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基于计算机建模的抗真菌靶点鉴定

Identification of Antifungal Targets Based on Computer Modeling.

作者信息

Bencurova Elena, Gupta Shishir K, Sarukhanyan Edita, Dandekar Thomas

机构信息

Department of Bioinformatics, Am Hubland, Biozentrum, University of Würzburg, 97074 Würzburg, Germany.

BioComputing Unit, EMBL Heidelberg, 69117 Heidelberg, Germany.

出版信息

J Fungi (Basel). 2018 Jul 4;4(3):81. doi: 10.3390/jof4030081.

Abstract

is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host⁻pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.

摘要

是一种腐生的、分布广泛的真菌,会侵袭免疫系统薄弱的患者。对抗真菌感染的合理解决方案旨在操纵真菌代谢或阻断其生存所必需的酶。在此,我们讨论并比较不同的生物信息学方法,以分析针对真菌独特途径的可能靶向策略。例如,系统发育分析可揭示真菌靶点,而结构域分析能让我们发现宿主与真菌在蛋白质组成上的细微差异。此外,通过查看直系同源物并利用宿主 - 病原体相互作用数据库中的信息,可以系统地比较宿主与真菌之间的蛋白质网络。更多数据,如三维结构知识、基因表达数据或计算出的代谢通量信息,可优化搜索并迅速聚焦于抗真菌药物的最佳靶点。我们分析了几个适用于基于结构的药物设计的最佳靶点。最后,我们讨论了应用生物信息学工具识别独特真菌途径和蛋白质靶点时的一般优势和局限性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebea/6162656/54c9fe539de9/jof-04-00081-g001.jpg

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