Literature DB >> 17481417

Quantitative structure activity relationship model for predicting the depletion percentage of skin allergic chemical substances of glutathione.

Hongzong Si1, Tao Wang, Kejun Zhang, Yun-Bo Duan, Shuping Yuan, Aiping Fu, Zhide Hu.   

Abstract

A quantitative model was developed to predict the depletion percentage of glutathione (DPG) compounds by gene expression programming (GEP). Each kind of compound was represented by several calculated structural descriptors involving constitutional, topological, geometrical, electrostatic and quantum-chemical features of compounds. The GEP method produced a nonlinear and five-descriptor quantitative model with a mean error and a correlation coefficient of 10.52 and 0.94 for the training set, 22.80 and 0.85 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones, better than those of the heuristic method.

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Year:  2007        PMID: 17481417     DOI: 10.1016/j.aca.2007.03.070

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  3 in total

1.  DG-GL: Differential geometry-based geometric learning of molecular datasets.

Authors:  Duc Duy Nguyen; Guo-Wei Wei
Journal:  Int J Numer Method Biomed Eng       Date:  2019-02-07       Impact factor: 2.747

Review 2.  Current mathematical methods used in QSAR/QSPR studies.

Authors:  Peixun Liu; Wei Long
Journal:  Int J Mol Sci       Date:  2009-04-29       Impact factor: 6.208

3.  Prediction of PKCθ inhibitory activity using the Random Forest Algorithm.

Authors:  Ming Hao; Yan Li; Yonghua Wang; Shuwei Zhang
Journal:  Int J Mol Sci       Date:  2010-09-20       Impact factor: 5.923

  3 in total

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