In SilicoMolecular Docking andIn VitroAntidiabetic Studies of Dihydropyrimido[4,5-a]acridin-2-amines

Bharathi, A.; Roopan, Selvaraj Mohana; Vasavi, C. S.; Munusami, Punnagai; Gayathri, G. A.; Gayathri, M.

doi:10.1155/2014/971569

Cited by 31 publications

(17 citation statements)

References 37 publications

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“…In silico drug discovery methods, and the development of antidiabetic drug repurposing has become an important factor in new drug discovery. Several computational approaches that help us to uncover new antidiabetic drug opportunities and discovery process have been screened or adapted from previous applications [ 286 ]. Accordingly, identification of new drugs is expected to help predict new drug-targets, [ 228 ].…”

Section: Perspectives Of In Silico Modelling For Discovery and Development Of Anti-diabetes Drugsmentioning

confidence: 99%

In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II Diabetes

Riyaphan¹,

Pham

Leong

et al. 2021

Biomolecules

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Type-II diabetes mellitus (T2DM) results from a combination of genetic and lifestyle factors, and the prevalence of T2DM is increasing worldwide. Clinically, both α-glucosidase and α-amylase enzymes inhibitors can suppress peaks of postprandial glucose with surplus adverse effects, leading to efforts devoted to urgently seeking new anti-diabetes drugs from natural sources for delayed starch digestion. This review attempts to explore 10 families e.g., Bignoniaceae, Ericaceae, Dryopteridaceae, Campanulaceae, Geraniaceae, Euphorbiaceae, Rubiaceae, Acanthaceae, Rutaceae, and Moraceae as medicinal plants, and folk and herb medicines for lowering blood glucose level, or alternative anti-diabetic natural products. Many natural products have been studied in silico, in vitro, and in vivo assays to restrain hyperglycemia. In addition, natural products, and particularly polyphenols, possess diverse structures for exploring them as inhibitors of α-glucosidase and α-amylase. Interestingly, an in silico discovery approach using natural compounds via virtual screening could directly target α-glucosidase and α-amylase enzymes through Monte Carto molecular modeling. Autodock, MOE-Dock, Biovia Discovery Studio, PyMOL, and Accelrys have been used to discover new candidates as inhibitors or activators. While docking score, binding energy (Kcal/mol), the number of hydrogen bonds, or interactions with critical amino acid residues have been taken into concerning the reliability of software for validation of enzymatic analysis, in vitro cell assay and in vivo animal tests are required to obtain leads, hits, and candidates in drug discovery and development.

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Section: Perspectives Of In Silico Modelling For Discovery and Development Of Anti-diabetes Drugsmentioning

confidence: 99%

In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II Diabetes

Riyaphan¹,

Pham

Leong

et al. 2021

Biomolecules

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“…This technique provides information about drug receptor interactions that are useful to predict the binding orientation of drug candidates to their target proteins 22 . Besides, this approach helps in systemic study by introducing a molecule on the binding spot of the object macromolecule in a non-covalent fashion, leading to an accurate binding at the active sites of each ligand 23 .…”

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confidence: 99%

GC–MS analysis of phytoconstituents from Amomum nilgiricum and molecular docking interactions of bioactive serverogenin acetate with target proteins

