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Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities

A theoretical model is proposed for the identification of individual amino acids (AAs) in an unfolded whole protein’s primary sequence. It is based in part on a recent report (Nat. Biotech. 41, 1130–1139, 2023) that describes the unfolding and translocation of whole proteins at constant speed throug...

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Autor principal: Sampath, G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491143/
https://www.ncbi.nlm.nih.gov/pubmed/37693569
http://dx.doi.org/10.1101/2023.08.31.555759
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author Sampath, G.
author_facet Sampath, G.
author_sort Sampath, G.
collection PubMed
description A theoretical model is proposed for the identification of individual amino acids (AAs) in an unfolded whole protein’s primary sequence. It is based in part on a recent report (Nat. Biotech. 41, 1130–1139, 2023) that describes the unfolding and translocation of whole proteins at constant speed through a biological nanopore (alpha-Hemolysin) of length 5 nm with a residue dwell time inside the pore of ~10 μs. Here current blockade levels in the pore due to the translocating protein are assumed to be measured with a limited precision of 70 nm(3) and a bandwidth of 20 KHz for measurement with a low-bandwidth detector. Exclusion volumes in two pores of slightly different lengths are used as a computational proxy for the blockade signal; subsequence exclusion volume differences along the protein sequence are computed from the sampled translocation signals in the two pores relatively shifted multiple times. These are then converted into a system of linear inequalities that can be solved with linear programming and related methods; residues are coarsely identified as belonging to one of 4 subsets of the 20 standard AAs. To obtain the exact identity of a residue an artifice analogous to the use of base-specific tags for DNA sequencing with a nanopore (PNAS 113, 5233–5238, 2016) is used. Conjugates that add volume are attached to a given AA type, this biases the set of inequalities toward the volume of the conjugated AA, from this biased set the position of occurrence of every residue of the AA type in the whole sequence is extracted. By applying this step separately to each of the 20 standard AAs the full sequence can be obtained. The procedure is illustrated with a protein in the human proteome (Uniprot id UP000005640_9606).
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spelling pubmed-104911432023-09-09 Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities Sampath, G. bioRxiv Article A theoretical model is proposed for the identification of individual amino acids (AAs) in an unfolded whole protein’s primary sequence. It is based in part on a recent report (Nat. Biotech. 41, 1130–1139, 2023) that describes the unfolding and translocation of whole proteins at constant speed through a biological nanopore (alpha-Hemolysin) of length 5 nm with a residue dwell time inside the pore of ~10 μs. Here current blockade levels in the pore due to the translocating protein are assumed to be measured with a limited precision of 70 nm(3) and a bandwidth of 20 KHz for measurement with a low-bandwidth detector. Exclusion volumes in two pores of slightly different lengths are used as a computational proxy for the blockade signal; subsequence exclusion volume differences along the protein sequence are computed from the sampled translocation signals in the two pores relatively shifted multiple times. These are then converted into a system of linear inequalities that can be solved with linear programming and related methods; residues are coarsely identified as belonging to one of 4 subsets of the 20 standard AAs. To obtain the exact identity of a residue an artifice analogous to the use of base-specific tags for DNA sequencing with a nanopore (PNAS 113, 5233–5238, 2016) is used. Conjugates that add volume are attached to a given AA type, this biases the set of inequalities toward the volume of the conjugated AA, from this biased set the position of occurrence of every residue of the AA type in the whole sequence is extracted. By applying this step separately to each of the 20 standard AAs the full sequence can be obtained. The procedure is illustrated with a protein in the human proteome (Uniprot id UP000005640_9606). Cold Spring Harbor Laboratory 2023-09-03 /pmc/articles/PMC10491143/ /pubmed/37693569 http://dx.doi.org/10.1101/2023.08.31.555759 Text en https://creativecommons.org/licenses/by-nd/4.0/This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Sampath, G.
Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
title Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
title_full Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
title_fullStr Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
title_full_unstemmed Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
title_short Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
title_sort identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491143/
https://www.ncbi.nlm.nih.gov/pubmed/37693569
http://dx.doi.org/10.1101/2023.08.31.555759
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