| Literature DB >> 27838184 |
Sk Abdul Amin1, Nilanjan Adhikari2, Tarun Jha2, Shovanlal Gayen3.
Abstract
Huntington's disease (HD) is caused by mutation of huntingtin protein (mHtt) leading to neuronal cell death. The mHtt induced toxicity can be rescued by inhibiting the kynurenine monooxygenase (KMO) enzyme. Therefore, KMO is a promising drug target to address the neurodegenerative disorders such as Huntington's diseases. Fiftysix arylpyrimidine KMO inhibitors are structurally explored through regression and classification based multi-QSAR modeling, pharmacophore mapping and molecular docking approaches. Moreover, ten new compounds are proposed and validated through the modeling that may be effective in accelerating Huntington's disease drug discovery efforts.Entities:
Keywords: Artificial neural network; Bayesian modeling; Huntington’s disease; Kynurenine monooxygenase; Linear discriminant analysis; Molecular docking; Pharmacophore mapping; Support vector machine
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Year: 2016 PMID: 27838184 DOI: 10.1016/j.bmcl.2016.10.058
Source DB: PubMed Journal: Bioorg Med Chem Lett ISSN: 0960-894X Impact factor: 2.823