Konappa

Udayashankar

Krishnamurthy

et al. 2020

Sci Rep

148

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Amomum nilgiricum is one of the plant species reported from Western Ghats of India, belonging to the family Zingiberaceae, with ethno-botanical values, and is well-known for their ethno medicinal applications. In the present investigation, ethyl acetate and methanol extracts of A. nilgiricum were analyzed by Fourier transform infrared spectrometer (FTIR) and gas chromatography-mass spectrometry (GC–MS) to identify the important functional groups and phytochemical constituents. The FTIR spectra revealed the occurrence of functional characteristic peaks of aromatic amines, carboxylic acids, ketones, phenols and alkyl halides group from leaf and rhizome extracts. The GC–MS analysis of ethyl acetate and methanol extracts from leaves, and methanol extract from rhizomes of A. nilgiricum detected the presence of 25 phytochemical compounds. Further, the leaf and rhizome extracts of A. nilgiricum showed remarkable antibacterial and antifungal activities at 100 mg/mL. The results of DPPH and ferric reducing antioxidant power assay recorded maximum antioxidant activity in A. nilgiricum methanolic leaf extract. While, ethyl acetate leaf extract exhibited maximum α-amylase inhibition activity, followed by methanolic leaf extract exhibiting aldose reductase inhibition. Subsequently, these 25 identified compounds were analyzed for their bioactivity through in silico molecular docking studies. Results revealed that among the phytochemical compounds identified, serverogenin acetate might have maximum antibacterial, antifungal, antiviral, antioxidant and antidiabetic properties followed by 2,4-dimethyl-1,3-dioxane and (1,3-13C2)propanedioic acid. To our best knowledge, this is the first description on the phytochemical constituents of the leaves and rhizomes of A. nilgiricum, which show pharmacological significance, as there has been no literature available yet on GC–MS and phytochemical studies of this plant species. The in silico molecular docking of serverogenin acetate was also performed to confirm its broad spectrum activities based on the binding interactions with the antibacterial, antifungal, antiviral, antioxidant and antidiabetic target proteins. The results of the present study will create a way for the invention of herbal medicines for several ailments by using A. nilgiricum plants, which may lead to the development of novel drugs.

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“…This bond is an essential bond in the process of combining the nonpolar region of the drug molecule with the nonpolar region of the biologic receptor, where the nonpolar part of the drug molecule that is unable to dissolve in water will combine with the surrounding water molecules through hydrophobic bonds form a quasi-crystalline structure. This hydrophobic bond also has a significant role in determining the binding strength between protein and ligand (Bharathi et al, 2014;Chakraborty et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

Molecular Docking of Compounds in Moringa oleifera Lam with Dipeptidyl Peptidase-4 Receptors as Antidiabetic Candidates

Rendi

Maranata

Chaerunisa

et al. 2021

JFIKI

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Background: Diabetes mellitus (DM) type 2 is a metabolic disorder that needs special attention because it can damage several organs if the severity increases. One of the treatments for diabetes mellitus (DM) type 2 is by inhibiting Dipeptidyl peptidase 4 (DPP-IV) with vildagliptin to prolong the hypoglycemic effect of GLP-1 and GIP. Objective: In the search for candidate compounds as new antidiabetic compounds, an in silico test with molecular docking was carried out to predict the antidiabetic activity of 10 Moringa oleifera Lam (MO) plant compounds at the DPP-IV receptor (PDB ID: 6B1E). Method: The study was conducted using the molecular docking method. Result: Validation of the vildagliptin DPP-IV ligand obtained free energy values of -9.27 kcal/mol and RMSD 1.49 Å (RMSD < 2 Å), then tested with 10 test compounds obtained 8 test compounds that have the potential to be antidiabetic. Conclusion: Serpentine compounds have better potential as an antidiabetic drug than other target compounds because they have the closest Gibbs energy (∆G) value to the natural ligand of Vidaglibtin, which is -7.90 kcal/mol. This value is still lower than the free energy of vildagliptin, which is -9.37 kcal/mol. Therefore further testing is needed to ensure the potential of the compound as a candidate for antidiabetic drugs.

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In SilicoMolecular Docking andIn VitroAntidiabetic Studies of Dihydropyrimido[4,5-a]acridin-2-amines

Cited by 31 publications

References 37 publications

In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II Diabetes

In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II Diabetes

GC–MS analysis of phytoconstituents from Amomum nilgiricum and molecular docking interactions of bioactive serverogenin acetate with target proteins

Molecular Docking of Compounds in Moringa oleifera Lam with Dipeptidyl Peptidase-4 Receptors as Antidiabetic Candidates

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