Egg-Curry: Insights into the Interaction Between Curcumin and Ovalbumin Using Spectroscopic Analyses and Protein-Ligand Docking Simulations

2021 ◽  
Author(s):  
Md. Abdur Razzak ◽  
Jiaoyang Li ◽  
Shin Sik Choi
Keyword(s):  
Ligand Docking ◽  
Docking Simulations ◽  
Spectroscopic Analyses

Improving protein–ligand binding prediction by considering the bridging water molecules in Autodock

2019 ◽  
Vol 18 (05) ◽  
pp. 1950027 ◽  
Author(s):  
Qiangna Lu ◽  
Lian-Wen Qi ◽  
Jinfeng Liu
Keyword(s):  
Ligand Binding ◽  
Considerable Improvement ◽  
Ligand Docking ◽  
Water Molecules ◽  
Binding Modes ◽  
Binding Prediction ◽  
Docking Simulations ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Docking Program

Water plays a significant role in determining the protein–ligand binding modes, especially when water molecules are involved in mediating protein–ligand interactions, and these important water molecules are receiving more and more attention in recent years. Considering the effects of water molecules has gradually become a routine process for accurate description of the protein–ligand interactions. As a free docking program, Autodock has been most widely used in predicting the protein–ligand binding modes. However, whether the inclusion of water molecules in Autodock would improve its docking performance has not been systematically investigated. Here, we incorporate important bridging water molecules into Autodock program, and systematically investigate the effectiveness of these water molecules in protein–ligand docking. This approach was evaluated using 18 structurally diverse protein–ligand complexes, in which several water molecules bridge the protein–ligand interactions. Different treatment of water molecules were tested by using the fixed and rotatable water molecules, and a considerable improvement in successful docking simulations was found when including these water molecules. This study illustrates the necessity of inclusion of water molecules in Autodock docking, and emphasizes the importance of a proper treatment of water molecules in protein–ligand binding predictions.

Protein-ligand Docking Simulations with AutoDock4 Focused on the Main Protease of SARS-CoV-2

2021 ◽  
Vol 28 ◽  
Author(s):  
Walter Filgueira de Azevedo Junior ◽  
Gabriela Bitencourt-Ferreira ◽  
Joana Retzke Godoy ◽  
Hilda Mayela Aran Adriano ◽  
Wallyson André dos Santos Bezerra ◽  
...  
Keyword(s):  
Scientific Evidence ◽  
Three Dimensional ◽  
Structural Data ◽  
Ligand Docking ◽  
Dimensional Structure ◽  
Computational Approaches ◽  
Docking Simulations ◽  
Protein Target ◽  
Main Protease ◽  
Docking Protocol

Background: The main protease of SARS-CoV-2 (Mpro) is one of the targets identified in SARS-CoV-2, the causative agent of COVID-19. The application of X-ray diffraction crystallography made available the three-dimensional structure of this protein target in complex with ligands, which paved the way for docking studies. Objective: Our goal here is to review recent efforts in the application of docking simulations to identify inhibitors of the Mpro using the program AutoDock4. Method: We searched PubMed to identify studies that applied AutoDock4 for docking against this protein target. We used the structures available for Mpro to analyze intermolecular interactions and reviewed the methods used to search for inhibitors. Results: The application of docking against the structures available for the Mpro found ligands with an estimated inhibition in the nanomolar range. Such computational approaches focused on the crystal structures revealed potential inhibitors of Mpro that might exhibit pharmacological activity against SARS-CoV-2. Nevertheless, most of these studies lack the proper validation of the docking protocol. Also, they all ignored the potential use of machine learning to predict affinity. Conclusion: The combination of structural data with computational approaches opened the possibility to accelerate the search for drugs to treat COVID-19. Several studies used AutoDock4 to search for inhibitors of Mpro. Most of them did not employ a validated docking protocol, which lends support to critics of their computational methodology. Furthermore, one of these studies reported the binding of chloroquine and hydroxychloroquine to Mpro. This study ignores the scientific evidence against the use of these antimalarial drugs to treat COVID-19.

