关于稳定蛋白复合物的互连:在酿酒酵母和智人网络中的复合物中心及其保护

Q4 Health Professions
C. Guerra
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引用次数: 0

摘要

蛋白质复合物是执行各种基本细胞功能的关键分子实体。复合物内蛋白质的连通性已经通过实验和计算技术得到了广泛的研究。我们开发了一种计算方法来识别和表征在相互连接复合物中起作用的蛋白质。我们基于连接不同复合物中蛋白质的不相交路径,计算了复合物间中心性的度量,即十字路口指数,并将复合物间枢纽确定为具有高十字路口指数值的蛋白质。我们将该方法应用于酿酒酵母和智人中的一组稳定复合物。正如对集线器所做的那样,我们评估了复杂集线器的拓扑和生物学特性,解决了以下问题。复杂枢纽是否趋向于进化保守?十字路口指数和本质是什么关系?我们发现复杂中心与进化保守性和本质性之间存在良好的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks
Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.
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来源期刊
International Journal of Bioinformatics Research and Applications
International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management
CiteScore
0.60
自引率
0.00%
发文量
26
期刊介绍: Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.
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