QSTR with Extended Topochemical Atom Indices. 10. Modeling of Toxicity of Organic Chemicals to Humans Using Different Chemometric Tools

Abstract

In this communication, we have developed quantitative predictive models using human lethal concentration values of 26 organic compounds including some pharmaceuticals with extended topochemical atom (ETA) indices applying different chemometric tools and compared the extended topochemical atom models with the models developed from non-extended topochemical atom ones. Extended topochemical atom descriptors were also tried in combination with non-extended topochemical atom descriptors to develop better predictive models. The use of extended topochemical atom descriptors along with non-extended topochemical atom ones improved equation statistics and cross-validation quality. The best model with sound statistical quality was developed from partial least squares regression using extended topochemical atom descriptors in combination non-extended topochemical atom ones. Finally, to check true predictability of the ETA parameters, the data set was divided into training (n = 19) and test (n = 7) sets. Partial least squares and genetic partial least squares models were developed from the training set using extended topochemical atom indices and the models were validated using the test set. The extended topochemical atom models developed from different statistical tools suggest that the toxicity increases with bulk, chloro functionality, presence of electronegative atoms within a chain or ring and unsaturation, and decreases with hydroxy functionality and branching. The results suggest that the extended topochemical atom descriptors are sufficiently rich in chemical information to encode the structural features for QSAR/QSPR/QSTR modeling.

On Two Novel Parameters for Validation of Predictive QSAR Models

“…An alternative measure r m 2 (based on observed and predicted data of the test set compounds) was suggested to be a better metric to indicate external predictability. But it can as well be applied for training set if one considers the correlation between observed and leave-one-out (LOO) predicted values of the training set compounds [ 30 , 31 ]. More interestingly, this can be used for the whole set considering LOO-predicted values for the training set and predicted values of the test set compounds.…”

Least Absolute Shrinkage and Selection Operator-Based Prediction of the Binding Constant of p-Sulfonatocalix[6]/[8]arenes with Alkaloids

“…ETA_AlphaP denoted the sum of alpha values of all nonhydrogen vertices of a molecule relative to molecular size, which described the shape of molecules. 34 MDEC-22 belonged to molecular distance edge; this vector descriptor can more effectively describe the structure and interaction between atoms in a molecular graph. 35 VE3_D was the descriptor describing the topological distance matrix.…”

QSTR with extended topochemical atom (ETA) indices. 14. QSAR modeling of toxicity of aromatic aldehydes to Tetrahymena pyriformis

“…The ETA [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] indices formulated based on modification of TAU descriptors [38][39][40][41][42][43][44][45][46][47][48][49][50], which were developed in the valence electron mobile (VEM) environment, have been used to develop the QSTR models for 40-h T. pyriformis toxicity of 77 aromatic aldehydes. Some basic parameters of the ETA scheme used in the development of QSTR models for the above mentioned dataset have been defined in Supplementary Materials section.…”