Modeling loop backbone flexibility in receptor-ligand docking simulations

2012 ◽  
Vol 33 (31) ◽  
pp. 2504-2515 ◽  
Author(s):  
Johannes Flick ◽  
Frank Tristram ◽  
Wolfgang Wenzel
Keyword(s):  
Ligand Docking ◽  
Backbone Flexibility ◽  
Receptor Ligand ◽  
Docking Simulations

scholarly journals An Evaluation of the Potential of Heparin to Inhibit the Viral Entry of SARS-CoV-2

2021 ◽  
Keyword(s):  
Viral Entry ◽  
The Body ◽  
Ligand Docking ◽  
Binding Potential ◽  
Docking Simulations ◽  
Binding Domains ◽  
Wide Range ◽  
Novel Coronavirus ◽  
Viral Components ◽  
High Degree

Heparin is an anticoagulant medicine that prevents the formation of harmful blood clots in the vessels. Following the outbreak of the novel coronavirus disease 2019 (COVID-19), heparin has helped to improve the health of affected patients beyond its anticoagulant effects. The potential antiviral activity of heparin has attracted speculation due to its highly sulfated profile, which allows it to have a high binding affinity to a wide range of viral components. Heparin’s successful binding to the ZIKA virus, human immunodeficiency virus, as well as the SARS CoV and MERS CoV spike proteins have demonstrated its potential to inhibit the entry of SARS-CoV-2 into the body. A high degree of sequence homology also enables heparin to have inhibitory binding potential on viral components. The SARS-CoV-2 virus exhibits significant differences in its spike glycoprotein (SGP) sequence compared to other coronaviruses. The SGP sequence in SARS-CoV-2 contains additional potential glycosaminoglycan (GAG) binding domains that may drive differences in the attachment and entry process of the virus. Findings from unbiased computational ligand docking simulations, pseudotyped spike protein experiments, and cell to cell fusion assays have also opened possibilities to investigate the antiviral properties of heparin in clinical trials

scholarly journals Natural Compounds Activities against SARS-CoV-2 Mpro through Bioinformatics Approaches for Development of Antivirus Candidates

2021 ◽  
Vol 24 (5) ◽  
pp. 170-176
Author(s):  
Taufik Muhammad Fakih
Keyword(s):  
Binding Free Energy ◽  
Natural Compounds ◽  
Protein Docking ◽  
Ligand Docking ◽  
Angiotensin Converting Enzyme 2 ◽  
Docking Simulations ◽  
Main Protease ◽  
Alternative Approach ◽  
Therapeutic Mechanism ◽  
Almost All

Coronavirus infection (COVID-19) caused by SARS-CoV-2 appears as a pandemic that has spread to almost all countries in the world. Antiviral therapy using natural compounds is one alternative approach to overcome this infectious disease. The therapeutic mechanism is proven effective against the main protease (Mpro) of SARS-CoV-2. This research aims to perform bioinformatics studies, including ligand-docking simulations and protein-protein docking simulations, to identify, evaluate, and explore five compounds' activity on SARS-CoV-2 Mpro and their effects against Angiotensin-Converting Enzyme 2 (ACE-2). Protein-ligand docking simulations show kaempferol, flavonol, and their glycosides (Afzelin and Juglanin) and other flavonoids (Quercetin, Naringenin, and Genistein) have a high affinity towards SARS-CoV-2 Mpro. These results were then confirmed using protein-protein docking simulations to observe the ability of five compounds to prevent the attachment of ACE-2 to the active site. Based on the results of the bioinformatics studies, Quercetin has the best affinity, with a binding free energy value of −33.18 kJ/mol. The five compounds are predicted to be able to interact strongly with SARS-CoV-2. The results in this research are useful for further studies in the development of novel anti-infective drugs for COVID-19 that target SARS-CoV-2 Mpro.

