scholarly journals Molecular docking studies of deacetylbisacodyl with intestinal sucrase-maltase enzyme

2017 ◽  
Vol 2 (12) ◽  
pp. 191 ◽  
Author(s):  
Ramchander Merugu ◽  
Uttam Kumar Neerudu ◽  
Karunakar Dasa ◽  
Kalpana V. Singh
Keyword(s):  
Hydrogen Bond ◽  
Molecular Docking ◽  
Electrostatic Interactions ◽  
Docking Studies ◽  
Amino Acid Residues ◽  
Interaction Study ◽  
Ligand Interaction ◽  
Docking Analysis ◽  
Protein Ligand Interaction ◽  
Intestinal Sucrase

Molecular docking of sucrase-isomaltase with ligand deacetylbisacodyl when subjected to docking analysis using docking server, predicted in-silico result with a free energy of -3.36 Kcal/mol which was agreed well with physiological range for protein-ligand interaction, making bisacodyl probable potent anti-isomaltase molecule. According to docking server Inhibition constant is 5.98Mm. which predicts that the ligand is going to inhibits enzyme and result in a clinically relevant drug interaction with a substrate for the enzyme. Hydrogen bond with bond length 3.45is formed between Pro 64 (A) of target and of ligand, which is again indicative of the docking between target and ligand. Excellent electrostatic interactions of polar, hydrophobic, pi-pi and Van der walls are observed. The proteinligand interaction study showed 6 amino acid residues interaction with the ligand.

Homology Modeling of Mus Musculus CDK5 and Molecular Docking Studies with Flavonoids

2017 ◽  
Vol 9 (6) ◽  
Author(s):  
Sowmya Suri ◽  
Rumana Waseem ◽  
Seshagiri Bandi ◽  
Sania Shaik
Keyword(s):  
Molecular Docking ◽  
3D Model ◽  
Structural Features ◽  
Docking Studies ◽  
Amino Acid Residues ◽  
Cyclin Dependent Kinase ◽  
Ligand Complex ◽  
Ligand Interaction ◽  
Molecular Docking Studies ◽  
Cyclin Dependent Kinase 5

A 3D model of Cyclin-dependent kinase 5 (CDK5) (Accession Number: Q543f6) is generated based on crystal structure of P. falciparum PFPK5-indirubin-5-sulphonate ligand complex (PDB ID: 1V0O) at 2.30 Å resolution was used as template. Protein-ligand interaction studies were performed with flavonoids to explore structural features and binding mechanism of flavonoids as CDK5 (Cyclin-dependent kinase 5) inhibitors. The modelled structure was selected on the basis of least modeler objective function. The model was validated by PROCHECK. The predicted 3D model is reliable with 93.0% of amino acid residues in core region of the Ramachandran plot. Molecular docking studies with flavonoids viz., Diosmetin, Eriodictyol, Fortuneletin, Apigenin, Ayanin, Baicalein, Chrysoeriol and Chrysosplenol-D with modelled protein indicate that Diosmetin is the best inhibitor containing docking score of -8.23 kcal/mol. Cys83, Lys89, Asp84. The compound Diosmetin shows interactions with Cys83, Lys89, and Asp84.

Spiro-acridine inhibiting tyrosinase enzyme: Kinetic, protein-ligand interaction and molecular docking studies

2019 ◽  
Vol 122 ◽  
pp. 289-297 ◽  
Author(s):  
Thaís Meira Menezes ◽  
Sinara Mônica Vitalino de Almeida ◽  
Ricardo Olímpio de Moura ◽  
Gustavo Seabra ◽  
Maria do Carmo Alves de Lima ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Docking Studies ◽  
Enzyme Kinetic ◽  
Ligand Interaction ◽  
Molecular Docking Studies ◽  
Protein Ligand Interaction ◽  
Tyrosinase Enzyme

Protein–ligand interaction study of signal transducer smoothened protein with different drugs: molecular docking and QM/MM calculations

