Evidence map›Paper›PMID 38829838›Full record

ArticlePloS one2024

Atomistic description of the OCTN1 recognition mechanism via in silico methods.

Omar Ben Mariem, Luca Palazzolo, Beatrice Torre, Yao Wei, Davide Bianchi, Uliano Guerrini, Tommaso Laurenzi, Simona Saporiti, Emma De Fabiani, Lorena Pochini and 2 more

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Omar Ben MariemDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.ORCID 0000-0001-5210-8089
Luca PalazzoloDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Beatrice TorreDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Yao WeiDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Davide BianchiDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Uliano GuerriniDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Tommaso LaurenziDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Simona SaporitiAnalytical Excellence and Program Management, Merck Serono S.p.A., Rome, Italy.ORCID 0000-0002-2096-1066
Emma De FabianiDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.
Lorena PochiniDipartimento di Biologia, Ecologia e Scienze della Terra, Università della Calabria, Arcavacata CS, Italy.
Cesare IndiveriDipartimento di Biologia, Ecologia e Scienze della Terra, Università della Calabria, Arcavacata CS, Italy.
Ivano EberiniDipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy.ORCID 0000-0001-5521-3829

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Organic Cation Transporter Novel 1 (OCTN1), also known as SLC22A4, is widely expressed in various human tissues, and involved in numerous physiological and pathological processes remains. It facilitates the transport of organic cations, zwitterions, with selectivity for positively charged solutes. Ergothioneine, an antioxidant compound, and acetylcholine (Ach) are among its substrates. Given the lack of experimentally solved structures of this protein, this study aimed at generating a reliable 3D model of OCTN1 to shed light on its substrate-binding preferences and the role of sodium in substrate recognition and transport. A chimeric model was built by grafting the large extracellular loop 1 (EL1) from an AlphaFold-generated model onto a homology model. Molecular dynamics simulations revealed domain-specific mobility, with EL1 exhibiting the highest impact on overall stability. Molecular docking simulations identified cytarabine and verapamil as highest affinity ligands, consistent with their known inhibitory effects on OCTN1. Furthermore, MM/GBSA analysis allowed the categorization of substrates into weak, good, and strong binders, with molecular weight strongly correlating with binding affinity to the recognition site. Key recognition residues, including Tyr211, Glu381, and Arg469, were identified through interaction analysis. Ach demonstrated a low interaction energy, supporting the hypothesis of its one-directional transport towards to outside of the membrane. Regarding the role of sodium, our model suggested the involvement of Glu381 in sodium binding. Molecular dynamics simulations of systems at increasing levels of Na+ concentrations revealed increased sodium occupancy around Glu381, supporting experimental data associating Na+ concentration to molecule transport. In conclusion, this study provides valuable insights into the 3D structure of OCTN1, its substrate-binding preferences, and the role of sodium in the recognition. These findings contribute to the understanding of OCTN1 involvement in various physiological and pathological processes and may have implications for drug development and disease management.

Indexed as

Molecular Docking SimulationMolecular Dynamics SimulationOrganic Cation Transport ProteinsAcetylcholineBinding SitesComputer SimulationErgothioneineHumansLigandsProtein BindingSodiumSymportersAcetylcholineErgothioneineLigandsOrganic Cation Transport ProteinsSLC22A4 protein, humanSodiumSymporters

Identifiers

PMID38829838
PMCPMC11146731

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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.