摘要：SummaryThe identification of proteins at the single-molecule level would open exciting new venues in biological research and disease diagnostics. Previously, we proposed a nanopore-based method for protein identification called chop-n-drop fingerprinting, in which the fragmentation pattern induced and measured by a proteasome-nanopore construct is used to identify single proteins. In the simulation study presented here, we show that 97.1% of human proteome constituents are uniquely identified under close to ideal measuring circumstances, using a simple alignment-based classification method. We show that our method is robust against experimental error, as 69.4% can still be identified if the resolution is twice as low as currently attainable, and 10% of proteasome restriction sites and protein fragments are randomly ignored. Based on these results and our experimental proof of concept, we argue that chop-n-drop fingerprinting has the potential to make cost-effective single-molecule protein identification feasible in the near future.Graphical abstractDisplay OmittedHighlights•A proteasome-nanopore construct can cleave a protein and interrogate the fragments•In simulations, this process provides sufficient information to identify proteins•An alignment-based classifier attains 97% accuracy on the entire human proteomeBiocomputational method; Sequence analysis; Proteomics
