Design, synthesis, biological evaluation and molecular docking studies of novel 3-substituted-5-[(indol-3-yl)methylene]-thiazolidine-2,4-dione derivatives

Kumar, K. Srikanth; Rao, A. Lakshmana; Rao, Mandava V. Basaveswara

doi:10.1016/j.heliyon.2018.e00807

Cited by 19 publications

(10 citation statements)

References 29 publications

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“…Using ChemDraw Tools, the molecules were sketched and imported and saved into sdf format using open free software from Babel. The co-crystallised protein structures of CEBPD, TP73, ESR2, TAB1 and MAP 3K5 of its PDB code 3L4W, 2XWC, 1U3Q, 5NZZ & 2CLQwas extracted from Protein Data Bank [ 32 – 36 ]. Together with the TRIPOS force field, GasteigerHuckel (GH) charges were added to all designed derivatives for the structure optimization process.…”

Section: Methodsmentioning

confidence: 99%

Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

Prashanth

Vastrad²,

Tengli

et al. 2021

BMC Endocr Disord

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Background Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results A total of 820 DEGs were identified between healthy obese and metabolically unhealthy obese, among 409 up regulated and 411 down regulated genes. The GO enrichment analysis results showed that these DEGs were significantly enriched in ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway enrichment analysis results showed that these DEGs were significantly enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP 3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play an essential role in obesity associated type 2 diabetes mellitus was further screened. Conclusions The present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing therapeutic targets for obesity associated type 2 diabetes mellitus.

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Section: Methodsmentioning

confidence: 99%

Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

Prashanth

Vastrad²,

Tengli

et al. 2021

BMC Endocr Disord

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“…AutoDock 4.2.6 works on the principle of the Lamarckian Genetic Algorithm (LGA) which is a combination of the Genetic Algorithm (GA), Monte Carlo simulation, and hybrid local search Genetic Algorithm (Forli et al., 2016 ; Ibrahim et al., 2020; Morris et al., 1998 ). This algorithm helps us in the comprehensive study of protein-ligand conformations based on lowest-binding energies (Kumar et al., 2018 ). Development of bioinformatics and computational biology has led to several add on features such as overcoming the previous drawbacks such as the identification of inhibitory constants for the docked conformations.…”

Section: Introductionmentioning

confidence: 99%

Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease

Shivanika

Kumar²,

Ragunathan

et al. 2020

Journal of Biomolecular Structure and Dynamics

172

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The study aims to evaluate the potency of two hundred natural antiviral phytocompounds against the active site of the Severe Acquired Respiratory Syndrome-Coronavirus À 2 (SARS-CoV-2) Main-Protease (M pro) using AutoDock 4.2.6. The three-dimensional crystal structure of the M pro (PDB Id: 6LU7) was retrieved from the Protein Data Bank (PDB), the active site was predicted using MetaPocket 2.0. Food and Drug Administration (FDA) approved viral protease inhibitors were used as standards for comparison of results. The compounds theaflavin-3-3'-digallate, rutin, hypericin, robustaflavone, and (-)-solenolide A with respective binding energy of À12.41 (Ki ¼ 794.96 pM); À11.33 (Ki ¼ 4.98 nM); À11.17 (Ki ¼ 6.54 nM); À10.92 (Ki ¼ 9.85 nM); and À10.82 kcal/mol (Ki ¼ 11.88 nM) were ranked top as Coronavirus Disease À 2019 (COVID-19) M pro inhibitors. The interacting amino acid residues were visualized using Discovery Studio 3.5 to elucidate the 2-dimensional and 3-dimensional interactions. The study was validated by i) re-docking the N3-peptide inhibitor-M pro and superimposing them onto co-crystallized complex and ii) docking decoy ligands to M pro. The ligands that showed low binding energy were further predicted for and pharmacokinetic properties and Lipinski's rule of 5 and the results are tabulated and discussed. Molecular dynamics simulations were performed for 50 ns for those compounds using the Desmond package, Schr€ odinger to assess the conformational stability and fluctuations of protein-ligand complexes during the simulation. Thus, the natural compounds could act as a lead for the COVID-19 regimen after in-vitro and in-vivo clinical trials.

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“…The binding energy was negative. Thus, the change (ΔG) indicates that the binding process is spontaneous and the drug fits well in the binding pocket receptor, forming the most stable drug receptor [ 26 ]. If the binding energy value of the chemical compound is negative and larger, accepted as a drug [ 27 ].…”

Section: Resultsmentioning

confidence: 99%

Cheonggukjang-Specific Component 1,3-Diphenyl-2-Propanone as a Novel PPARα/γ Dual Agonist: An In Vitro and In Silico Study

Arulkumar

Jung

Noh

et al. 2021

IJMS

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Background: Cheonggukjang is a traditional fermented soybean paste that is mostly consumed in Korea. However, the biological activities of Cheonggukjang specific compounds have not been studied. Thus, we aimed to discover a novel dual agonist for PPARα/γ from dietary sources such as Cheonggukjang specific volatile compounds and explore the potential role of PPARα/γ dual agonists using in vitro and in silico tools. Methods: A total of 35 compounds were selected from non-fermented and fermented soybean products cultured with Bacillus subtilis, namely Cheonggukjang, for analysis by in vitro and in silico studies. Results: Molecular docking results showed that 1,3-diphenyl-2-propanone (DPP) had the lowest docking score for activating PPARα (1K7L) and PPARγ (3DZY) with non-toxic effects. Moreover, DPP significantly increased the transcriptional activities of both PPARα and PPARγ and highly activated its expression in Ac2F liver cells, in vitro. Here, we demonstrated for the first time that DPP can act as a dual agonist of PPARα/γ using in vitro and in silico tools. Conclusions: The Cheonggukjang-specific compound DPP could be a novel PPARα/γ dual agonist and it is warranted to determine the therapeutic potential of PPARα/γ activation by dietary intervention and/or supplementation in the treatment of metabolic disorders without causing any adverse effects.

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Design, synthesis, biological evaluation and molecular docking studies of novel 3-substituted-5-[(indol-3-yl)methylene]-thiazolidine-2,4-dione derivatives

Cited by 19 publications

References 29 publications

Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease

Cheonggukjang-Specific Component 1,3-Diphenyl-2-Propanone as a Novel PPARα/γ Dual Agonist: An In Vitro and In Silico Study

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