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Quasi-SMILES for Nano-QSAR Prediction of Toxic Effect of Al2O3 Nanoparticles
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Author(s): Alla P. Toropova (IRCCS, Istituto di Ricerche Farmacologiche Mario Negri, Italy), P. Ganga Raju Achary (Institute of Technical Education and Research (ITER), Siksha ‘O'Anusandhan University, India)and Andrey A. Toropov (IRCCS, Istituto di Ricerche Farmacologiche Mario Negri, Italy)
Copyright: 2017
Pages: 12
Source title:
Materials Science and Engineering: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1798-6.ch066
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Abstract
The level of malondialdehyde (MDA) in wet tissue of different organs is utilized as a measure of toxic effect. The numerical data on the concentration of MDA in wet tissue of liver, kidneys, brain, and heart of rat is examined as the endpoint which are impacted by different dose (mg/kg), exposure time (3 and 14 days) and single oral treatment of aluminium nano-oxide (Al2O3) with 30 nm or 40 nm. An attempt to develop predictive model for this endpoint has been carried out in this work. SMILES is a traditional tool to represent molecular structure for QSPRs/QSARs. In contrast to traditional SMILES, so-called quasi-SMILES can be a tool to build up quantitative features – property / activity relationships (QFPRs/QFARs) for endpoints which are not defined by solely molecular structure, but by a group of physicochemical and/or biochemical conditions. The quasi-SMILES is the representation of the above eclectic conditions whereas the QFPR/QFAR are models of endpoints which are modified under impacts of these eclectic conditions.
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