Virtual screening of commercial cyclic peptides as NS2B-NS3 protease inhibitor of dengue virus serotype 2 through molecular docking simulation

Dengue is a global health problem which predominantly affected the tropical and subtropical region of Asia, Africa, and America. However, there are no available antiviral agents to treat dengue virus (DENV) infection. This study was conducted to utilize natural product compounds as an inhibitor of NS5 Methyltransferase, a viral protein which plays an essential role in the synthesis of DENV RNA. The natural product compounds were collected from the Universal Natural Product Database (UNPD), totaling 229,000 compounds. The in silico screening of the natural product compounds was performed by molecular docking simulation method, which simulates the interaction of the compounds on the active site of the NS5 methyltransferase. From the molecular docking simulation, about 51 compounds showed better affinity and interaction compared to the standard compound, S-Adenosyl-L-Homocysteine (SAH). Then, a series of pharmacological tests were performed to find the best drug candidates by employing DataWarrior and SwissADME software. Finally, three natural product compounds, namely UNPD98966, UNPD183023, and UNDP104952, were regarded as the best inhibitor against NS5 methyltransferase based on its molecular affinity and interaction. These compounds also showed potential as drug candidates due to their desirable pharmacological properties.

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Isoindole-1,3-dione derivatives as RSK2 inhibitors: synthesis, molecular docking simulation and SAR analysis

MedChemComm ◽

10.1039/c5md00469a ◽

2016 ◽

Vol 7 (2) ◽

pp. 292-296 ◽

Cited By ~ 8

Author(s):

Wei Zhou ◽

Shiliang Li ◽

Weiqiang Lu ◽

Jun Yuan ◽

Yufang Xu ◽

...

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Docking Simulation ◽

Molecular Docking Simulation ◽

Sar Analysis

The present study reports a series of novel potent RSK2 inhibitors obtained from structure modifications of a virtual screening hit.

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Molecular Docking Simulation based Virtual Screening for The Design of Potential Inhibitors of Heme Oxygenase of Corney Bacterium Diphtheria

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.a3411.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 1086-1091

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Docking Simulation ◽

Upper Respiratory Tract ◽

Molecular Docking Simulation ◽

Simulation Based ◽

Cardiac Muscles ◽

Oxidase Enzyme ◽

Corynebacterium Diphtheria ◽

Potential Inhibitors

Diphtheria is an infectious human disorder affecting upper respiratory tract which is characterized by fever, sore throat, and malaise. It is caused by Corynebacterium diphtheria and other pathogenic strains of Corynebacterium. The pathogen invades in the nasopharynx and infects the host by releasing an exotoxin leading to the severe concerns in thekidneys, nervous system and cardiac muscles. Sometimes diphtheria infections may be fatal because of the circulatory failure caused by myocarditis.Hemeoxygenase is the rate limiting enzyme in heme degradation and catalyzes the NADPHcytochrome P450 reductase-dependent cleavage of heme to biliverdin with the release of iron and carbon monoxide. In the present paper we have performed molecular docking simulation based in-silico virtual screening of an NCI diversity set-II containing 1593 diverse ligands to identify potential inhibitor of the Heme oxidase enzyme of Corneybacterium diphtheria. The lead molecules are shortlisted on the basis of their binding energy and these molecules are supposed to be further evaluated experimentally for development of a newer therapy for the treatment of diphtheria.

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Molecular docking study of Lens culinaris L. phytochemicals to NS3-NS2B protease of dengue virus serotype 2

German Journal of Microbiology - Special Issue: Existence Battle: Viruses vs. Creatures ◽

10.51585/gjm.2021.0005 ◽

2021 ◽

Vol 1 (1) ◽

pp. 26-37

Keyword(s):

