The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application

Author(s): Andrey A. Toropov, Alla P. Toropova, Aleksandar M. Veselinovic, Jovana B. Veselinovic, Karel Nesmerak, Ivan Raska, Pablo R. Duchowicz, Eduardo A. Castro, Valentin O. Kudyshkin, Danuta Leszczynska, Jerzy Leszczynski

Journal Name: Combinatorial Chemistry & High Throughput Screening
Accelerated Technologies for Biotechnology, Bioassays, Medicinal Chemistry and Natural Products Research

Volume 18 , Issue 4 , 2015

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The theoretical predictions of endpoints related to nanomaterials are attractive and more efficient alternatives for their experimental determinations. Such type of calculations for the "usual" substances (i.e. non nanomaterials) can be carried out with molecular graphs. However, in the case of nanomaterials, descriptors traditionally used for the quantitative structure - property/activity relationships (QSPRs/QSARs) do not provide reliable results since the molecular structure of nanomaterials, as a rule, cannot be expressed by the molecular graph. Innovative principles of computational prediction of endpoints related to nanomaterials extracted from available eclectic data (technological attributes, conditions of the synthesis, etc.) are suggested, applied to two different sets of data, and discussed in this work.

Keywords: CORAL software, optimal descriptor, Quasi-QSPR/QSAR.

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Article Details

Year: 2015
Page: [376 - 386]
Pages: 11
DOI: 10.2174/1386207318666150305125044
Price: $65

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