背景:微管蛋白是高度保守的球状蛋白,参与细胞周期过程中细胞骨架微管的稳定。微管蛋白的不同同工型在各种细胞类型中差异表达,和它们的蛋白质-蛋白质相互作用(PPI)分析将有助于确定癌症和神经系统疾病的抗微管药物靶标。最近正在使用许多基于网络的PPI分析方法,在这篇论文中,我用基因本体论(GO)工具,例如,Stringbase,ProteomeHD,遗传狂躁症,还有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同工型(每种α-,β-,和γ-微管蛋白),并发现了数千个节点到节点的蛋白质相互作用(在GeneMANIA中最高4956),并选择了得分最高的前10个强烈相互作用的节点到节点的相互作用,其中包括7个微管蛋白家族蛋白和6个非微管蛋白家族蛋白(共13个)。功能富集分析表明这13种蛋白质在成核中起着重要作用,微管的聚合或解聚,膜系链和对接,背根神经节发育,有丝分裂周期,和细胞骨架组织。我发现已知γ-微管蛋白(TUBG1,TUBGCP4和TUBBGCP6)对微管蛋白相关功能有主要贡献,其次是α-微管蛋白(TUBA1A)和β-微管蛋白(TUBB和TUBB3)。在PPI结果中,我发现了几种非管状蛋白与微管蛋白相互作用,其中六个(HTT,DPYSL2,SKI,UNC5C,NINL,和DDX41)与它们的功能密切相关。
结论:报道了越来越多的调节蛋白和微管蛋白亚群,但对它们与微管组装和拆卸的关联了解不足。使用最近的GO工具对微管蛋白同种型进行功能富集分析,从而鉴定出γ-微管蛋白在微管功能中起关键作用,并观察到非微管蛋白HTT家族,DPYSL2,SKI,UNC5C,NINL,和DDX41与微管蛋白的功能蛋白强烈相互作用。本研究产生了一个有前途的模型系统,使用GO工具缩小微管蛋白相关蛋白作为癌症的药物靶标。老年痴呆症,神经系统疾病,等。
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.