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Updated: Jun 3, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
coral Software: QSAR for Anticancer Agents
Emilio Benfenati1, Andrey A Toropov, Alla P Toropova
1Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.
Abstract:
CORrelations And Logic (coral at http://www.insilico.eu/coral) is freeware aimed at establishing a quantitative structure - property/activity relationships (QSPR/QSAR). Simplified molecular input line entry system (SMILES) is used to represent the molecular structure. In fact, symbols in SMILES nomenclatures are indicators of the presence of defined molecular fragments. By means of the calculation with Monte Carlo optimization of the so called correlation weights (contributions) for the above-mentioned molecular fragments, one can define optimal SMILES-based descriptors, which are correlated with an endpoint for the training set. The predictability of these descriptors for an external validation set can be estimated. A collection of SMILES-based models of anticancer activity of 1,4-dihydro-4-oxo-1-(2-thiazolyl)-1,8-naphthyridines for different splits into training and validation set which are calculated with the coral are examined and discussed. Good performance has been obtained for three splits: the r(2) ranged between 0.778 and 0.829 for the sub-training set, between 0.828 and 0.933 for the calibration set, and between 0.807 and 0.931 for the validation set.
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