Prediction of anti-microtubular target proteins of tubulins and their interacting proteins using Gene Ontology tools

Abstract

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.