RSC Advances ◽  
2015 ◽  
Vol 5 (84) ◽  
pp. 68829-68838 ◽  
Author(s):  
Hossein Farrokhpour ◽  
Vahid Pakatchian ◽  
Abdolreza Hajipour ◽  
Fatemeh Abyar ◽  
Alireza Najafi Chermahini ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Antitumor Agent ◽  
Signal Transducer ◽  
Interaction Study ◽  
Ligand Interaction ◽  
Protein Ligand Interaction

A part of signal transducer smoothened (SMO) protein including antitumor agent LY2940680. The site of this antitumor was considered for the docking of 716 ligands.

scholarly journals MOLECULAR DOCKING ANALYSIS OF NATRIURETIC PEPTIDE RECEPTOR-C TOWARDS THE DESIGN OF POTENTIAL ATRIAL FIBRILLATION INHIBITORS

2020 ◽  
Vol 9 (5) ◽  
pp. 2595-2600
Author(s):  
Shubhda Dev
Keyword(s):  
Atrial Fibrillation ◽  
Molecular Docking ◽  
Natriuretic Peptide ◽  
Antiarrhythmic Agents ◽  
Natriuretic Peptide Receptor ◽  
Ligand Interaction ◽  
Docking Analysis ◽  
Peptide Receptor ◽  
Protein Ligand Interaction ◽  
Molecular Docking Analysis

Atrial fibrillation (AF) stands the most widely recognized kind of clinical arrhythmia. Right now accessible anti-Atrial Fibrillation drugs are restricted by just moderate adequacy and an unfavorable safety profile. There is a perceived requirement for enhanced antiarrhythmic agents including activities that are specific for the fibrillating atrium. Therefore, it is of interest to design an appropriate medication for the disease Atrial Fibrillation using Molecular Docking techniques through protein-ligand interaction analysis. Hence, we document the Molecular docking analysis of natriuretic peptide receptor-C towards the design of potential Atrial Fibrillation inhibitors (Aprindine, Inclacumab, and Budiodarone) with the most favorable binding features for further consideration. This study centers around the process for drug discovery finding appropriate medication for the disease Atrial Fibrillation by Molecular Docking technique through protein-ligand interaction. The examination uncovered that out of a couple of molecules that were chosen as target, three of them were seen as most reasonable having the least energies compared to the other molecules. Aprindine, which is utilized in arrhythmia patients as a cardiac depressant. Inclacumab, which is an investigational sedate utilized in trials to look at the treatment and evasion of Myocardial Infarction, Peripheral Arterial Disease (PAD), and Coronary Heart Disease. Budiodarone, which is an antiarrhythmic drug at present in clinical preliminaries identified with amiodarone.

scholarly journals Herbal Compounds from Syzygium aromaticum and Cassia acutifolia as a Shield against SARS-CoV-2 Mpro: a Molecular Docking Approach

2021 ◽  
Vol 11 (6) ◽  
pp. 14853-14865
Keyword(s):  
Molecular Docking ◽  
Docking Studies ◽  
New Drugs ◽  
In Vivo Studies ◽  
Syzygium Aromaticum ◽  
Amino Acid Residues ◽  
Ligand Interaction ◽  
Docking Approach ◽  
Novel Coronavirus

Novel coronavirus (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) was first identified in China in December 2019. Currently, the novel coronavirus disease 2019 (COVID-19) is the most infectious disease worldwide. In the absence of a vaccine or drug, herbal compounds may be used to treat or control this disease. To explore novel potent inhibitors that suppress this virus's growth, we performed molecular docking studies on SARS-CoV-2 Mpro using 17 effective herbal compounds, along with three reference drugs. Docking results showed that crategolic acid from Syzygium aromaticum (clove) had the highest binding affinity with SARS-CoV-2 Mpro protease, followed by sennoside (A, B, C, and D) compounds from Cassia acutifolia (Sana Makki). Crategolic acid and sennoside (A, B, C, and D) contain amino acid residues and hydrogen bonds involved in the protein-ligand interaction. The present study confirms that crategolic acid and sennoside represent the strongest potential inhibitors of SARS-CoV-2 Mpro. This study's results may help in vivo studies validate the usefulness of compounds from clove and Sana Makki in preparing herbal medicine for the treatment of COVID-19. This analysis supports the production of new drugs for the treatment and control of COVID-19.

