Literature DB >> 16996653

QSAR analysis of tyrosine kinase inhibitor using modified ant colony optimization and multiple linear regression.

Wei-min Shi1, Qi Shen, Wei Kong, Bao-xian Ye.   

Abstract

Quantitative structure-activity relationship (QSAR) models of inhibiting action of some analogues of 4-(3-bromoanilino)-6,7-dimethoxyquinazoline on epidermal growth factor receptor tyrosine kinase were constructed using modified ant colony optimization (ACO) method. As a comparison to this method, the evolutionary algorithm (EA) was also tested. It has been demonstrated that the modified ACO is a useful tool for variable selection comparable to EA. In the selected descriptors, electronic descriptor sigma(Y)(-) is the most important descriptor in predicting EGFR inhibitory activity. Electron-donating groups such as Y-substituents enhance the activity as evident by negative sigma(Y)(-). In addition, for quinazoline substituents, nitro group has a large deactivating effect.

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Year:  2006        PMID: 16996653     DOI: 10.1016/j.ejmech.2006.08.001

Source DB:  PubMed          Journal:  Eur J Med Chem        ISSN: 0223-5234            Impact factor:   6.514


  2 in total

1.  Prediction of inhibitory activity of epidermal growth factor receptor inhibitors using grid search-projection pursuit regression method.

Authors:  Hongying Du; Zhide Hu; Andrea Bazzoli; Yang Zhang
Journal:  PLoS One       Date:  2011-07-21       Impact factor: 3.240

2.  Shuffling multivariate adaptive regression splines and adaptive neuro-fuzzy inference system as tools for QSAR study of SARS inhibitors.

Authors:  M Jalali-Heravi; M Asadollahi-Baboli; A Mani-Varnosfaderani
Journal:  J Pharm Biomed Anal       Date:  2009-07-14       Impact factor: 3.935

  2 in total

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