SMILES-based QSAR Approaches for Carcinogenicity and Anticancer Activity: Comparison of Correlation Weights for Identical SMILES Attributes

Title: SMILES-based QSAR Approaches for Carcinogenicity and Anticancer Activity: Comparison of Correlation Weights for Identical SMILES Attributes

Volume: 11 Issue: 10

Author(s): Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Giuseppina Gini, Danuta Leszczynska and Jerzy Leszczynski

Affiliation:

Keywords: artificial neural networks, anticancer activity, threshold, Carcinogenicity, QSAR, SMILES, Validation, CORAL software

Abstract: CORAL software (http://www.insilico.eu/coral/) has been used for modeling of carcinogenicity (logTD50) of 401 compounds, and anticancer activity (-logIC50) of 100 compounds, on the basis of quantitative structure – activity relationships (QSAR). The simplified molecular input line entry system (SMILES) was used for the representation of the molecular structures. A new additional global invariant of the molecular structure was tested. This is an indicator of the presence of pairs of chemical elements (F, Cl, Br, N, O, S, and P). Three random splits into sub-training, calibration, and test set were examined. Molecular features (calculated with SMILES and statistically significant), which increase the anticancer activity have been identified: their presence in the molecular structure could be helpful criterion in the search for new anticancer agents.

Cite this article as:

A. Toropov Andrey, P. Toropova Alla, Benfenati Emilio, Gini Giuseppina, Leszczynska Danuta and Leszczynski Jerzy, SMILES-based QSAR Approaches for Carcinogenicity and Anticancer Activity: Comparison of Correlation Weights for Identical SMILES Attributes, Anti-Cancer Agents in Medicinal Chemistry 2011; 11 (10) . https://dx.doi.org/10.2174/187152011797927625