QSTR with Extended Topochemical Atom Indices. 2. Fish Toxicity of Substituted Benzenes

Abstract

Considering the importance of quantitative structure-toxicity relationship (QSTR) studies in the field of aquatic toxicology from the viewpoint of ecological safety assessment, fish toxicity of various benzene derivatives has been modeled by the multiple regression technique using recently introduced extended topochemical atom (ETA) indices. The toxicity data have also been modeled using other selected topological descriptors and physicochemical variables, and the best ETA model has been compared to the non-ETA ones. Principal component factor analysis was used as the data preprocessing step to reduce the dimensionality of the data matrix and identify the important variables that are devoid of collinearities. All-possible-subsets regression was also applied on the parameters to cross-check the variable selection for the best model. Multiple linear regression analyses show that the best non-ETA model involves 1chi, ALogP98, and LUMO (energy) as predictor variables and the quality of the relation is as follows: n = 92, Q2 = 0.718, Ra2 = 0.730, R2 = 0.738, R = 0.859, F = 82.8 (df 3, 88), s = 0.340. On the other hand, the best ETA model has the following quality: n = 92, Q2 = 0.865, Ra2 = 0.876, R2 = 0.885, R = 0.941, F = 92.6 (df 7, 84), s = 0.230. The ETA relations showed positive contributions of molecular bulk (size), chloro and hydroxy substitutions in the benzene ring, and the simultaneous presence of methyl and nitro substitutions to the toxicity. Further, the presence of fluoro and ether functionality, amino or nitro functionality in an otherwise unsubstituted ring, and nitro functionality that is ortho to a chloro substituent decreases toxicity. An attempt to use non-ETA descriptors along with ETA ones did not improve the quality in comparison to the best ETA model. Interestingly, the ETA model developed presently for the fish toxicity is better than the previously reported models on the same data set. Thus, it appears that ETA descriptors have significant potential in QSAR/QSPR/QSTR studies, which warrants extensive evaluation.

Correlation weighted successive projections algorithm as a novel method for variable selection in QSAR studies: investigation of anti‐HIV activity of HEPT derivatives

“…A frequently used method simply computes models for all possible subset combinations of descriptors [15,16], in which all reasonable subsets of descriptor are modeled and tested. The long necessary computation time is the major problem with this method, since 2 n models (n is the number of descriptors) must be tested.…”

QSTR with Extended Topochemical Atom (ETA) Indices 8.a QSAR for the inhibition of substituted phenols on germination rate of Cucumis sativus using chemometric tools

“…Table 7 shows that the best statistical quality along with prediction statistics with ETA descriptors is found in case of GFA-MLR equation. (1, 5, 9, 13, 17, 21, 25, 29, 33, 7, 41), (2, 6, 10, 14, ..., 34, 38), ..., (4,8,12,16,20,24,28,32,36,40). …”

“…The toxicity data for 82 aliphatic chemicals with an a, b-unsaturated carbonyl substructure was modeled well by 1-octanol/water partition coefficient (logK ow ) in conjunction with the sum of partial charges on the vinylene carbon atoms (q C4 þ q C3 ) and energy of the lowest unoccupied molecular orbital (E lumo ) by Schultz et al [14]. In this back ground, we have recently introduced [15 -21] extended topochemical atom (ETA) indices as an extension of the TAU concept in the valence electron mobile (VEM) environment [22 -33], and modeled different toxicity data (phenol toxicity [15], fish toxicity [16] and nitrobenzene toxicity [17]) to establish the utility of ETA indices in modeling studies. We have also reported modeling of the acute toxicity of 56 phenylsulfonyl carboxylates to V. fischeri using factor analysis and principal component regression analysis [18] and also using Genetic Function Approximation (GFA) [19].…”

Quimioinformática: Uma Introdução

“…As aplicações dos princípios de QSAR/QSPR são várias, de forma que diversas derivações da nomenclatura têm surgido na literatura, como QSRR (quantitative structure-(chromatographic) retention relationships), 152 QNAR (quantitative nanostructure-activity relationships), 153 QSTR (quantitative structure-toxicity relationships), 154 entre outros. [155][156][157] Existem atualmente softwares para elucidação de estruturas químicas através de seus espectros de ressonância magnética nuclear, como ACD/Structure Elucidator Suite (http:// www.acdlabs.com/products/com_iden/elucidation/struc_eluc/).…”