iScience · 2021 · 27 citations · 39 references
Life SciencesBiochemistryMolecular BiologyBiomolecular ModelingComputational BiologyProteomicsPeptide IdentificationProtein IdentificationProtein StructureData Analysis For Targeted ProteomicsFörster Resonance Energy Transfer (Fret)Förster Resonance Energy Transfer SensorsSupport Vector ClassificationSupport Vector Machine Classification
Single-molecule protein identification is an unrealized concept with potentially ground-breaking applications in biological research. We propose a method called FRET X (Förster Resonance Energy Transfer via DNA eXchange) fingerprinting, in which the FRET efficiency is read out between exchangeable dyes on protein-bound DNA docking strands and accumulated FRET efficiencies constitute the fingerprint for a protein. To evaluate the feasibility of this approach, we simulated fingerprints for hundreds of proteins using a coarse-grained lattice model and experimentally demonstrated FRET X fingerprinting on model peptides. Measured fingerprints are in agreement with our simulations, corroborating the validity of our modeling approach. In a simulated complex mixture of >300 human proteins of which only cysteines, lysines, and arginines were labeled, a support vector machine was able to identify constituents with 95% accuracy. We anticipate that our FRET X fingerprinting approach will form the basis of an analysis tool for targeted proteomics.
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