Literature DB >> 11597486

QSAR prediction of toxicity of nitrobenzenes.

V K Agrawal1, P V Khadikar.   

Abstract

A QSAR analysis has been carried out on the toxicities of 40 mono-substituted nitrobenzenes using recently introduced PI and Sz indices, as well as older molecular redundancy (MRI) and Balaban indices (J). The results have shown that no statistically significant mono-parametric QSAR models are possible. Also, that along with PI, Sz, MRI and J indices are the appropriate parameters to be used in developing multiparametric QSAR models. The toxicities of nitrobenzenes are well predicted by a penta-parametric model consisting of PI, Sz, J, MRI and Ip(1) (an indicator parameter taking care of the effect of substitution at 2-position) as the correlating parameters. The predictive ability of the model is determined by a cross-validation method.

Entities:  

Mesh:

Substances:

Year:  2001        PMID: 11597486     DOI: 10.1016/s0968-0896(01)00211-5

Source DB:  PubMed          Journal:  Bioorg Med Chem        ISSN: 0968-0896            Impact factor:   3.641


  6 in total

1.  The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study.

Authors:  Victor E Kuz'min; Eugene N Muratov; Anatoly G Artemenko; Leonid Gorb; Mohammad Qasim; Jerzy Leszczynski
Journal:  J Comput Aided Mol Des       Date:  2008-04-02       Impact factor: 3.686

2.  QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: structural factors and possible modes of action.

Authors:  A G Artemenko; E N Muratov; V E Kuz'min; N N Muratov; E V Varlamova; A V Kuz'mina; L G Gorb; A Golius; F C Hill; J Leszczynski; A Tropsha
Journal:  SAR QSAR Environ Res       Date:  2011-06-30       Impact factor: 3.000

3.  Structure-toxicity relationships of nitroaromatic compounds.

Authors:  Olexandr Isayev; Bakhtiyor Rasulev; Leonid Gorb; Jerzy Leszczynski
Journal:  Mol Divers       Date:  2006-05-19       Impact factor: 2.943

4.  QSAR study of C allosteric binding site of HCV NS5B polymerase inhibitors by support vector machine.

Authors:  Eslam Pourbasheer; Siavash Riahi; Mohammad Reza Ganjali; Parviz Norouzi
Journal:  Mol Divers       Date:  2010-10-08       Impact factor: 2.943

5.  QSAR Study of 17β-HSD3 Inhibitors by Genetic Algorithm-Support Vector Machine as a Target Receptor for the Treatment of Prostate Cancer.

Authors:  Eslam Pourbasheer; Saadat Vahdani; Davood Malekzadeh; Reza Aalizadeh; Amin Ebadi
Journal:  Iran J Pharm Res       Date:  2017       Impact factor: 1.696

6.  Quantitative Structure-Activity Relationship Studies of 4-Imidazolyl- 1,4-dihydropyridines as Calcium Channel Blockers.

Authors:  Farzin Hadizadeh; Saadat Vahdani; Mehrnaz Jafarpour
Journal:  Iran J Basic Med Sci       Date:  2013-08       Impact factor: 2.699

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.