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BP和概率神经网络预测微生物热稳定性的比较
  • 期刊名称:江南大学学报(人文社会科学版)
  • 时间:2012
  • 页码:637-641
  • 分类:Q81[生物学—生物工程] TP391[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]江南大学数字媒体学院,江苏 无锡 214122, [2]江南大学物联网工程学院,江苏 无锡 214122
  • 相关基金:国家自然科学基金资助项目(No.21001053)
  • 相关项目:铁超氧化物歧化酶热稳定性的关键因素研究
中文摘要:

蛋白质结构的鲁棒性能够提高蛋白质在不稳定环境中保持生物功能的能力。用氨基酸网络表示超氧化物歧化酶(Fe-SOD)的结构,从研究氨基酸网络鲁棒性的角度研究Fe-SOD结构的鲁棒性。实验结果显示,氨基酸网络的鲁棒性比同等规模大小的随机网络的鲁棒性差。尤其以介数方式攻击,Fe-SOD氨基酸网络表现出明显的脆弱性。嗜热的Fe-SOD氨基酸网络的鲁棒性比常温的氨基酸网络的鲁棒性高。通过鲁棒性分析,识别氨基酸网络中关键残基,发现关键残基主要包括进化保守残基、疏水性残基、规则二级结构内部的残基以及Fe-SOD活性位点残基。与热稳定性低的Fe-SOD氨基酸网络相比,热稳定性高的Fe-SOD氨基酸网络中的关键残基较均匀地分布在Fe-SOD内部。关键残基在Fe-SOD结构中均匀分布,有利于提高嗜热Fe-SOD整体的稳定性。

英文摘要:

The robustness of protein structure can improve protein biological activity in unstable environment. In this paper, we use amino acid networks to describe iron superoxide dismutase (Fe-SOD) structure. Analysis of Fe-SOD structure robustness from the perspective of Fe-SOD amino acid networks robustness, we observed that the robustness of Fe-SOD amino acid network is worse than random network with the same scale. Especially, under betweenness attack, Fe-SOD amino acid networks show obvious vulnerability. Thermophilic Fe-SOD amino acid networks have better robustness than mesophilic Fe-SOD amino acid networks. Moreover, analysis of Fe-SOD amino acid network robustness, we identified key residues of Fe-SOD amino acid networks. These key residues mainly consist of conserved residues, hydrophobic residues, residues in regular secondary structures and Fe-SOD activity site residues. The comparison of key residues distribution in different thermal stability Fe-SOD, we found that key residues are more uniform distribution in thermophilic Fe-SOD. The uniform distribution of key residues, can improve the overall robustness of Fe-SOD.

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