a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

binary logistic regression (blr) has been developed as non-linear models to establish quantitative structure- activity relationships (qsar) between structural descriptors and biochemical activity of carbonic anhydrase inhibitors. using a training set consisted of 21 compounds with known ki values, the model was trained and tested to solve two-class problems as active or inactive on the basis of...

It is important to determine whether a candidate molecule is capable of penetrating the plasma-brain barrier indrug discovery and development. The aim of this paper is to establish a predictive model for plasma-brainbarrier penetration using simple descriptors The usefulness of the quantum chemical descriptors, calculated atthe level of the DFT and HE theories using 6-310* basis set for QSAR st...

In this work, quantitative structure-property relationship (QSPR) approaches were used to predict the redox potential of 42 phenolic antioxidants. The structures of all compounds optimized by the AM1 semi-empirical method and then a large number of molecular descriptors were calculated for each compound in the data set. Subsequently, stepwise multilinear regression was applied to select the mos...