MAPanalyzer: a novel online tool for analyzing microtubule-associated proteins.
Bottom Line: In the database, a core MAP dataset, which is fully manually curated from the literature, is further enriched by MAP information collected via automated pipeline.The core dataset, on the other hand, enables the building of a novel MAP predictor which combines specialized machine learning classifiers and the BLAST homology searching tool.Benchmarks on the curated testing dataset and the Arabidopsis thaliana whole genome dataset have shown that the proposed predictor outperforms not only its own components (i.e. the machine learning classifiers and BLAST), but also another popular homology searching tool, PSI-BLAST.
Affiliation: State Key Laboratory of Agrobiotechnology and.Show MeSH
Related in: MedlinePlus
Mentions: Based on literature reading, a dataset of 611 microtubule-related proteins (MRPs) has been collected. This dataset contains four types of MRPs: (i) MAPs, that is, the proteins which directly bind microtubules or tubulins; (ii) Proteins whose gene perturbations induce the alteration of microtubule organization and dynamics in vivo (i.e. proteins with microtubule phenotype); (iii) Proteins that colocalize with microtubules and (iv) Proteins indirectly interacting with microtubules, including proteins that interact with a known MAP or presented in the tubulin-containing purification compartment. The MAPs constitute the largest proportion of the core dataset (310 in total; Figure 1A). Among these 310 MAPs, 209 are capable to bind microtubules, 91 bind tubulins, while the remaining 10 interact with EB1 (the core component of microtubule plus end). In terms of experimental evidence, the microtubule cosedimentation assay ranks the top as the standard MAP identification procedure (supporting 54.5% MAPs), followed by popular PPI assays such as coimmunoprecipitation (CoIP), pull down and yeast two hybrid.Figure 1.