Evidence map›Paper›PMID 39150098›Full record

ArticleJournal of chemical information and modeling2024

Ribosome Tunnel Environment Drives the Formation of α-Helix during Cotranslational Folding.

Takunori Yasuda, Rikuri Morita, Yasuteru Shigeta, Ryuhei Harada

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Takunori YasudaDoctoral Program in Biology, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Japan.ORCID 0009-0003-9423-0957
Rikuri MoritaCenter for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.ORCID 0000-0002-0465-5528
Yasuteru ShigetaCenter for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.ORCID 0000-0002-3219-6007
Ryuhei HaradaCenter for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.ORCID 0000-0001-7987-0540

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein conformations in cells are not solely determined by amino acid sequences; they also depend on cellular environments. For instance, the ribosome tunnel induces its specific α-helix formation during cotranslational folding. Owing to the link between these temporally α-helix and biological functions, the mechanism of α-helix formation inside the ribosome tunnel has been previously explored. Consequently, the conformational restrictions of the tunnel were considered one of the driving forces of α-helix formation. Conversely, the ribosomal tunnel environment, including its chemical properties, appears to influence the α-helix formation. However, a comprehensive analysis of the ribosome tunnel environment's impact on the α-helix formation has not been conducted yet due to challenges in experimentally controlling it. Therefore, as a new computational approach, we proposed a ribosome environment-mimicking model (REMM) based on the radius and components of the experimentally determined ribosome tunnel structures. Using REMM, we assessed the impact of the ribosome tunnel environment on α-helix formation. Herein, we employed carbon nanotubes (CNT) as a reference model alongside REMM because CNT reproduce conformational restrictions rather than the ribosome tunnel environment. Quantitatively, the ability to reproduce the α-helix of nascent peptides in the experimental structure was compared between the CNT and REMM using enhanced all-atom molecular dynamics simulations. Consequently, the REMM more accurately reproduced the α-helix of the nascent peptides than the CNT, highlighting the significance of the ribosome tunnel environment in α-helix formation. Additionally, we analyzed the properties of the peptide inside each model to reveal the mechanism of ribosome tunnel-specific α-helix formation. Consequently, we revealed that the chemical diversities of the tunnel are essential for the formation of backbone-to-backbone hydrogen bonds in the peptides. In conclusion, the ribosome tunnel environment, with the diverse chemical properties, drives its specific α-helix formation. By proposing REMM, we newly provide the technical basis for investigating the protein conformations in various cellular environments.

Indexed as

Protein BiosynthesisProtein Conformation, alpha-HelicalProtein FoldingRibosomesModels, MolecularMolecular Dynamics SimulationNanotubes, CarbonNanotubes, Carbon

Identifiers

PMID39150098
PMCPMC11351022

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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.