Molecular Docking ◽

Binding Energy ◽

Dengue Virus ◽

Binding Affinity ◽

Lens Culinaris ◽

Binding Affinities ◽

High Binding ◽

Virus Serotype ◽

Dengue Virus Serotype 2 ◽

High Binding Affinity

Forty-three phytochemicals present in Lens culinaris were evaluated through in-silico molecular docking studies for their binding affinities to the NS2B-NS3 activator-protease complex of dengue virus serotype 2 (DENV-2). Among the various compounds tested, flavonoids (flavanols,favonols, proanthocyanidins, flavanones, flavones, and anthocyanins) demonstrated high binding affinities for the protease complex. Eriodictyol-7-O-rutinoside showed the least predicted binding energy at -9.1 kcal/mol followed by luteolin-7-O-glucoside at -8.8 kcal/mol. Glycosidic linkages appeared to enhance the binding affinities of flavonoids, aldohexoses being more potent than aldopentoses. Besides flavonoids, other classes of compounds demonstrating high binding affinities for the protease were carotenoids, phytosterols, and polyphenolic compounds like resveratrol and trans-resveratrol 3-O-b-glucoside (piceid), the latter showing predicted binding energy of -8.5 kcal/mol versus predicted binding energy of -7.2 kcal/mol for resveratrol. The 2D interactions of four high binding affinity compounds like eriodictyol, eriodictyol-7-O-rutinoside, catechin gallate, and luteolin-7-O-glucoside showed that all four compounds bound to the active site of the NS3 protease and not to the activator NS2B. Lys74 of NS3 was the common amino acid interacting with all four phytochemicals. Analysis of physicochemical properties of the compounds (Lipinski's Rule of 5) showed that the high binding affinity compounds have less than two violations, indicating that they can serve as useful lead compounds or as dengue virus serotype 2 therapeutics.

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Pharmacophore-based virtual screening and molecular docking simulation of flavonoids as smoothened protein inhibitor of Hedgehog signaling pathways

10.1063/1.5132487 ◽

2019 ◽

Author(s):

M. A. F. Nasution ◽

F. Stephanie ◽

U. S. F. Tambunan

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Signaling Pathways ◽

Hedgehog Signaling ◽

Docking Simulation ◽

Protein Inhibitor ◽

Molecular Docking Simulation

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Molecular docking and QSAR theoretical model for prediction of phthalazinone derivatives as new class of potent dengue virus inhibitors

Beni-Suef University Journal of Basic and Applied Sciences ◽

10.1186/s43088-020-00073-9 ◽

2020 ◽

Vol 9 (1) ◽

Author(s):

Samuel Ndaghiya Adawara ◽

Gideon Adamu Shallangwa ◽

Paul Andrew Mamza ◽

Abdulkadir Ibrahim

Keyword(s):

Molecular Docking ◽

Dengue Virus ◽

Density Functional ◽

Binding Free Energy ◽

Statistical Parameter ◽

Chemical Compounds ◽

Basis Set ◽

Binding Affinities ◽

Virus Serotype ◽

Dengue Virus Serotype 2

Abstract Background Dengue fever is a key public health unease in various tropical and sub-tropical regions. The improvement of existing agents that can inhibit the dengue virus is therefore of utmost importance. In this work, the QSAR study was carried out on 25 molecules of phthalazinone derivatives which have been reported to possess excellent dengue virus inhibitory activity. Density functional computational technique was used in the optimisation of the molecules with the basis set at theory level (B3LYP, 6-31G*) respectively. The multiple linear regression (MLR) model was built using genetic function approximation (GFA) in the material studio software package. Also, in this study, molecular docking simulation was carried between dengue virus serotype 2 protease (PDB CODE: 6mol) and some selected phthalazinone derivatives (compounds 1, 2, 7, 11, and 21). Results The model was robust as evidenced by validation and robustness statistical parameter which include predicted R2pred., adjusted R2adj., cross-validated Q2 and R2 regression coefficient, etc (R2pred. = 0.71922, R2adj. = 0.939699, Q2CV = 0.905909, R2 = 0.955567) respectively. The molecular docking studies conducted in this study have outlined the binding affinities of the selected compounds (1, 2, 7 11, and 21) which are all in good correlation with their respective pIC50 values. The free binding affinities of the selected compounds were found to be (− 8.7, − 8.8, − 8.7, − 8.3, and − 8.9 kcal/mol) respectively, compound 21 with the binding affinity of − 8.9 kcal/mol had the best binding free energy with the protease relative to other compounds under consideration. Conclusion The MLR-GFA model study alongside with the molecular docking analysis has essentially provided a valuable and in-depth understanding as well as knowledge for the development of novel chemical compounds with enhanced inhibitory potential against the dengue virus serotype 2 (DNV-2). Hence, the developed model can be applicable in predicting the anti-dengue activity of a new set of chemical compounds that fall within its applicability domain.

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