QSAR Models for Anti-Malarial Activity of 4-Aminoquinolines

被引:20
|
作者
Masand, Vijay H. [1 ]
Toropov, Andrey A. [2 ]
Toropova, Alla P. [2 ]
Mahajan, Devidas T. [1 ]
机构
[1] Vidya Bharati Coll, Dept Chem, Amravati 444602, Maharashtra, India
[2] IRCCS, Ist Ric Farmacol Mario Negri, I-20156 Milan, Italy
关键词
Anti-malarial activity; 4-aminoquinolines; QSAR; optimal descriptor; CORAL software; DIFFERENT VALIDATION CRITERIA; REAL EXTERNAL PREDICTIVITY; SYNTHETIC PRODIGININES; XANTHONE DERIVATIVES; CORAL SOFTWARE; TOXICITY; IMPACT; DRUG; NANOPARTICLES; SOLUBILITY;
D O I
10.2174/1573409910666140303114621
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
In the present study, predictive quantitative structure - activity relationship (QSAR) models for anti-malarial activity of 4-aminoquinolines have been developed. CORAL, which is freely available on internet (http://www.insilico.eu/coral), has been used as a tool of QSAR analysis to establish statistically robust QSAR model of anti-malarial activity of 4-aminoquinolines. Six random splits into the visible sub-system of the training and invisible subsystem of validation were examined. Statistical qualities for these splits vary, but in all these cases, statistical quality of prediction for anti-malarial activity was quite good. The optimal SMILES-based descriptor was used to derive the single descriptor based QSAR model for a data set of 112 aminoquinolones. All the splits had r(2)> 0.85 and r(2)> 0.78 for sub-training and validation sets, respectively. The three parametric multilinear regression (MLR) QSAR model has Q(2) = 0.83, R-2 = 0.84 and F = 190.39. The anti-malarial activity has strong correlation with presence/absence of nitrogen and oxygen at a topological distance of six.
引用
收藏
页码:75 / 82
页数:8
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