3d-Pharmacophore Modelling of Omega-3 Derivatives With Peroxisome Proliferator-Activated Receptor Gamma as an Anti-Obesity Agent

Musfiroh, Ida; Megawati, Ginna; Herawati, Dewi Marhaeni Diah; RUSDIN, AGUS

doi:10.22159/ijap.2021.v13s4.43851

Cited by 3 publications

(7 citation statements)

References 16 publications

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“…Software: ChemDraw 8.0, Discovery Studio, GaussView 8.0, Ligandscout 4.4.5 [9], Autodock Tools 1.5.6., Protein Data Bank (PDB) (http://www.rscb.org)…”

Section: Methodsmentioning

confidence: 99%

“…[10], Pub Chem (http://pubchem.ncbi.nlm.nih.gov/) [11], and database activedecoys used dude (http://dude.docking.org/) [9,12] were used in this study [13]. The ligand structure was drawn using Chemdraw software and the structure was optimized using the Gaussian…”

Section: Methodsmentioning

confidence: 99%

“…In structural modeling, a total of 10 models were validated using the enrichment factor parameter (EF 1%) to determine the specificity, accuracy, sensitivity values, and Receiver Operating Characteristics (ROC) of the Area Under Curve (AUC 100%). Pharmacophore screening was carried out based on a selected best model against a database of test compounds consisting of γ-mangosteen, α-mangosteen, ibuprofen, celecoxib, and L-arginine [9].…”

Section: Pharmacophore Modelingmentioning

confidence: 99%

“…The following method validation results (fig. 1) Represent the best model of the ROC curve of the COX-1, COX-2, and iNOS targets [9]. Based on the results, the value of Area Under Curve (AUC100%) and enrichment factor (EF100%) iNOs; COX-1 (0.75 and 4.0), COX-2 (1.00 and 5.0), and iNOS (1.00 and 5,0).…”

Section: Screening Pharmacophore Of Inos Cox-1 and Cox-2mentioning

confidence: 99%

“…positively ionized, hydrophobic interactions, hydrogen bond donors, and acceptors, are represented as blue stars, yellow circled, green arrows, and red arrows, respectively. The interaction between the COX-1 or COX-2 target with the test compound was mainly hydrophobic and hydrogen bonding interactions existed in all compounds that had hits on the COX-1 and COX-2 targets [20,9].…”

Section: Screening Pharmacophore Of Inos Cox-1 and Cox-2mentioning

confidence: 99%

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Interactions of Xanthone Compounds From the Mangosteen (Garcinia Mangostana L) Pericarps Against Inos, Cox-1, and Cox-2 Enzyme Receptors as Anti-Inflammatory

Lestari¹,

SARI²,

Musfiroh

et al. 2023

Int J App Pharm

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Objective: Mangosteen is a plant that is very effective for inflammation. Besides that, the skin of the mangosteen plant in Indonesia continues to be developed because it is an antioxidant and suppresses the production of cytokines. Methods: Screening pharmacophores and molecular docking simulations by molecular modeling computation to predict the activity of the Mangosteen plant in silico and to determine potential drug candidates from mangosteen for inflammation to the iNOS, COX-1, and COX-2. Results: Pharmacophore Screening, γ-mangosteen has the highest pharmacophore fit score of 33.32 and 33.64 on COX-1 and COX-2 and is selective to iNOS target. Molecular docking of α-mangosteen and γ-mangosteen test compounds to the active site of used, COX-1, and COX-2 enzymes showed free energy binding (ΔG °) values of,-5.09,-5.00,-6.15; and-6.76,-5.30,-7.81 Kcal/mol respectively. Meanwhile, hydrogen bonds and good ΔG ° values were formed between γ-mangosteen and COX-2, where the Hydroxyl group on γ-mangosteen interacted with the amino acids His75, Ser339, and Ala513 with ΔG ° of-7.81 Kcal/mol. Conclusion: It can be said that α-mangosteen and γ-mangosteen have molecular interactions with COX-1 and COX-2 active sites with the highest affinity for COX-2 compared to COX-1, and iNOS.

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“…Software: ChemDraw 8.0, Discovery Studio, GaussView 8.0, Ligandscout 4.4.5 [9], Autodock Tools 1.5.6., Protein Data Bank (PDB) (http://www.rscb.org)…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Pharmacophore Modelingmentioning

confidence: 99%

Section: Screening Pharmacophore Of Inos Cox-1 and Cox-2mentioning

confidence: 99%

Section: Screening Pharmacophore Of Inos Cox-1 and Cox-2mentioning

confidence: 99%

See 3 more Smart Citations

Interactions of Xanthone Compounds From the Mangosteen (Garcinia Mangostana L) Pericarps Against Inos, Cox-1, and Cox-2 Enzyme Receptors as Anti-Inflammatory

