Evidence map›Paper›PMID 41557786›Full record

ArticleThe journal of physical chemistry. B2026

Decoding Allosteric Inhibition in MALT1: The Hidden Role of Conformational Plasticity in Metastable States via Biased MD and Deep Learning.

Rodrigo M Santos, Taináh M R Santos, Teodorico C Ramalho

Abstract read
In one paragraph

Article in The journal of physical chemistry. B, 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

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

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

3 authors.

Rodrigo M SantosLaboratory of Molecular Modelling, Department of Chemistry, Federal University of Lavras, Lavras 37200-000, Minas Gerais, Brazil.
Taináh M R SantosLaboratory of Molecular Modelling, Department of Chemistry, Federal University of Lavras, Lavras 37200-000, Minas Gerais, Brazil.ORCID 0000-0002-7737-9595
Teodorico C RamalhoLaboratory of Molecular Modelling, Department of Chemistry, Federal University of Lavras, Lavras 37200-000, Minas Gerais, Brazil.ORCID 0000-0002-7324-1353

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mucosa-associated lymphoid tissue lymphoma-translocation protein 1 (MALT1) is a key protein in the adaptive immune response system in humans. This protein is widely expressed in the human body and is related to nuclear factor-κB (NF-κB) signaling activation in response to T-cell receptors. Due to this, MALT1 is key in the regulation of inflammatory events in a variety of tissues, where its dysregulation is associated with several types of cancer, especially hematological cancers. In this sense, its relevance makes MALT1 a valuable target to treat many diseases, drawing the attention of many researchers with the aim of proposing new MALT1 inhibitors. However, there is a lack of literature describing its complex dynamical behavior and allosteric inhibition, which considerably hampers the computational design of new MALT1 allosteric inhibitors. In that regard, the present work investigated the complex conformational behavior of MALT1 protein during its allosteric inhibition. For this, biased molecular dynamics simulations, sophisticated machine learning techniques such as neural networks, and docking calculations were used. From the performed investigation, it was observed that through allosteric inhibition, Loop 1 and 3 movements were crucial to reduce the catalytic site cavity volume, keeping cysteine unavailable for substrate mimic binding. In addition, statistical information over the explored ensemble showed that the great majority of the inhibited conformations presented an unavailable catalytic cysteine for substrate binding. Hence, the presented results can be used as an objective criterion for the computational proposal of new MALT1 allosteric inhibitors. However, despite mouse MALT1 and human MALT1 presenting 93% homology, the generalization of the findings to human MALT1 protein should be taken with care, and the obtained results apply specifically to the mouse MALT1 construct.

Indexed as

Deep LearningMolecular Dynamics SimulationMucosa-Associated Lymphoid Tissue Lymphoma Translocation 1 ProteinAllosteric RegulationCatalytic DomainHumansMolecular Docking SimulationProtein ConformationMALT1 protein, humanMucosa-Associated Lymphoid Tissue Lymphoma Translocation 1 Protein

Identifiers

PMID41557786
PMCPMC12862816

What Socratic holds

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LicenceCC BY
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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 Socratic graph.