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Molecular Docking and In Silico ADMET Study Reveals Acylguanidine 7a as a Potential Inhibitor of ?-Secretase.

ABSTRACT: Amyloidogenic pathway in Alzheimer's disease (AD) involves breakdown of APP by ?-secretase followed by ?-secretase and results in formation of amyloid beta plaque. ?-secretase has been a promising target for developing novel anti-Alzheimer drugs. To test different molecules for this purpose, test ligands like acylguanidine 7a, rosiglitazone, pioglitazone, and tartaric acid were docked against our target protein ?-secretase enzyme retrieved from Protein Data Bank, considering MK-8931 (phase III trial, Merck) as the positive control. Docking revealed that, with respect to their free binding energy, acylguanidine 7a has the lowest binding energy followed by MK-8931 and pioglitazone and binds significantly to ?-secretase. In silico ADMET predictions revealed that except tartaric acid all other compounds had minimal toxic effects and had good absorption as well as solubility characteristics. These compounds may serve as potential lead compound for developing new anti-Alzheimer drug.

SUBMITTER: Nisha CM

PROVIDER: S-EPMC4842033 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Molecular Docking and In Silico ADMET Study Reveals Acylguanidine 7a as a Potential Inhibitor of β-Secretase.

Nisha Chaluveelaveedu Murleedharan CM Kumar Ashwini A Nair Prateek P Gupta Nityasha N Silakari Chitrangda C Tripathi Timir T Kumar Awanish A

Advances in bioinformatics 20160410

Amyloidogenic pathway in Alzheimer's disease (AD) involves breakdown of APP by β-secretase followed by γ-secretase and results in formation of amyloid beta plaque. β-secretase has been a promising target for developing novel anti-Alzheimer drugs. To test different molecules for this purpose, test ligands like acylguanidine 7a, rosiglitazone, pioglitazone, and tartaric acid were docked against our target protein β-secretase enzyme retrieved from Protein Data Bank, considering MK-8931 (phase III t ...[more]

PMID: 27190510

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Project description:IntroductionIn modern drug design, in silico methods are largely used to understand drug-receptor interactions and quantum chemical properties. In the present study, a computational de novo design approach was used to confirm mode of binding for antibacterial activity, elucidating quantum chemical properties and ADMET-drug-likeness of carbazole alkaloid (1) and three coumarins (2-4) isolated from roots of Clausena anisata.MethodsDocking studies were performed with DNA-Gyrase (6F86) and LasR binding domain (2UV0) employing a flexible ligand docking approach using AutoDock Vina. SwissADME prediction and toxicological predictions were performed by ADMET. The optimized structures and molecular electrostatic potential surface of the isolated compounds were predicted by DFT analysis using B3LYP/6-31G basis levels.Results and discussionThe docking results revealed that compound 3 showed better docking scores against both DNA gyrase B and LasR binding domain compared with ciprofloxacin with potential as an inhibitor of bacterial DNA gyrase and quorum sensing LasR binding domain. The SwissADME prediction results showed that all the isolated compounds (1-4) satisfy Lipinski's rule of five with zero violations. Toxicological prediction results suggested that all compounds and ciprofloxacin are non-hepatotoxic, non-carcinogenic, non-irritant, immunogenic, and non-cytotoxic. The DFT analysis results revealed that compound 3 has large electronegativity (?eV), global softness (? eV-1), global electrophilicity (?eV), and mutagenicity value closer to ciprofloxacin (with LD50 value of 480 mg/kg) suggesting better bioactivity and chemical reactivity with considerable intra-molecular charge transfer between electron-donor to electron-acceptor groups.ConclusionOverall, compound 3 may serve as a lead molecule that could be developed into a potent E. coli DNA gyrase B inhibitor and efficient inhibitor for quorum sensing auto-inducer LasR binding domain of Pseudomonas aeruginosa.

Dataset Information

Molecular Docking and In Silico ADMET Study Reveals Acylguanidine 7a as a Potential Inhibitor of ?-Secretase.

Publications

Molecular Docking and In Silico ADMET Study Reveals Acylguanidine 7a as a Potential Inhibitor of β-Secretase.

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