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Functional Analysis and Molecular Docking studies of Medicinal Compounds for AChE and BChE in Alzheimer's Disease and Type 2 Diabetes Mellitus.

ABSTRACT: Acetylcholinesterase and Butyrylcholinesterase share unravelling link with components of metabolic syndromes that's characterised by low levels of HDL cholesterol, obesity, high fast aldohexose levels, hyper-trigliceridaemia and high blood pressure, by regulation of cholinergic transmission and therefore the enzyme activity within a living system. The phosphomotifs associated with amino acid and tyrosine binding motifs in AChE and BChE were known to be common. Phylogenetic tree was constructed to these proteins usinf UPGMA and Maximum Likelihood methods in MEGA software has shown interaction of AChE and BChE with ageing diseases like Alzheimer's disease and Diabetes. AChE has shown closely related to BChE, retinol dehydrogenase and ?-polypeptide. The present studies is also accomplished that AChE, BChE, COLQ, HAND1, APP, NLGN2 and NGF proteins has interactions with diseases such as Alzheimer's and D2M using Pathwaylinker and STRING. Medicinal compounds like Ortho-7, Dibucaine and HI-6 are predicted as good targets for modeled AChE and BChE proteins based on docking studies. Hence perceptive studies of cholinesterase structure and the biological mechanisms of inhibition are necessary for effective drug development.

SUBMITTER: Kaladhar DS

PROVIDER: S-EPMC3733582 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Functional Analysis and Molecular Docking studies of Medicinal Compounds for AChE and BChE in Alzheimer's Disease and Type 2 Diabetes Mellitus.

Kaladhar Dowluru Svgk DS Yarla Nagendra Sastry NS Anusha N N

Aging and disease 20130620 4

Acetylcholinesterase and Butyrylcholinesterase share unravelling link with components of metabolic syndromes that's characterised by low levels of HDL cholesterol, obesity, high fast aldohexose levels, hyper-trigliceridaemia and high blood pressure, by regulation of cholinergic transmission and therefore the enzyme activity within a living system. The phosphomotifs associated with amino acid and tyrosine binding motifs in AChE and BChE were known to be common. Phylogenetic tree was constructed t ...[more]

PMID: 23936743

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Project description:A set of 25 novel, silicon-based carbamate derivatives as potential acetyl- and butyrylcholinesterase (AChE/BChE) inhibitors was synthesized and characterized by their in vitro inhibition profiles and the selectivity indexes (SIs). The prepared compounds were also tested for their inhibition potential on photosynthetic electron transport (PET) in spinach (Spinacia oleracea L.) chloroplasts. In fact, some of the newly prepared molecules revealed comparable or even better inhibitory activities compared to the marketed drugs (rivastigmine or galanthamine) and commercially applied pesticide Diuron®, respectively. Generally, most compounds exhibited better inhibition potency towards AChE; however, a wider activity span was observed for BChE. Notably, benzyl N-[(1S)-2-[(tert-butyldimethylsilyl)oxy]-1-[(2-hydroxyphenyl)carbamoyl]ethyl]-carbamate (2) and benzyl N-[(1S)-2-[(tert-butyldimethylsilyl)oxy]-1-[(3-hydroxyphenyl)carbamoyl]ethyl]-carbamate (3) were characterized by fairly high selective indexes. Specifically, compound 2 was prescribed with the lowest IC50 value that corresponds quite well with galanthamine inhibition activity, while the inhibitory profiles of molecules 3 and benzyl-N-[(1S)-2-[(tert-butyldimethylsilyl)oxy]-1-[(4-hydroxyphenyl)carbamoyl]ethyl]carbamate (4) are in line with rivastigmine activity. Moreover, a structure-activity relationship (SAR)-driven similarity evaluation of the physicochemical properties for the carbamates examined appeared to have foreseen the activity cliffs using a similarity-activity landscape index for BChE inhibitory response values. The 'indirect' ligand-based and 'direct' protein-mediated in silico approaches were applied to specify electronic/steric/lipophilic factors that are potentially valid for quantitative (Q)SAR modeling of the carbamate analogues. The stochastic model validation was used to generate an 'average' 3D-QSAR pharmacophore pattern. Finally, the target-oriented molecular docking was employed to (re)arrange the spatial distribution of the ligand property space for BChE and photosystem II (PSII).

Project description:Neurodegenerative diseases, for example Alzheimer's, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world; innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds' pIC50 values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R2 = 0.86 and Q2 = 0.73), pls_38 (R2 = 0.77 and Q2 = 0.72), kpls_desc_44 (R2 = 0.81 and Q2 = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of -9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of -9.60 and -9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (-6.30 kcal/mol). The docking scores of our standards were -10.40 and -7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.

Dataset Information

Functional Analysis and Molecular Docking studies of Medicinal Compounds for AChE and BChE in Alzheimer's Disease and Type 2 Diabetes Mellitus.

Publications

Functional Analysis and Molecular Docking studies of Medicinal Compounds for AChE and BChE in Alzheimer's Disease and Type 2 Diabetes Mellitus.

Similar Datasets

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