S Rule ◽  
Main Protease ◽  
Dynamics Simulations

Coronavirus disease (COVID-19) is a pandemic burdening the global economy. It is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Black cumin (Nigella sativa) seed may contain antivirals for the disease since it was reported to inhibit the human immunodeficiency virus (HIV) and hepatitis C virus (HCV). Main protease (Mpro) is a vital protein for viral replication and a promising target for COVID-19 drug development. Hence, in this study, we intended to uncover the potency of N. sativa seed as the natural source of inhibitors for SARS-CoV-2 Mpro. We collected secondary metabolites in N. sativa seed through a literature search and employed Lipinski’s rule of five as the initial filter. Subsequently, virtual screening campaigns using a molecular docking method were performed, with N3 inhibitor and leupeptin as reference ligands. The top hits were analyzed further using a molecular dynamics simulation approach. Molecular dynamics simulations showed that binding affinities of nigellamine A2 and A3 to Mpro are comparable to that of leupeptin, with median values of -43.9 and -36.2 kcal mol–1, respectively. Ultimately, this study provides scientific information regarding N. sativa seeds’ potency against COVID-19 and helps direct further wet experiments.

scholarly journals Identification of Potential Binders of the SARS-Cov-2 Spike Protein via Molecular Docking, Dynamics Simulation and Binding Free Energy Calculation

2020 ◽  
Author(s):  
Dr. Chirag N. Patel ◽  
Dr. Prasanth Kumar S. ◽  
Dr. Himanshu A. Pandya ◽  
Dr. Rakesh M. Rawal
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Energy Calculations ◽  
Dynamics Simulations

<p>The pandemic outbreak of COVID-19 virus (SARS-CoV-2) has become critical global health issue. The biophysical and structural evidence shows that SARS-CoV-2 spike protein possesses higher binding affinity towards angiotensin-converting enzyme 2 (ACE2) and hemagglutinin-acetylesterase (HE) glycoprotein receptor. Hence, it was selected as a target to generate the potential candidates for the inhibition of HE glycoprotein. The present study focuses on extensive computational approaches which contains molecular docking, ADMET prediction followed by molecular dynamics simulations and free energy calculations. Furthermore, virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin were interact with high affinity. The ADMET prediction revealed pharmacokinetics and drug-likeness properties of top-ranked compounds. Molecular dynamics simulations and binding free energy calculations affirmed that these five NPACT compounds were robust HE inhibitor.</p>

scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Simulation Analysis ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Multilinear Regression ◽  
Qsar Analysis ◽  
Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

Advancements in Docking and Molecular Dynamics Simulations Towards Ligand-receptor Interactions and Structure-function Relationships

2018 ◽  
Vol 18 (20) ◽  
pp. 1755-1768 ◽  
Author(s):  
Ahmad Abu Turab Naqvi ◽  
Taj Mohammad ◽  
Gulam Mustafa Hasan ◽  
Md. Imtaiyaz Hassan
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Computational Method ◽  
Dynamics Simulation ◽  
Ligand Molecule ◽  
Ligand Interaction ◽  
Modern Drug ◽  
Dynamics Simulations

Protein-ligand interaction is an imperative subject in structure-based drug design and protein function prediction process. Molecular docking is a computational method which predicts the binding of a ligand molecule to the particular receptor. It predicts the binding pose, strength and binding affinity of the molecules using various scoring functions. Molecular docking and molecular dynamics simulations are widely used in combination to predict the binding modes, binding affinities and stability of different protein-ligand systems. With advancements in algorithms and computational power, molecular dynamics simulation is now a fundamental tool to investigative bio-molecular assemblies at atomic level. These methods in association with experimental support have been of great value in modern drug discovery and development. Nowadays, it has become an increasingly significant method in drug discovery process. In this review, we focus on protein-ligand interactions using molecular docking, virtual screening and molecular dynamics simulations. Here, we cover an overview of the available methods for molecular docking and molecular dynamics simulations, and their advancement and applications in the area of modern drug discovery. The available docking software and their advancement including application examples of different approaches for drug discovery are also discussed. We have also introduced the physicochemical foundations of molecular docking and simulations, mainly from the perception of bio-molecular interactions.

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