Bahramali Golnaz, Goliaei Bahram, Minuchehr Zarrin, Marashi Sayed-Amir
Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Department of Systems Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.
Amino Acids. 2017 Feb;49(2):303-315. doi: 10.1007/s00726-016-2361-6. Epub 2016 Nov 24.
Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.
变色龙蛋白是一类包含特定序列的蛋白质,这些序列能够形成α-螺旋-β-链(HE-变色龙)、α-螺旋-卷曲(HC-变色龙)或β-链-卷曲(CE-变色龙)结构,以发挥其关键的生物学功能。在本研究中,我们采用基于网络的方法对变色龙蛋白进行研究,以更深入地了解这些蛋白质。我们聚焦于不同蛋白质数据银行(PDB)条目中具有相同且长度大于或等于七个残基的变色龙序列的蛋白质,这些蛋白质在同一蛋白中采用HE-变色龙、HC-变色龙和CE-变色龙结构。通过我们内部的程序鉴定出了191种人类变色龙蛋白。然后,我们对所得数据集进行了蛋白质-蛋白质相互作用(PPI)网络、基因本体(GO)富集、疾病网络和通路富集分析。我们发现,存在一些变色龙序列位于对两种蛋白质的双重功能至关重要的蛋白质-蛋白质相互作用区域。对变色龙蛋白的PPI网络分析引入了五个枢纽蛋白,即TP53、表皮生长因子受体(EGFR)、热休克蛋白90α家族成员1(HSP90AA1)、过氧化物酶体增殖物激活受体α(PPARA)和缺氧诱导因子1α(HIF1A),它们出现在四个PPI簇中。结果表明,变色龙区域位于这些蛋白质的关键结构域中,对人类癌症的发生发展和治疗具有重要意义。本报告是首次使用计算方法对变色龙蛋白进行基于网络的功能研究,可能为理解疾病机制提供新的视角,有助于我们开发新的医学疗法,并发现具有变色龙特性的新蛋白质,这些蛋白质在癌症研究中具有高度重要性。