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One hundred and sixty-five pairs of protein structural files were collected and BLASTP was then utilized to compare their similarities. The spherical polar coordinate was established. The radius of the sphere,the azimuth and elevation were bisected and trisected,respectively,so the protein was divided into 8 and 27 blocks which were similar to spherical shell fragments. On this basis,the similarity of 12 parameters was calculated using MATLAB. The full regression model,stepwise regression model and filter regression model between the total similarity and the similarity of 12 parameters when they were bisected and trisected were established using SPSS. The BP neural network model was established using MATLAB for comparison. According to the results of stepwise regression model,similarity of the atomic number,similarity of C and N atomic number,similarity of P and S position and density had the most significant correlation with the overall similarity. Results of bisection were much better when compared with that of trisection,and stepwise regression model had the best results.
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Basic Information:
DOI：10.13705/j.issn.1671-6841.2015211
China Classification Code:Q51
Citation Information:
[1]ZHANG Pingping,ZHANG Jianhua,YIN Mimi ,et al.Establishing Algorithm Model of the Protein Spatial Structure Similarity Based on Multi-parameter[J].Journal of Zhengzhou University(Natural Science Edition),2016,48(02):105-109.DOI:10.13705/j.issn.1671-6841.2015211.
Fund Information:
国家自然科学青年基金资助项目(813D3150);; 中国中医药行业科研专项基金资助项目(201007001)
2016-06-23
2016-06-23
2016-06-23