Evidence map›Paper›PMID 36625864›Full record

ArticleThe Journal of general physiology2023

Multiscale molecular dynamics simulations predict arachidonic acid binding sites in human ASIC1a and ASIC3 transmembrane domains.

Anna Ananchenko, Maria Musgaard

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of general physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Anna AnanchenkoDepartment of Chemistry and Biomolecular Sciences, University of Ottawa , Ottawa, Canada.
Maria MusgaardDepartment of Chemistry and Biomolecular Sciences, University of Ottawa , Ottawa, Canada.ORCID 0000-0001-6096-9014
University of Ottawa · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acid-sensing ion channels (ASICs) play important roles in inflammatory pathways by conducting ions across the neuronal membrane in response to proton binding under acidic conditions. Recent studies have shown that ASICs can be modulated by arachidonic acid (AA), and, in the case of the ASIC3 subtype, even activated by AA at physiological pH. However, the mechanism by which these fatty acids act on the channel is still unknown. Here, we have used multiscale molecular dynamics simulations to predict a putative, general binding region of AA to models of the human ASIC protein. We have identified, in agreement with recent studies, residues in the outer leaflet transmembrane region which interact with AA. In addition, despite their similar modulation, we observe subtle differences in the AA interaction pattern between human ASIC1a and human ASIC3, which can be reversed by mutating three key residues at the outer leaflet portion of TM1. We further probed interactions with these residues in hASIC3 using atomistic simulations and identified possible AA coordinating interactions; salt bridge interactions of AA with R65hASIC3 and R68hASIC3 and AA tail interactions with the Y58hASIC3 aromatic ring. We have shown that longer fatty acid tails with more double bonds have increased relative occupancy in this region of the channel, a finding supported by recent functional studies. We further proposed that the modulatory effect of AA on ASIC does not result from changes in local membrane curvature. Rather, we speculate that it may occur through structural changes to the ion channel upon AA binding.

Indexed as

Acid Sensing Ion ChannelsMolecular Dynamics SimulationArachidonic AcidsBinding SitesHumansNeuronsProtein DomainsAcid Sensing Ion ChannelsArachidonic AcidsASIC3 protein, human

Identifiers

PMID36625864
PMCPMC9836442
OpenAlexW4313989936

What OpenQuestion holds

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LicenceCC BY-NC-SA
Read underepoch 390

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.