A theoretical analysis of single molecule protein sequencing via weak binding spectra
Author(s)
Rodriques, Samuel G.; Marblestone, Adam H.; Boyden, Edward S.
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© 2019 Rodriques et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. We propose and theoretically study an approach to massively parallel single molecule peptide sequencing, based on single molecule measurement of the kinetics of probe binding (Havranek, et al., 2013) to the N-termini of immobilized peptides. Unlike previous proposals, this method is robust to both weak and non-specific probe-target affinities, which we demonstrate by applying the method to a range of randomized affinity matrices consisting of relatively low-quality binders. This suggests a novel principle for proteomic measurement whereby highly non-optimized sets of low-affinity binders could be applicable for protein sequencing, thus shifting the burden of amino acid identification from biomolecular design to readout. Measurement of probe occupancy times, or of time-averaged fluorescence, should allow high-accuracy determination of N-terminal amino acid identity for realistic probe sets. The time-averaged fluorescence method scales well to weakly-binding probes with dissociation constants of tens or hundreds of micromolar, and bypasses photobleaching limitations associated with other fluorescence-based approaches to protein sequencing. We argue that this method could lead to an approach with single amino acid resolution and the ability to distinguish many canonical and modified amino acids, even using highly non-optimized probe sets. This readout method should expand the design space for single molecule peptide sequencing by removing constraints on the properties of the fluorescent binding probes.
Date issued
2019-03Department
Massachusetts Institute of Technology. Synthetic Neurobiology Group; Massachusetts Institute of Technology. Department of Physics; McGovern Institute for Brain Research at MIT; Massachusetts Institute of Technology. Media Laboratory; Massachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; Koch Institute for Integrative Cancer Research at MITJournal
PLoS ONE
Publisher
Public Library of Science (PLoS)
ISSN
1932-6203