First molecular modeling report on novel arylpyrimidine kynurenine monooxygenase inhibitors through multi-QSAR analysis against Huntington's disease: A proposal to chemists!

被引：42

作者：

Amin, Sk. Abdul ^{[1
,2
]}

Adhikari, Nilanjan ^{[2
]}

Jha, Tarun ^{[2
]}

Gayen, Shovanlal ^{[1
]}

机构：

[1] Dr Hari Singh Gour Vishwavidyalaya, Dept Pharmaceut Sci, Lab Drug Design & Discovery, Sagar 470003, Madhya Pradesh, India

[2] Jadavpur Univ, Dept Pharmaceut Technol, Nat Sci Lab, Div Med & Pharmaceut Chem, Kolkata 700032, W Bengal, India

来源：

BIOORGANIC & MEDICINAL CHEMISTRY LETTERS | 2016年 / 26卷 / 23期

关键词：

Huntington's disease; Kynurenine monooxygenase; Support vector machine; Artificial neural network; Linear discriminant analysis; Bayesian modeling; Pharmacophore mapping; Molecular docking; AGENTS; METABOLISM; DERIVATIVES; VALIDATION; PREDICTION; SERIES; BRAIN;

D O I：

10.1016/j.bmcl.2016.10.058

中图分类号：

R914 [药物化学];

学科分类号：

100705 [微生物与生化药学];

摘要：

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. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：5712 / 5718

页数：7

共 36 条

[1]

Structural findings of phenylindoles as cytotoxic antimitotic agents in human breast cancer cell lines through multiple validated QSAR studies [J].