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基于模糊油滴模型的功能位点预测

Prediction of functional sites based on the fuzzy oil drop model.

作者信息

Bryliński Michał, Prymula Katarzyna, Jurkowski Wiktor, Kochańczyk Marek, Stawowczyk Ewa, Konieczny Leszek, Roterman Irena

机构信息

Department of Bioinformatics and Telemedicine, Jagiellonian University-Collegium Medicum, Kraków, Poland.

出版信息

PLoS Comput Biol. 2007 May;3(5):e94. doi: 10.1371/journal.pcbi.0030094. Epub 2007 Apr 12.

Abstract

A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localization of active sites in proteins. This paper describes a computational model that can be used to identify potential areas that are able to interact with other molecules (ligands, substrates, inhibitors, etc.). The model for active site recognition is based on the analysis of hydrophobicity distribution in protein molecules. It is shown, based on the analyses of proteins with known biological activity and of proteins of unknown function, that the region of significantly irregular hydrophobicity distribution in proteins appears to be function related.

摘要

对许多生物过程的描述需要了解蛋白质的三维结构,特别是负责生物功能的特定活性位点。许多蛋白质,其基因已通过人类基因组测序得以鉴定,并已通过实验合成,但其生物活性仍有待确定。目前使用的方法并不总是能产生令人满意的结果,因此需要开发新的算法来识别蛋白质中活性位点的定位。本文描述了一种计算模型,可用于识别能够与其他分子(配体、底物、抑制剂等)相互作用的潜在区域。活性位点识别模型基于对蛋白质分子中疏水性分布的分析。基于对具有已知生物活性的蛋白质和功能未知的蛋白质的分析表明,蛋白质中疏水性分布明显不规则的区域似乎与功能相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e310/1876487/ae2356ffa5c3/pcbi.0030094.g001.jpg

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