Lestari¹,

SARI²,

Musfiroh

et al. 2023

Int J App Pharm

Self Cite

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STABILITY OF OMEGA-3 COMPOUNDS COMPLEX WITH PPAR-γ RECEPTOR AS AN ANTI-OBESITY USING MOLECULAR DYNAMIC SIMULATION

Musfiroh

Megawati²,

Herawati³

et al. 2022

Int J App Pharm

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Objective: Obesity is a major contributor to comorbid diseases based on low grade chronic inflammation. Omega-3 fatty acids have a role in inflammation so it is thought to prevent obesity. This study was conducted to analyze the stability of omega-3 fatty acids with the PPAR-γ receptor using molecular dynamic simulation to investigate the relationship of macromolecule interactions to biologically relevant as an obesity comorbid. Methods: The methods consisted of ligand acquisition, molecular dynamic simulation, and analysis of dynamic molecular results using Gromacs 2016.3 software and the results of the MD analysis were carried out by simulating time with VMD software and graphing the results of MD data analysis using Microsoft Excel. Results: The result showed that docosahexaenoic acid (DHA), docosapentaenoic acid (DPA), and heneicosapentaenoic acid (HPA) have good stability. Average RMSD values of DHA, DPA, and HPA were 0.347 Å, 0.464 Å, and 0.706 Å with similar pattern of fluctuation across the region. DHA forms a hydrogen bond to Tyr347 and Leu343. Meanwhile, DPA binds to Asn52 and HPA bind to Arg213. DHA, DPA, and HPA have an average SASA of 233.91 nm2, 231.47 nm2, and 225.52 nm2, respectively. DHA has the lowest total binding energy (-129.914 kJ/mol) compared to DPA (-102.018 kJ/mol) and HPA (-115.992 kJ/mol). Conclusion: Based on the molecular dynamics simulation approach, omega-3 compounds, DHA, DPA, and HPA showed that DHA has good stability compared to DPA and HPA. DHA, DPA, and HPA can be used as lead drugs to bind to PPAR-γ receptors to prevent and treat obesity.

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Molecular dynamic of omega-3 compounds as an anti-obesity agent into GPR-120 receptor

Musfiroh,

Megawati,

Diah Herawati

et al. 2023

PHAR

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Obesity is a cause of comorbid diseases such as type 2 diabetes mellitus, dyslipidemia, hypertension which is based on low-level chronic inflammation. The GPR-120 receptor plays a role in insulin sensitization which is related to diabetes mellitus which is a comorbid obesity. Omega-3 fatty acids are believed to possess anti-inflammatory properties, hence potentially serving as a preventive measure against obesity-related comorbidities. The aim of this study is to do a stability analysis of the binding affinity between nine specific chemicals derived from omega-3 and the active site of the human GPR120 receptor using molecular dynamics simulations. Docking analysis was performed using Discovery Studio Visualizer, AutoDock Tools 1.5.6, and molecular dynamic simulation with AMBER 16. In this study, we used neurotensin 8–13 as a natural ligand to bind with the neurotensin receptor. Based on the neurotensin receptor docking results, the ΔG values for the following compounds are close to the values for neurotensin 8–13 -6.41 kcal/mol; docosahexaenoic acid -8.96 kcal/mol; eicosapentaenoic acid -7.41 kcal/mol; and heneicosapentaenoic acid -6.34 kcal/mol. Neurotensin 8–13 forms hydrogen bonds with TYR146, ARG213, and PHE344 of the neurotensin receptor, whereas docosahexaenoic acid forms hydrogen bonds with TYR146. Meanwhile, the average RMSD fluctuations for each system, namely docosahexaenoic acid, eicosapentaenoic acid, and heneicosapentaenoic acid, were 0.672, 0.437, and 0.650, respectively. The SASA of the neurotensin receptor-ligand complex showed similar fluctuations, with the average values for docosahexaenoic acid, eicosapentaenoic acid, and heneicosapentaenoic acid being 230.40, 229.89, and 230.20 nm2.

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3d-Pharmacophore Modelling of Omega-3 Derivatives With Peroxisome Proliferator-Activated Receptor Gamma as an Anti-Obesity Agent

Cited by 3 publications

References 16 publications

Interactions of Xanthone Compounds From the Mangosteen (Garcinia Mangostana L) Pericarps Against Inos, Cox-1, and Cox-2 Enzyme Receptors as Anti-Inflammatory

Interactions of Xanthone Compounds From the Mangosteen (Garcinia Mangostana L) Pericarps Against Inos, Cox-1, and Cox-2 Enzyme Receptors as Anti-Inflammatory

STABILITY OF OMEGA-3 COMPOUNDS COMPLEX WITH PPAR-γ RECEPTOR AS AN ANTI-OBESITY USING MOLECULAR DYNAMIC SIMULATION

Molecular dynamic of omega-3 compounds as an anti-obesity agent into GPR-120 receptor

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