利用基因本体工具预测微管蛋白的抗微管靶蛋白及其相互作用蛋白。

IF 3.6 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Journal, genetic engineering & biotechnology Pub Date : 2023-07-19 DOI:10.1186/s43141-023-00531-8
Polani B Ramesh Babu
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引用次数: 0

摘要

背景:微管蛋白是高度保守的球状蛋白,在细胞周期中参与细胞骨架微管的稳定。微管蛋白的不同亚型在不同的细胞类型中有不同的表达,它们的蛋白-蛋白相互作用(PPIs)分析将有助于确定治疗癌症和神经系统疾病的抗微管药物靶点。最近有许多基于网络的PPIs分析方法被使用,在本文中,我使用基因本体(Gene Ontology, GO)工具,如Stringbase、ProteomeHD、GeneMANIA和ShinyGO,通过选择微管蛋白的强相互作用蛋白来鉴定抗微管靶蛋白。结果:我使用了6种不同的人微管蛋白亚型(α-、β-和γ-微管蛋白各2种),发现了数千种节点间蛋白质相互作用(GeneMANIA中最高4956种),并选择了得分最高的前10种强相互作用的节点间相互作用,其中7种微管蛋白家族蛋白和6种非微管蛋白家族蛋白(共13种)。功能富集分析表明,这13种蛋白在成核、微管聚合或解聚、膜系结和对接、背根神经节发育、有丝分裂周期和细胞骨架组织中发挥重要作用。我发现已知γ-微管蛋白(TUBG1, TUBGCP4和TUBBGCP6)主要参与微管蛋白相关功能,其次是α-微管蛋白(TUBA1A)和β-微管蛋白(TUBB和TUBB3)。在PPI结果中,我发现了几种与微管蛋白相互作用的非管状蛋白,其中6种(HTT、DPYSL2、SKI、UNC5C、NINL和DDX41)与其功能密切相关。结论:越来越多的调节蛋白和微管蛋白亚群被报道,但对它们与微管组装和拆卸的关系知之甚少。利用最新的氧化石墨烯工具对微管蛋白异构体进行功能富集分析,鉴定出在微管功能中起关键作用的γ-微管蛋白,并观察到非微管蛋白家族的HTT、DPYSL2、SKI、UNC5C、NINL和DDX41等与微管蛋白有强相互作用的功能蛋白。目前的研究产生了一个有前途的模型系统,使用氧化石墨烯工具来缩小微管蛋白相关蛋白作为癌症、阿尔茨海默氏症、神经系统疾病等药物靶点的范围。
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Prediction of anti-microtubular target proteins of tubulins and their interacting proteins using Gene Ontology tools.

Background: Tubulins are highly conserved globular proteins involved in stabilization of cellular cytoskeletal microtubules during cell cycle. Different isoforms of tubulins are differentially expressed in various cell types, and their protein-protein interactions (PPIs) analysis will help in identifying the anti-microtubular drug targets for cancer and neurological disorders. Numerous web-based PPIs analysis methods are recently being used, and in this paper, I used Gene Ontology (GO) tools, e.g., Stringbase, ProteomeHD, GeneMANIA, and ShinyGO, to identify anti-microtubular target proteins by selecting strongly interacting proteins of tubulins.

Results: I used 6 different human tubulin isoforms (two from each of α-, β-, and γ-tubulin) and found several thousands of node-to-node protein interactions (highest 4956 in GeneMANIA) and selected top 10 strongly interacting node-to-node interactions with highest score, which included 7 tubulin family protein and 6 non-tubulin family proteins (total 13). Functional enrichment analysis indicated a significant role of these 13 proteins in nucleation, polymerization or depolymerization of microtubules, membrane tethering and docking, dorsal root ganglion development, mitotic cycle, and cytoskeletal organization. I found γ-tubulins (TUBG1, TUBGCP4, and TUBBGCP6) were known to contribute majorly for tubulin-associated functions followed by α-tubulin (TUBA1A) and β-tubulins (TUBB AND TUBB3). In PPI results, I found several non-tubular proteins interacting with tubulins, and six of them (HTT, DPYSL2, SKI, UNC5C, NINL, and DDX41) were found closely associated with their functions.

Conclusions: Increasing number of regulatory proteins and subpopulation of tubulin proteins are being reported with poor understanding in their association with microtubule assembly and disassembly. The functional enrichment analysis of tubulin isoforms using recent GO tools resulted in identification of γ-tubulins playing a key role in microtubule functions and observed non-tubulin family of proteins HTT, DPYSL2, SKI, UNC5C, NINL, and DDX41 strongly interacting functional proteins of tubulins. The present study yields a promising model system using GO tools to narrow down tubulin-associated proteins as a drug target in cancer, Alzheimer's, neurological disorders, etc.

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