Evaluation of Grey Wolf Optimization Algorithm on Rigid and Flexible Receptor Docking

2020 ◽  
Author(s):  
Kin Meng Wong ◽  
Shirley Siu
Keyword(s):  
Scoring Function ◽  
Ligand Docking ◽  
Receptor Protein ◽  
Pose Prediction ◽  
Grey Wolf ◽  
Success Rates ◽  
Autodock Vina ◽  
Grey Wolf Optimization ◽  
Structure Based Drug Design ◽  
Docking Program

Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein in current structure-based drug design. In this paper, we evaluate the performance of grey wolf optimization (GWO) in protein-ligand docking. Two versions of the GWO docking program – the original GWO and the modified one with random walk – were implemented based on AutoDock Vina. Our rigid docking experiments show that the GWO programs have enhanced exploration capability leading to significant speedup in the search while maintaining comparable binding pose prediction accuracy to AutoDock Vina. For flexible receptor docking, the GWO methods are competitive in pose ranking but lower in success rates than AutoDockFR. Successful redocking of all the flexible cases to their holo structures reveals that inaccurate scoring function and lack of proper treatment of backbone are the major causes of docking failures.

In Silico Approach to Inhibition of Tyrosinase by Ascorbic Acid Using Molecular Docking Simulations

2014 ◽  
Vol 14 (12) ◽  
pp. 1469-1472 ◽  
Author(s):  
F. Senol ◽  
M. Khan ◽  
Gurdal Orhan ◽  
Erdem Gurkas ◽  
Ilkay Orhan ◽  
...  
Keyword(s):  
Ascorbic Acid ◽  
Molecular Docking ◽  
In Silico ◽  
Docking Simulations

Synthesis of Coumarin Derivatives as Versatile Scaffolds for GSK-3β Enzyme Inhibition

2020 ◽  
Vol 20 (2) ◽  
pp. 153-160 ◽  
Author(s):  
Carla S. Francisco ◽  
Clara L. Javarini ◽  
Iatahanderson de S. Barcelos ◽  
Pedro A.B. Morais ◽  
Heberth de Paula ◽  
...  
Keyword(s):  
Kinase Inhibitors ◽  
Glycogen Synthase ◽  
Synthetic Methods ◽  
Kinase Assay ◽  
Crystallographic Structure ◽  
Coumarin Derivatives ◽  
Enzymatic Production ◽  
Docking Simulations ◽  
In Silico Studies ◽  
Gsk 3Β

Background: Glycogen synthase kinase-3 (GSK-3) is involved in the phosphorylation and inactivation of glycogen synthase. GSK-3 inhibitors have been associated with a variety of diseases, including Alzheimer´s disease (AD), diabetes type II, neurologic disorders, and cancer. The inhibition of GSK-3β isoforms is likely to represent an effective strategy against AD. Objective: The present work aimed to design and synthesize coumarin derivatives to explore their potential as GSK-3β kinase inhibitors. Method: The through different synthetic methods were used to prepare coumarin derivatives. The GSK-3β activity was measured through the ADP-Glo™ Kinase Assay, which quantifies the kinasedependent enzymatic production of ADP from ATP, using a coupled-luminescence-based reaction. A docking study was performed by using the crystallographic structure of the staurosporine/GSK-3β complex [Protein Data Bank (PDB) code: 1Q3D]. Results: The eleven coumarin derivatives were obtained and evaluated as potential GSK-3β inhibitors. Additionally, in silico studies were performed. The results revealed that the compounds 5c, 5d, and 6b inhibited GSK-3β enzymatic activity by 38.97–49.62% at 1 mM. The other coumarin derivatives were tested at 1 mM, 1 µM, and 1 nM concentrations and were shown to be inhibitor candidates, with significant IC50 (1.224–6.875 µM) values, except for compound 7c (IC50 = 10.809 µM). Docking simulations showed polar interactions between compound 5b and Lys85 and Ser203, clarifying the mechanism of the most potent activity. Conclusion: The coumarin derivatives 3a and 5b, developed in this study, showed remarkable activity as GSK-3β inhibitors.

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