scholarly journals Molecular docking analysis of stevioside with AKT and PPARγ

2021 ◽  
Vol 17 (1) ◽  
pp. 283-288
Author(s):  
Abilasha Deenadayalan ◽  
Keyword(s):  
Hydrogen Bond ◽  
Molecular Docking ◽  
Docking Studies ◽  
Autodock Vina ◽  
Docking Analysis ◽  
Hydrogen Bond Interactions ◽  
Ppar Γ ◽  
Molecular Docking Analysis

Stevioside is a diterpenoid glycoside consisting of an aglycone (steviol) and three glucose molecules. It is commonly used as an anti-hyperglycemic food because of its non-caloric property. Therefore, it is of interest to document the interactions of stevioside with AKT & PPAR-γ proteins using Autodock Vina PyRx docking techniques. Results of the docking studies indicate that stevioside had more than two hydrogen bond interactions with the AKT and PPAR γ protein for further consideration.

Evaluation of Cytotoxic and Tyrosinase Inhibitory Activities of 2-phenoxy(thiomethyl) pyridotriazolopyrimidines: In Vitro and Molecular Docking Studies

2020 ◽  
Vol 20 (14) ◽  
pp. 1714-1721
Author(s):  
Hatem A. Abuelizz ◽  
El Hassane Anouar ◽  
Mohamed Marzouk ◽  
Mizaton H. Hasan ◽  
Siti R. Saleh ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Kojic Acid ◽  
Docking Studies ◽  
Breast Adenocarcinoma ◽  
Amino Acid Residues ◽  
New Class ◽  
Structure Activity ◽  
Tyrosinase Inhibitors ◽  
Mcf 7

Background: The use of tyrosinase has confirmed to be the best means of recognizing safe, effective, and potent tyrosinase inhibitors for whitening skin. Twenty-four 2-phenoxy(thiomethyl)pyridotriazolopyrimidines were synthesized and characterized in our previous studies. Objective: The present work aimed to evaluate their cytotoxicity against HepG2 (hepatocellular carcinoma), A549 (pulmonary adenocarcinoma), MCF-7 (breast adenocarcinoma) and WRL 68 (embryonic liver) cell lines. Methods: MTT assay was employed to investigate the cytotoxicity, and a tyrosinase inhibitor screening kit was used to evaluate the Tyrosinase (TYR) inhibitory activity of the targets. Results: The tested compounds exhibited no considerable cytotoxicity, and nine of them were selected for a tyrosinase inhibitory test. Compounds 2b, 2m, and 5a showed good inhibitory percentages against TYR compared to that of kojic acid (reference substance). Molecular docking was performed to rationalize the Structure-Activity Relationship (SAR) of the target pyridotriazolopyrimidines and analyze the binding between the docked-selected compounds and the amino acid residues in the active site of tyrosinase. Conclusion: The target pyridotriazolopyrimidines were identified as a new class of tyrosinase inhibitors.

Selection of oxypeucedanin as a potential antagonist from molecular docking analysis of HSP90

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Joshua Oluwasegun Bamidele ◽  
George Oche Ambrose ◽  
Oluwaseun Suleiman Alakanse
Keyword(s):  
Molecular Docking ◽  
Liver Toxicity ◽  
Docking Study ◽  
Docking Studies ◽  
Molecular Docking Study ◽  
Docking Analysis ◽  
Computational Docking ◽  
Drug Candidates ◽  
Expression Rate ◽  
Client Proteins

AbstractHSP90 is observed as one of the copious molecular chaperones that play a key role in mediating appropriate folding, maturation, and firmness of many client proteins in cells. The expression rate of HSP90 in cancer cells is at a level of 2- to 10-fold higher than the 1- to 2-fold of its unstressed and healthy ones. To combat this, several inhibitors to HSP90 protein have been studied (such as geldanamycin and its derivative 17-AAG and 17-DMAG) and have shown some primary side effects including plague, nausea, vomiting, and liver toxicity, hence the search for the best-in-class inhibitor for this protein through in silico. This study is aimed at analyzing the inhibitory potency of oxypeucedanin-a furocoumarin derivations, which have been reported to have antipoliferative activity in human prostrate carcinoma DN145 cells, and three other drug candidates retrieved from the literature via computational docking studies. The results showed oxypeucedanin as the compound with the highest binding energy of −9.2 kcal/mol. The molecular docking study was carried out using PyRx, Auto Dock Vina option, and the target was validated to confirm the proper target and the docking procedure employed for this study.

