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从分子表面数据库eF-site中识别蛋白质功能。

Identification of protein functions from a molecular surface database, eF-site.

作者信息

Kinoshita Kengo, Furui Jun'ichi, Nakamura Haruki

机构信息

Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan.

出版信息

J Struct Funct Genomics. 2002;2(1):9-22. doi: 10.1023/a:1011318527094.

Abstract

A bioinformatics method was developed to identify the protein surface around the functional site and to estimate the biochemical function, using a newly constructed molecular surface database named the eF-site (electrostatic surface of Functional site. Molecular surfaces of protein molecules were computed based on the atom coordinates, and the eF-site database was prepared by adding the physical properties on the constructed molecular surfaces. The electrostatic potential on each molecular surface was individually calculated solving the Poisson-Boltzmann equation numerically for the precise continuum model, and the hydrophobicity information of each residue was also included. The eF-site database is accessed by the internet (http://pi.protein.osaka-u.ac.jp/eF-site/). We have prepared four different databases, eF-site/antibody, eF-site/prosite, eF-site/P-site, and eF-site/ActiveSite, corresponding to the antigen binding sites of antibodies with the same orientations, the molecular surfaces for the individual motifs in PROSITE database, the phosphate binding sites, and the active site surfaces for the representatives of the individual protein family, respectively. An algorithm using the clique detection method as an applied graph theory was developed to search of the eF-site database, so as to recognize and discriminate the characteristic molecular surfaces of the proteins. The method identifies the active site having the similar function to those of the known proteins.

摘要

开发了一种生物信息学方法,用于识别功能位点周围的蛋白质表面并估计其生化功能,该方法使用一个新构建的名为eF-site(功能位点静电表面)的分子表面数据库。基于原子坐标计算蛋白质分子的分子表面,并通过在构建的分子表面上添加物理性质来制备eF-site数据库。针对精确的连续介质模型,通过数值求解泊松-玻尔兹曼方程分别计算每个分子表面上的静电势,并且还包括每个残基的疏水性信息。可通过互联网(http://pi.protein.osaka-u.ac.jp/eF-site/)访问eF-site数据库。我们已经制备了四个不同的数据库,即eF-site/抗体、eF-site/Prosite、eF-site/P位点和eF-site/活性位点,它们分别对应具有相同取向的抗体的抗原结合位点、Prosite数据库中各个基序的分子表面、磷酸结合位点以及各个蛋白质家族代表的活性位点表面。开发了一种使用团检测方法作为应用图论的算法来搜索eF-site数据库,以便识别和区分蛋白质的特征分子表面。该方法识别出具有与已知蛋白质相似功能的活性位点。

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