In Silico Drug Repositioning Identifies SYK Kinase Inhibitors as Potential Neuroprotective Agents for Ataxia-Telangiectasia.

Overview

Authors: Alessia Romano¹, Rocco Buccheri¹, Chiara Zagni¹, Antonio Rescifina¹

Department of Drug and Health Sciences, University of Catania, Catania, Italy

Institutions: University of Catania (Italy)

Journal: Chemical biology & drug design, volume 108, issue 1, article e70354

Dates: received 10 February 2026; accepted 19 June 2026; published online 1 July 2026; in print July 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1111/cbdd.70354 · PMID 42384606 · PMCID PMC13322510 · OpenAlex W7166809654

Open access: hybrid, a free copy (OpenAlex)

Status: data only

Categories: computational modeling (no new data) (modality), human (organism), other condition (population), cellular / molecular (subfield)

Methods: Smoothing, state filtering, decompositions

Keywords: Ataxia–Telangiectasia, drug repositioning, molecular docking, molecular dynamics, network medicine, structure‐based drug design, SYK kinase

MeSH: Ataxia Telangiectasia*, Drug Repositioning*, Neuroprotective Agents*, Protein Kinase Inhibitors*, Syk Kinase*, Catalytic Domain, Humans, Molecular Docking Simulation, Molecular Dynamics Simulation (* major topic)

Topic: Melanoma and MAPK Pathways (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex

Funding: Ministero della Salute (CUP E63C22001680001—ID T4‐AN‐04); Italian Ministry of Health, Piano di Sviluppo e Coesione del Ministero della Salute 2014-2020 (CUP E63C22001680001-ID T4-AN-04)

Citations: not cited yet (Europe PMC); 36 references in the paper

Abstract

Ataxia–Telangiectasia (AT) is a rare neurodegenerative disorder characterized by progressive neuronal loss and chronic neuroinflammation. Emerging evidence indicates that aberrant overexpression of the adaptor protein TYROBP promotes sustained recruitment and activation of spleen tyrosine kinase (SYK), contributing to pathogenic inflammatory signaling in AT. In this study, we applied a drug repositioning strategy to identify clinically approved compounds that inhibit SYK activity. An integrated in silico workflow was employed, combining convolutional neural network (CNN)–based molecular docking with network medicine analysis using the SAveRUNNER platform to screen a library of 2342 FDA‐approved drugs. The top‐ranked candidates were further evaluated using long‐timescale molecular dynamics simulations and post‐simulation redocking to assess their binding stability and conformational persistence within the SYK catalytic pocket under explicit solvent conditions. This multilevel computational analysis identified vemurafenib and palbociclib as the most promising SYK inhibitors, both exhibiting sustained binding affinity and stable intermolecular interactions following protein relaxation. These findings support the feasibility of repurposing FDA‐approved drugs to modulate SYK‐driven neuroinflammatory pathways and provide a mechanistic framework for developing novel neuroprotective interventions for AT.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

The paper's code and data availability statement is in the Data section.

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Data

Datasets cited

github.com/rocco-b/hthq-gnina — at github.com; found in the text, “Comparison With Representative SYK Inhibitors”
github.com/rocco-b/syk-kinase-inhibitors-docking-and-md-data — at github.com; found in “Data Availability Statement”

Data Availability Statement

The data supporting the findings of this study are available at https://github.com/rocco‐b/SYK‐Kinase‐Inhibitors‐Docking‐and‐MD‐data (https://github.com/rocco-b/SYK-Kinase-Inhibitors-Docking-and-MD-data).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 2, 28 September 2026

Publisher: — → Wiley

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 7 keywords, 9 MeSH terms, 2 funders, 36 references.

Cite

This paper

Romano, A., Buccheri, R., Zagni, C., & Rescifina, A. (2026). In Silico Drug Repositioning Identifies SYK Kinase Inhibitors as Potential Neuroprotective Agents for Ataxia-Telangiectasia. Chemical biology & drug design, 108(1), e70354. https://doi.org/10.1111/cbdd.70354

BibTeX

@article{romano2026silico, author = {Romano, Alessia and Buccheri, Rocco and Zagni, Chiara and Rescifina, Antonio}, title = {{In Silico Drug Repositioning Identifies SYK Kinase Inhibitors as Potential Neuroprotective Agents for Ataxia-Telangiectasia}}, journal = {Chemical biology \& drug design}, year = {2026}, month = jul, volume = {108}, number = {1}, pages = {e70354}, publisher = {Wiley}, issn = {1747-0277}, doi = {10.1111/cbdd.70354}, url = {https://doi.org/10.1111/cbdd.70354}, pmid = {42384606}, pmcid = {PMC13322510} }

RIS

TY - JOUR AU - Romano, Alessia AU - Buccheri, Rocco AU - Zagni, Chiara AU - Rescifina, Antonio TI - In Silico Drug Repositioning Identifies SYK Kinase Inhibitors as Potential Neuroprotective Agents for Ataxia-Telangiectasia T2 - Chemical biology & drug design J2 - Chem Biol Drug Des PY - 2026 DA - 2026/07/01 VL - 108 IS - 1 SP - e70354 SN - 1747-0277 PB - Wiley DO - 10.1111/cbdd.70354 UR - https://doi.org/10.1111/cbdd.70354 LA - en ER -

CSL-JSON

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