Introduction
Chemical proteomics is considered as one of the effective tool for identification proteins that bind specifically to candidate compounds by means of affinity chromatographic column and mass spectrometry technology in drug discovery. Comprehensive, but medium scale chemical proteomics gives insights to chemists as well as biologists, because this contains tremendous information in terms of chemical structures about biological equivalence, binding proteins and their domains, and protein interactions. Here we have developed a new tool to integrate that information.
Methods
A hundred different compounds were immobilized as affinity columns and HCT116 cell lysates were applied onto each column. After the identification, binding amount was estimated by calculating emPAI values. The emPAI values of basal protein expression levels in HCT116 also were obtained, and then ratio between binding emPAI- and basal emPAI-values to each protein was calculated as enrichment factor. We have applied this approach to mice brains for Alzheimer disease research.
Results
To evaluate finger prints of each compound, first we have made a large 2D heat map including over 100 compounds and 17,000 proteins for giving the bird view of results. As feasibility studies, two series of compounds known biological activities and having similar scaffold structures were added in our experiments. After 2D clustering analysis, these compounds were reasonably grouped as separate clusters in chemical dimension. After functional analysis of binding proteins, some of our compounds seemed to be preferable to ATP binding proteins, therefore we extracted protein kinases from binding protein lists and mapped them onto kinome map(Figure). We compared kinase expression between wild and APP/tau transgenic mice brains after kinase enrichments. Then we also did phosphoproteome analysis between these brains to identify substrates of Alzheimer disease specific kinases.
