Application of multivariate image analysis in QSPR study of pKa of various acids by principal components-least squares support vector machine was written by Veyseh, Somayeh;Hamzehali, Hamideh;Niazi, Ali;Ghasemi, Jahan B.. And the article was included in Journal of the Chilean Chemical Society in 2015.Name: Pyridinehydrochloride This article mentions the following:
A new implemented quant. structure-property relationships (QSPR) method, whose descriptors achieved from bidimensional images, was suggested for the predicting of acidity constant (pKa) of various acid. The resulted descriptors were subjected to principal component anal. (PCA) and the most significant principal components (PCs) were extracted Multivariate image anal. applied to QSPR modeling was done by means of principal component-least squares support vector machine (PC-LSSVM) methods. The resulted model showed high prediction ability with root mean square error of prediction of 0.0195 for PC-LSSVM. In the experiment, the researchers used many compounds, for example, Pyridinehydrochloride (cas: 628-13-7Name: Pyridinehydrochloride).
Pyridinehydrochloride (cas: 628-13-7) belongs to pyridine derivatives. Pyridine is diamagnetic and has a diamagnetic susceptibility of −48.7 × 10−6 cm3·mol−1.The molecular electric dipole moment is 2.2 debyes. The standard enthalpy of formation is 100.2 kJ·mol−1 in the liquid phase and 140.4 kJ·mol−1 in the gas phase. Many analogues of pyridine are known where N is replaced by other heteroatoms . Substitution of one C–H in pyridine with a second N gives rise to the diazine heterocycles (C4H4N2), with the names pyridazine, pyrimidine, and pyrazine.Name: Pyridinehydrochloride