Evidence map›Paper›PMID 31015503›Full record

ArticleScientific reports2019

Insights into protein sequencing with an α-Hemolysin nanopore by atomistic simulations.

Giovanni Di Muccio, Aldo Eugenio Rossini, Daniele Di Marino, Giuseppe Zollo, Mauro Chinappi

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  18. iScience · 2021
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Giovanni Di MuccioDipartimento di Ingegneria Industriale, Università di Roma Tor Vergata, Via del Politecnico 1, 00133, Roma, Italy.
Aldo Eugenio RossiniDipartimento di Scienze di Base e Applicate per l'Ingegneria, Università di Roma "La Sapienza", Via A. Scarpa 14-16, 00161, Rome, Italy.
Daniele Di MarinoFaculty of Biomedical Sciences, Institute of Computational Science - Center for Computational Medicine in Cardiology Università della Svizzera Italiana (USI), Lugano, Switzerland. daniele.di.marino@usi.ch.
Giuseppe ZolloDipartimento di Scienze di Base e Applicate per l'Ingegneria, Università di Roma "La Sapienza", Via A. Scarpa 14-16, 00161, Rome, Italy.
Mauro ChinappiDipartimento di Ingegneria Industriale, Università di Roma Tor Vergata, Via del Politecnico 1, 00133, Roma, Italy. mauro.chinappi@uniroma2.it.ORCID http://orcid.org/0000-0002-4509-1247

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single molecule protein sequencing would represent a disruptive burst in proteomic research with important biomedical impacts. Due to their success in DNA sequencing, nanopore based devices have been recently proposed as possible tools for the sequencing of peptide chains. One of the open questions in nanopore protein sequencing concerns the ability of such devices to provide different signals for all the 20 standard amino acids. Here, using equilibrium all-atom molecular dynamics simulations, we estimated the pore clogging in α-Hemolysin nanopore associated to 20 different homopeptides, one for each standard amino acid. Our results show that pore clogging is affected by amino acid volume, hydrophobicity and net charge. The equilibrium estimations are also supported by non-equilibrium runs for calculating the current blockades for selected homopeptides. Finally, we discuss the possibility to modify the α-Hemolysin nanopore, cutting a portion of the barrel region close to the trans side, to reduce spurious signals and, hence, to enhance the sensitivity of the nanopore.

Indexed as

NanoporesEscherichia coliEscherichia coli ProteinsHemolysin ProteinsEscherichia coli ProteinsHemolysin ProteinsHlya protein, E coli

Identifiers

PMID31015503
PMCPMC6478933

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.