Predictive chemometric modeling and three-dimensional toxicophore mapping of diverse organic chemicals causing bioluminescent repression of the bacterium genus pseudomonas

Supratik Kar, Kunal Roy

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Classification and regression-based quantitative structure-activity relationship (QSAR) as well as three-dimensional (3D) toxicophore models were developed for toxicity prediction of 104 organic chemicals causing bioluminescent repression of the bacterium genus Pseudomonas isolated from industrial wastewater. Statistically significant and interpretable in silico models were obtained using linear discriminant analysis (classification), genetic partial least-squares (regression), and 3D toxicophore models. The QSAR and toxicophore models were scrupulously validated internally as well as externally along with the randomization test to avoid the possibilities of chance correlation. Features such as octanol-water partition coefficient, third-order branching, =CH2 fragment or unsaturation, and the presence of a higher number of electronegative atoms (specifically halogen atoms) and their contribution toward hydrophobicity have been identified as major responsible structural attributes for higher toxicity from the developed in silico models. The present approaches can provide rich information in the context of virtual screening of relevant chemical libraries for aquatic toxicity prediction.

Original languageEnglish
Pages (from-to)17648-17657
Number of pages10
JournalIndustrial and Engineering Chemistry Research
Volume52
Issue number49
DOIs
StatePublished - 11 Dec 2013

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