Isolation and identification in human blood serum of the proteins possessing the ability to bind with 48 kDa form of unconventional myosin 1c and their possible diagnostic and prognostic value.
Marina StarykovychVolodymyr AntonyukTetyana NehrychNazar NegrychDaniel HorákSerhiy SouchelnytskyiOleg KitRostyslav StoikaYuriy KitPublished in: Biomedical chromatography : BMC (2020)
We firstly identified 48 kDa molecular form of the unconventional myosin 1c (p48/Myo1C), and isolated it from blood serum of multiple sclerosis patients. The amount of p48/Myo1C in human blood serum correlated with some autoimmune, hemato-oncological and neurodegenerative diseases and thus may serve as a potential molecular biomarker. The biological functions of this protein in human blood remain unknown. Previously, we used the monodisperse magnetic poly (glycidyl methacrylate)(mag-PGMA-NH2 ) microspheres with immobilized 48/Myo1C and western-blot analysis, which allowed us to identify IgM and IgG immunoglobulins presenting an affinity to this protein. Here, we used mass spectrometry followed by the western blotting in order to identify other blood serum proteins with affinity to 48/Myo1C. The obtained data demonstrate that 48/Myo1C binds to component 3 of the complement and the antithrombin-III proteins. A combination of magnetic microparticle-based affinity chromatography with MALDI-TOF mass spectrometry and an in silico analysis provided an opportunity to identify the partners of interaction of 48/Myo1C with other proteins, in particular those participating in complement and coagulation cascades.
Keyphrases
- mass spectrometry
- capillary electrophoresis
- endothelial cells
- multiple sclerosis
- liquid chromatography
- induced pluripotent stem cells
- binding protein
- end stage renal disease
- high performance liquid chromatography
- high resolution
- gas chromatography
- molecularly imprinted
- prostate cancer
- ejection fraction
- south africa
- chronic kidney disease
- newly diagnosed
- heat shock protein
- machine learning
- prognostic factors
- electronic health record
- rectal cancer
- molecular docking
- single molecule
- molecular dynamics simulations
- big data
- small molecule
- magnetic nanoparticles