Single-molecule protein sequencing through fingerprinting: computational assessment
Datacite citation style:
Yao, Y. (Yao); Docter, Margreet; Van Ginkel, H.G.T.M (Jetty); de Ridder, D. (Dick); Joo, C. (Chirlmin) (2018): Single-molecule protein sequencing through fingerprinting: computational assessment. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:08a078fc-9d4c-44d1-88c9-9cb412b83a46Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.
- 2018-01-19 first online, published, posted
formatmedia types: application/octet-stream, application/postscript, application/x-matlab-data, application/zip, text/plain, text/x-c, text/x-matlab, text/xml
organizationsKavli Institute of Nanoscience Delft, Delft University of Technology;
Wageningen University & Research, Bioinformatics Group