Literature DB >> 15293545

QSARS for toxicity to the bacterium Sinorhizobium meliloti.

I Lessigiarska1, M T D Cronin, A P Worth, J C Dearden, T I Netzeva.   

Abstract

In the present study, structure-activity relationship (QSAR) models for the prediction of the toxicity to the bacterium Sinorhizobium meliloti have been developed, based on a data set of 140 compounds. The data set is highly heterogeneous both in terms of chemistry and mechanisms of toxic action. For deriving QSARs, chemicals were divided into groups according to mechanism of action and chemical structure. The QSARs derived are considered to be of moderate statistical quality. A baseline effect (relationship between the toxicity and logP), which can be related to non-polar narcosis, was observed. To explain toxicity greater than the baseline toxicity, other structural descriptors were used. The development of models for non-polar and polar narcosis had some success. It appeared that the toxicity of compounds acting by more specific mechanisms of toxic action is difficult to predict. A global QSAR was also developed, which had square of the correlation coefficient r2 = 0.53. A QSAR with reasonable statistical parameters was developed for the aliphatic compounds in the data set (r2 = 0.83). QSARs could not be obtained for the aromatic compounds as a group.

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Year:  2004        PMID: 15293545     DOI: 10.1080/10629360410001697771

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  2 in total

1.  Prediction of toxicity using a novel RBF neural network training methodology.

Authors:  Georgia Melagraki; Antreas Afantitis; Kalliopi Makridima; Haralambos Sarimveis; Olga Igglessi-Markopoulou
Journal:  J Mol Model       Date:  2005-11-08       Impact factor: 1.810

2.  MOA-based linear and nonlinear QSAR models for predicting the toxicity of organic chemicals to Vibrio fischeri.

Authors:  Shengnan Zhang; Ning Wang; Limin Su; Xiaoyan Xu; Chao Li; Weichao Qin; Yuanhui Zhao
Journal:  Environ Sci Pollut Res Int       Date:  2020-01-08       Impact factor: 4.223

  2 in total

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