New QSPR/QSAR Models for Organic and Inorganic Compounds: Similarity and Dissimilarity - Alla P. Toropova; Andrey A. Toropov; Alessandra Roncaglioni; Emilio Benfenati (Inorganics)
Background: We studied in silico models of both organic and inorganic substances. In most cases, these in silico models are used for organic substances only. The following endpoints were taken for the case studies: the octanol–water coefficient (three models), the enthalpies of formation of organometallic compounds, and rat acute toxicity. Methods: The correlation weights were optimized using the Monte Carlo method with two special training and validation sets. The training set was structured into three subsets of active and passive training, as well as a calibration set. The division into these four subsets was carried out using the Las Vegas algorithm. It is assumed that considering groups of different splits into these four subsets is more informative than considering only a single split. Results: Models were built for the octanol–water coefficient for a set containing organic and inorganic substances or for a subset of the original data; other models were developed for a set containing only specially defined inorganic substances for platinum complexes. In addition, models of the enthalpy of formation and for toxicity in rats were built using the same approach for two sets of inorganic substances. Conclusions: A comparison of different methods for the optimization of correlation weights using the Monte Carlo method showed that optimization can be improved using the coefficient of conformism of a correlative prediction (CCCP) or the index of the ideality of correlation (IIC). Optimization with CCCP was the best option for the models of the octanol–water partition coefficient for the set of organic compounds, the octanol–water partition coefficient of the inorganic set, and the enthalpy of formation of the inorganic compounds. However, optimization with IIC was the best option in terms of the toxicity of the inorganic compounds in rats.