Literature DB >> 11813806

Quantitative structure-activity relationships based on functional and structural characteristics of organic compounds.

S A Kulkarni1, D V Raje, T Chakrabarti.   

Abstract

In the present quantitative structure-activity relationship (QSAR) modeling, organic compounds, including priority pollutants, have been considered and classified based on their functional and structural characteristics. Five physico-chemical characteristics have been used to develop a QSAR model for Pimephales promelas, by means of multiple regression analysis. Collinearity diagnostics was carried out using two different approaches based on condition index and K correlation index. The outlier analysis was carried out using the variable subsets obtained through both the approaches. An attempt has been made to justify the deletion of outliers in each group referring to their physico-chemical characteristics. The expressions obtained by using both approaches provide almost the same prediction accuracy, however, the latter approach resulted in expressions with reduced number of molecular descriptors. The QSARs obtained through this exercise would certainly assist in designing environment-friendly molecules with lower toxicity.

Entities:  

Mesh:

Substances:

Year:  2001        PMID: 11813806     DOI: 10.1080/10629360108039835

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


  2 in total

1.  In silico prediction of pesticide aquatic toxicity with chemical category approaches.

Authors:  Fuxing Li; Defang Fan; Hao Wang; Hongbin Yang; Weihua Li; Yun Tang; Guixia Liu
Journal:  Toxicol Res (Camb)       Date:  2017-07-31       Impact factor: 3.524

2.  Modeling the toxicity of chemical pesticides in multiple test species using local and global QSTR approaches.

Authors:  Nikita Basant; Shikha Gupta; Kunwar P Singh
Journal:  Toxicol Res (Camb)       Date:  2015-12-10       Impact factor: 3.524

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.