QSAR Models for Anti-Malarial Activity of 4-Aminoquinolines

Title:QSAR Models for Anti-Malarial Activity of 4-Aminoquinolines

Volume: 10 Issue: 1

Author(s): Vijay H. Masand, Andrey A. Toropov, Alla P. Toropova and Devidas T. Mahajan

Affiliation:

Keywords: Anti-malarial activity, 4-aminoquinolines, QSAR, optimal descriptor, CORAL software.

Abstract: 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 r²> 0.85 and r²> 0.78 for subtraining and validation sets, respectively. The three parametric multilinear regression (MLR) QSAR model has Q² = 0.83, R² = 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.

Cite this article as:

Masand H. Vijay, Toropov A. Andrey, Toropova P. Alla and Mahajan T. Devidas, QSAR Models for Anti-Malarial Activity of 4-Aminoquinolines, Current Computer-Aided Drug Design 2014; 10 (1) . https://dx.doi.org/10.2174/1573409910666140303114621