Abstract
Recommendations on the efficient application of CORAL software (http://www.insilico.eu/coral) to establish quantitative structure-property/activity relationships (QSPRs/QSARs) are provided. The predictive potential of the approach has been demonstrated for QSAR models developed for inhibitor concentrations (negative decimal logarithm of IC50) of derivatives of N-methyl-d-aspartate (NMDA) receptor, leucine-rich repeat kinase 2 (LRRK2), and tropomyosin receptor kinase A (TrkA). The above three protein targets are related to various neurodegenerative diseases such as Alzheimer's and Parkinson's. Each model was checked using several splits of the data for the training and the validation sets. The index of ideality of correlation (IIC) represents a tool to improve the predictive potential for an arbitrary model. However, the use of the IIC should be carried out according to rules, described in this work.
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