scholarly journals Binding Efficacy and Thermogenic Efficiency of Pungent and Nonpungent Analogs of Capsaicin

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3198 ◽  
Author(s):  
Padmamalini Baskaran ◽  
Kyle Covington ◽  
Jane Bennis ◽  
Adithya Mohandass ◽  
Teresa Lehmann ◽  
...  
Keyword(s):  
Hydrogen Bond ◽  
Molecular Docking ◽  
Energy Expenditure ◽  
High Fat Diet ◽  
Transient Receptor Potential ◽  
Receptor Potential ◽  
Docking Studies ◽  
Transient Receptor Potential Vanilloid ◽  
Metabolic Dysfunction ◽  
High Fat

(1) Background: Capsaicin, a chief ingredient of natural chili peppers, enhances metabolism and energy expenditure and stimulates the browning of white adipose tissue (WAT) and brown fat activation to counter diet-induced obesity. Although capsaicin and its nonpungent analogs are shown to enhance energy expenditure, their efficiency to bind to and activate their receptor—transient receptor potential vanilloid subfamily 1 (TRPV1)—to mediate thermogenic effects remains unclear. (2) Methods: We analyzed the binding efficiency of capsaicin analogs by molecular docking. We fed wild type mice a normal chow or high fat diet (± 0.01% pungent or nonpungent capsaicin analog) and isolated inguinal WAT to analyze the expression of thermogenic genes and proteins. (3) Results: Capsaicin, but not its nonpungent analogs, efficiently binds to TRPV1, prevents high fat diet-induced weight gain, and upregulates thermogenic protein expression in WAT. Molecular docking studies indicate that capsaicin exhibits the highest binding efficacy to TRPV1 because it has a hydrogen bond that anchors it to TRPV1. Capsiate, which lacks the hydrogen bond, and therefore, does not anchor to TRPV1. (4) Conclusions: Long-term activation of TRPV1 is imminent for the anti-obesity effect of capsaicin. Efforts to decrease the pungency of capsaicin will help in advancing it to mitigate obesity and metabolic dysfunction in humans.

scholarly journals Compound2Drug – a Machine/deep Learning Tool for Predicting the Bioactivity of PubChem Compounds

2020 ◽  
Author(s):  
Ben Geoffrey A S ◽  
Pavan Preetham Valluri ◽  
Akhil Sanker ◽  
Rafal Madaj ◽  
Host Antony Davidd ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Molecular Docking ◽  
Drug Target ◽  
Drug Targets ◽  
Learning Algorithms ◽  
Network Data ◽  
Ligand Interaction ◽  
Pubchem Compound ◽  
Protein Ligand Interaction

<p>Network data is composed of nodes and edges. Successful application of machine learning/deep learning algorithms on network data to make node classification and link prediction has been shown in the area of social networks through which highly customized suggestions are offered to social network users. Similarly one can attempt the use of machine learning/deep learning algorithms on biological network data to generate predictions of scientific usefulness. In the present work, compound-drug target interaction data set from bindingDB has been used to train machine learning/deep learning algorithms which are used to predict the drug targets for any PubChem compound queried by the user. The user is required to input the PubChem Compound ID (CID) of the compound the user wishes to gain information about its predicted biological activity and the tool outputs the RCSB PDB IDs of the predicted drug target. The tool also incorporates a feature to perform automated <i>In Silico</i> modelling for the compounds and the predicted drug targets to uncover their protein-ligand interaction profiles. The programs fetches the structures of the compound and the predicted drug targets, prepares them for molecular docking using standard AutoDock Scripts that are part of MGLtools and performs molecular docking, protein-ligand interaction profiling of the targets and the compound and stores the visualized results in the working folder of the user. The program is hosted, supported and maintained at the following GitHub repository </p> <p><a href="https://github.com/bengeof/Compound2Drug">https://github.com/bengeof/Compound2Drug</a></p>

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