Evidence map›Paper›PMID 42830633›Full record

ArticleChemMedChem2026

Capturing Hu Antigen R Domain Closure Through Supervised Molecular Dynamics Simulations.

Chiara Cavastracci Strascia, Andrea Dodaro, Gianluca Novello, Silvia Menin, Mattia Sturlese, Veronica Salmaso, Stefano Moro

Abstract read
In one paragraph

Article in ChemMedChem, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

7 authors.

Chiara Cavastracci StrasciaMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0009-0007-1605-2904
Andrea DodaroMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0009-0009-9515-5227
Gianluca NovelloMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0009-0008-5005-4329
Silvia MeninMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0001-9217-1461
Mattia SturleseMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0003-3944-0313
Veronica SalmasoMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0001-5305-8351
Stefano MoroMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0002-7514-3802

Funding

European Union - Next-Generation EU PNRR M4C2-Investimento 1.4-CN00000041
6 · The paper itself

Abstract

Hu antigen R (HuR), an RNA-binding protein implicated in cancer, inflammation, and neurodegenerative disorders, represents a challenging target for drug discovery due to its large solvent-exposed RNA-binding interface and pronounced conformational flexibility. HuR contains tandem RNA recognition motifs (RRM1 and RRM2) that undergo substantial rearrangements between an apo open state and an RNA-bound closed conformation. Here, we investigated both states using molecular dynamics (MD) simulations. While the RNA-bound complex maintained a stable closed architecture, the apo form displayed extensive interdomain motions, highlighting the intrinsic flexibility of HuR. Because conventional MD simulations failed to capture the open-to-closed transition, we developed a novel application of Supervised MD (SuMD), previously employed for intermolecular recognition processes, to characterize HuR intramolecular domain closure. Using a multistep supervision protocol based on selected interdomain residue pairs, SuMD reproduced a closed conformation resembling the experimental RNA-bound structure and identified a plausible reclosure pathway. Per-residue interaction analyses revealed key contributions from the RRM1-RRM2 linker region, particularly Arg97, together with Arg136 and Arg147 of RRM2, consistent with mutagenesis data. These findings extend the applicability of SuMD to intramolecular conformational transitions, provide mechanistic insight into HuR domain closure, and offer a structural framework for identifying druggable conformational states for future HuR-targeted drug discovery.

Indexed as

ELAV-Like Protein 1Molecular Dynamics SimulationHumansProtein DomainsRNAELAVL1 protein, humanELAV-Like Protein 1RNAconformational dynamicsdomain closureHuR (ELAVL1)structure‐based drug designsupervised molecular dynamics

Identifiers

PMID42830633
PMCPMC13635762

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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.