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Evaluation of Novel Dual Acetyl- and Butyrylcholinesterase Inhibitors as Potential Anti-Alzheimer's Disease Agents Using Pharmacophore, 3D-QSAR, and Molecular Docking Approaches.

ABSTRACT: DL0410, containing biphenyl and piperidine skeletons, was identified as an acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitor through high-throughput screening assays, and further studies affirmed its efficacy and safety for Alzheimer's disease treatment. In our study, a series of novel DL0410 derivatives were evaluated for inhibitory activities towards AChE and BuChE. Among these derivatives, compounds 6-1 and 7-6 showed stronger AChE and BuChE inhibitory activities than DL0410. Then, pharmacophore modeling and three-dimensional quantitative structure activity relationship (3D-QSAR) models were performed. The R² of AChE and BuChE 3D-QSAR models for training set were found to be 0.925 and 0.883, while that of the test set were 0.850 and 0.881, respectively. Next, molecular docking methods were utilized to explore the putative binding modes. Compounds 6-1 and 7-6 could interact with the amino acid residues in the catalytic anionic site (CAS) and peripheral anionic site (PAS) of AChE/BuChE, which was similar with DL0410. Kinetics studies also suggested that the three compounds were all mixed-types of inhibitors. In addition, compound 6-1 showed better absorption and blood brain barrier permeability. These studies provide better insight into the inhibitory behaviors of DL0410 derivatives, which is beneficial for rational design of AChE and BuChE inhibitors in the future.

SUBMITTER: Pang X

PROVIDER: S-EPMC6152156 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Evaluation of Novel Dual Acetyl- and Butyrylcholinesterase Inhibitors as Potential Anti-Alzheimer's Disease Agents Using Pharmacophore, 3D-QSAR, and Molecular Docking Approaches.

Pang Xiaocong X Fu Hui H Yang Shilun S Wang Lin L Liu Ai-Lin AL Wu Song S Du Guan-Hua GH

Molecules (Basel, Switzerland) 20170726 8

DL0410, containing biphenyl and piperidine skeletons, was identified as an acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitor through high-throughput screening assays, and further studies affirmed its efficacy and safety for Alzheimer's disease treatment. In our study, a series of novel DL0410 derivatives were evaluated for inhibitory activities towards AChE and BuChE. Among these derivatives, compounds 6-1 and 7-6 showed stronger AChE and BuChE inhibitory activities than DL ...[more]

PMID: 28933746

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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

Evaluation of Novel Dual Acetyl- and Butyrylcholinesterase Inhibitors as Potential Anti-Alzheimer's Disease Agents Using Pharmacophore, 3D-QSAR, and Molecular Docking Approaches.

Publications

Evaluation of Novel Dual Acetyl- and Butyrylcholinesterase Inhibitors as Potential Anti-Alzheimer's Disease Agents Using Pharmacophore, 3D-QSAR, and Molecular Docking Approaches.

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