Protein fingerprinting with digital sequences of linear protein subsequence volumes: a computational study

Sampath, G.

doi:10.1007/s12038-019-9863-9

Cited by 6 publications

(8 citation statements)

References 23 publications

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“…Thus with the slowdown procedure given here the resulting low bandwidth measurements of translocating short peptides may yield useful sequence information in the form of blockade volumes for them. For example in [35] it is shown that the volumes of short subsequences (as represented by the corresponding blockade current levels) can be used to identify almost all of the proteins in the yeast proteome.…”

Section: Discussionmentioning

confidence: 99%

“…For recent reviews of protein sequencing/sensing with nanopores, see [22,23]. As with DNA, protein identification is simpler than sequencing as it suffices to find a partial sequence and look for a matching subsequence in a proteome sequence database, see, for example, [24] and [25]. Detection of a protein may be even simpler, without requiring database lookup, for example through matching carrier molecules [26].…”

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confidence: 99%

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Slowing down an analyte in a nanopore

Sampath¹

2021

Preprint

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A major obstacle faced by nanopore-based polymer sequencing and analysis is the high speed of translocation of an analyte (nucleotide, DNA, amino acid (AA), peptide) through the pore; the rate currently exceeds available detector bandwidth. Except for one method that uses an enzyme ratchet to sequence DNA, attempts to resolve the problem satisfactorily have been largely unsuccessful. Here a counterintuitive method based on reversing the pore voltage, and, with some analytes, increasing their mobility, is described. A simplified Fokker-Planck model shows a significant increase in translocation times for single nucleotides and AAs (up from ∼10 ns to ∼1 ms). Simulations show that with a bi-level positive-negative pore voltage profile all four nucleotides and the 20 proteinogenic amino acids can be trapped inside the pore long enough for detection with bandwidths of ∼1-10 Khz. The method presented here provides, at least in theory, a potentially viable solution to a problem that has prevented nanopore-based polymer sequencing methods from realizing their full potential.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Slowing down an analyte in a nanopore

Sampath¹

2021

Preprint

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“…To get around this problem residue identification can be based on measurement of subsequence volumes. (In [26] such an approach was suggested for protein identification; it was shown in theory that over 90% of the proteins in the proteome of H. pylori (UniProt id UP000000210) can be identified with subsequences of length 4 to 8.) In the present study a residue exiting from the pore is associated with the volume excluded by it and its K-1 successor residues during the exit interval of 1 μs.…”

Section: Whole Protein Sequencing With a Nanopore From Subsequence Vo...mentioning

confidence: 99%

Whole protein sequencing and quantification without proteolysis, terminal residue cleavage, or purification: A computational model

Sampath

2024

Preprint

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Sequencing and quantification of whole proteins in a sample without separation, terminal residue cleavage, or proteolysis are modeled computationally. Similar to recent work on DNA sequencing (PNAS 113, 5233-5238, 2016), a high-volume conjugate is attached to every instance of amino acid (AA) type AAi, 1 ≤ i ≤ 20, in an unfolded whole protein, which is then translocated through a nanopore. From the volume excluded by 2L residues in a pore of length L (a proxy for the blockade current), a partial sequence containing AAi is obtained. Translocation is assumed to be unidirectional, with residues exiting the pore at a roughly constant rate of ~1/μs (Nature Biotechnology 41, 1130-1139, 2023). The blockade signal is sampled at intervals of 1 μs and digitized with a step precision of 70 nm3; the positions of the AAis are obtained from the positions of well-defined quantum jumps in the signal. This procedure is applied to all 20 standard AA types, the resulting 20 partial sequences are merged to obtain the whole protein sequence. The complexity of subsequence computation is O(N) for a protein with N residues. The method is illustrated with a sample protein from the human proteome (Uniprot id UP000005640_9606). A mixture containing M unknown protein molecules (which may include multiple copies) is sequenced by mapping their partial sequences to a graph GM with 20M vertexes; GM contains M disjoint cliques of degree 20. Unlike in general clique identification (computationally an NP-hard problem) the M cliques can be obtained through a connected graph components algorithm in polynomial time. Quantification is done by sorting the M sequences on the sequence strings and counting duplicates down the sequence. The complexity of sequencing and quantification of a mixture of M proteins is O(MN). The possibility of translating this procedure into practice and related implementation issues are discussed.

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“…Nonetheless, early experiments showed that when a protein was denatured and impelled through an α-hemolysin pore by an unfoldase, consistent current changes could be assigned to known point mutations and side-chain modifications [35]. The sensitivity of these nanopores was such that they could be used to distinguish between very similar peptides via established electric fingerprints [36,37]. Hypothetically, this should allow de novo identification of a protein sequence from residue volume.…”

Section: Sub-nanoscale Poresmentioning

confidence: 99%

Strategies for Development of a Next-Generation Protein Sequencing Platform

Callahan

Tullman

Kelman

et al. 2020

Trends in Biochemical Sciences

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Proteomic analysis can be a critical bottleneck in cellular characterization. The current paradigm relies primarily on mass spectrometry of peptides and affinity reagents (i.e. antibodies), both of which require a priori knowledge of the sample. A non-biased protein sequencing method, with a dynamic range that covered the full range of protein concentrations in proteomes, would revolutionize the field of proteomics, allowing a more facile characterization of novel gene products and subcellular complexes. To this end, several new platforms based on single-molecule protein-sequencing approaches have been proposed. This review summarizes four of these approaches, highlighting advantages, limitations and challenges for each method towards advancing as a core technology for next-generation protein sequencing.

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Protein fingerprinting with digital sequences of linear protein subsequence volumes: a computational study

Cited by 6 publications

References 23 publications

Slowing down an analyte in a nanopore

Slowing down an analyte in a nanopore

Whole protein sequencing and quantification without proteolysis, terminal residue cleavage, or purification: A computational model

Strategies for Development of a Next-Generation Protein Sequencing Platform

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