| 引用本文: | 李彩艳,马勇,邢俊凤,郭国栋,武一凡,闻昊坤,丁海麦,张改梅.基于氨基酸组分和位点保守信息识别蛋白质HEME结合残基[J].生物信息学,2022,20(3):189-194. |
| LI Caiyan,MA Yong,XING Junfeng,GUO Guodong,WU Yifan,WEN Haokun,DING Haimai,ZHANG Gaimei.Identification of protein binding residues HEME based on amino acid component and conservative information[J].Chinese Journal of Bioinformatics,2022,20(3):189-194. |
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| 基于氨基酸组分和位点保守信息识别蛋白质HEME结合残基 |
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李彩艳1,马勇1, 邢俊凤1,郭国栋1,武一凡1,闻昊坤1,丁海麦2,张改梅3
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( 1.包头医学院 计算机科学与技术学院,内蒙古 包头 014000; 2.包头医学院 基础与法医学院, 内蒙古 包头 014000; 3.呼和浩特第一医院,呼和浩特 010051 )
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| 摘要: |
| 血红素是一种重要的、常用的配体,在电子传递、催化、信号转导和基因表达等方面发挥着重要作用,准确预测蛋白质与血红素相互作用的结合残基是结构生物信息学的主要挑战之一。本文下载整理了Biolip数据库中HEME配体与蛋白质结合的信息,统计分析了结合残基和非结合残基的氨基酸组分和位点保守性信息并将其作为预测特征参数,用Fisher-PSSM判别法识别HEME结合残基,计算结果表明优化特征参数的Fisher-PSSM判别法得到了较好的预测结果。 |
| 关键词: 蛋白质配体 结合位点 统计分析 血红素HEME |
| DOI：10.12113/202103014 |
| 分类号:Q61 |
| 文献标识码:A |
| 基金项目:内蒙自然科学基金项目(No.2020MS08015);内蒙古大学生创新创业训练计划项目(No.S202119127006,S202119127007). |
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| Identification of protein binding residues HEME based on amino acid component and conservative information |
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LI Caiyan1, MA Yong1, XING Junfeng1, GUO Guodong1, WU Yifan1,WEN Haokun1,DING Haimai2, ZHANG Gaimei3
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(1.School of Computer Science and Technology, Baotou Medical College, Baotou 014000, Inner Mongolia, China; 2.School of Medical School of Foundation, Baotou Medical College, Baotou 014000, Inner Mongolia, China; 3.Hohhot First Hospital, Hohhot 010051, China)
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| Abstract: |
| HEME is an important and commonly used ligand that plays an important role in electron transfer, catalysis, signaling transduction, and gene expression. Accurate prediction of the binding residues of protein-HEME interactions is one of the main challenges in structural bioinformatics. In this study, the information of HEME ligand and protein was downloaded from Biolip database, and amino acid components and site conservative information of binding residues were and nonbinding residues were satistically analyzed and used as prediction characteristic parameters. HEME binding residues were identified by Fisher-PSSM criterion, and calculation results showed that the Fisher-PSSM criterion of optimizing characteristic parameters had good prediction results. |
| Key words: Protein ligand Binding site Statistical analysis HEME |
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