Evidence map›Paper›PMID 42857445›Full record

ReviewFrontiers in aging neuroscience2026

Tau protein in Parkinson's disease: advances in phosphoproteomics and molecular dynamics simulations.

Jessica Ledesma-Aparicio, Luis Alberto Caro-Gómez, Francisco Javier Padilla-Godínez, Omar Hernández-González, Luis O Soto-Rojas, Juan Pablo Reyes-Grajeda, Oscar Arias-Carrión, Marcela Palomero-Rivero, Brandt Bertrand, Carlos Munoz-Garay and 1 more

Abstract readReview
In one paragraph

Review in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Jessica Ledesma-AparicioLaboratory of Regenerative Medicine, Department of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico.
Luis Alberto Caro-GómezLaboratory of Regenerative Medicine, Department of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico.
Francisco Javier Padilla-GodínezDepartment of Mathematics and Physics, Western Institute of Technology and Higher Education, San Pedro Tlaquepaque, Jalisco, Mexico.
Omar Hernández-GonzálezLaboratory of Regenerative Medicine, Department of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico.
Luis O Soto-RojasLaboratory of Neuroscience, Aging and Neurodegeneration (LINEN), Medical Degree Program, Faculty of Higher Studies Iztacala, National Autonomous University of Mexico (UNAM), Tlalnepantla, State of Mexico, Mexico.
Juan Pablo Reyes-GrajedaProtein Structure Laboratory, National Institute of Genomic Medicine (INMEGEN), Mexico City, Mexico.
Oscar Arias-CarriónDivision of Clinical Neurosciences, National Institute of Rehabilitation, Mexico City, Mexico.
Marcela Palomero-RiveroDepartment of Cognitive Neuroscience, Division of Neurosciences, Institute of Cellular Physiology, National Autonomous University of Mexico, Mexico City, Mexico.
Brandt BertrandBiological Membrane Physics Laboratory, Institute of Physical Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico.
Carlos Munoz-GarayBiological Membrane Physics Laboratory, Institute of Physical Sciences, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico.
Magdalena Guerra-CrespoLaboratory of Regenerative Medicine, Department of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tau dysregulation, particularly abnormal phosphorylation, is increasingly implicated in Parkinson's disease (PD) and in the pathogenic interaction between Tau and α-synuclein. This review proposes an integrated PD-focused workflow connecting phosphoproteomic discovery, structural modeling, computational drug discovery, and experimental validation. Phosphoproteomic analyses of post-mortem brain tissue, biofluids, and patient-derived dopaminergic neuronal models can identify candidate Tau phosphosignatures associated with vulnerable brain regions, α-synuclein pathology, genetic background, or clinical progression. Molecular dynamics simulations can then evaluate how these signatures alter Tau conformation, microtubule binding, aggregation-prone motifs, membrane association, and pathogenic protein interactions. The resulting structural information can guide ensemble docking, chemoinformatics, and artificial intelligence approaches to prioritize conformer-selective ligands and regulatory targets. Candidate biomarkers should subsequently be validated in independent and longitudinal PD cohorts, whereas therapeutic candidates require mechanistic and functional validation in PD-relevant experimental models before clinical translation. This iterative framework may help distinguish mechanistically relevant Tau phosphoconformers from nonspecific phosphorylation changes, support biomarker-based patient stratification, and focus therapeutic development on structurally defined pathological states. Because much of the available structural evidence derives from Alzheimer's disease and other tauopathies, direct validation in PD remains essential. By linking PD-derived and disease-relevant molecular evidence with atomistic mechanisms and therapeutic prioritization, this workflow may support biomarker-informed strategies aimed at restoring Tau homeostasis and disrupting pathogenic Tau-α-synuclein interactions.

Indexed as

molecular dynamicsneurodegenerationParkinson’s diseasephosphoproteomicssynucleinopathiesTau

Identifiers

PMID42857445
PMCPMC13650618

What OpenQuestion holds

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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.