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Neuropharmacological Innovations in Treating Neurodegenerative Diseases

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Neurobiology".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 801

Special Issue Editor


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Guest Editor
Faculty of Medicine, Preclinical Department, Lucian Blaga University of Sibiu, 550024 Sibiu, Romania
Interests: clinical pharmacology; drug safety; neurodegeneration; biomedical data analysis

Special Issue Information

Dear Colleagues,

One of the most urgent medical issues of our day is neurodegenerative disease, which causes a steady reduction in patients' quality of life and is a significant social burden. The Special Issue "Neuropharmacological Innovations in Treating Neurodegenerative Diseases" aims to publish new research and therapeutic advancements that offer new hope for patients affected by these debilitating conditions.

Papers are encouraged to examine innovative pharmacological strategies, such as creating new drug candidates, repurposing already-approved drugs, and combining therapies to enhance neurological function. Significant areas of focus include finding pharmacological treatments that alter pathologic pathways and elucidating the molecular and cellular processes causing neurodegeneration. Research on neuroprotective substances, substances that promote neurogenesis, and methods for re-establishing synaptic plasticity and functional recovery are also welcomed.

We are also seeking research that combines electrophysiological techniques, imaging, and biomarker discovery to assess medication effectiveness and promote early diagnosis. Further, novel uses of AI and machine learning to highlight medication effects and enhance individualised treatment plans are welcome. We look forward to your contributions.

Dr. Gabriela Cioca
Guest Editor

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Keywords

  • neuropharmacology
  • neurodegenerative disorders
  • targeted drug delivery
  • blood–brain barrier permeability
  • synaptic modulation
  • neuroprotective agents
  • disease-modifying therapies
  • molecular mechanisms of neurodegeneration
  • innovative drug targets
  • translational neuroscience

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Published Papers (1 paper)

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Research

84 pages, 7286 KB  
Article
Network-Medicine-Guided Drug Repurposing for Alzheimer’s Disease: A Multi-Dimensional Systems Pharmacology Approach
by Ömer Akgüller, Mehmet Ali Balcı and Gabriela Cioca
Int. J. Mol. Sci. 2025, 26(20), 10003; https://doi.org/10.3390/ijms262010003 - 14 Oct 2025
Viewed by 689
Abstract
Alzheimer’s disease (AD) drug development faces persistent challenges from blood–brain barrier limitations and inadequate integration of medicinal chemistry considerations with computational predictions. We developed a comprehensive Central Nervous System (CNS)-focused network medicine framework integrating machine-learning-validated BBB penetration prediction (95.7% accuracy, 0.992 AUC-ROC), modality-specific [...] Read more.
Alzheimer’s disease (AD) drug development faces persistent challenges from blood–brain barrier limitations and inadequate integration of medicinal chemistry considerations with computational predictions. We developed a comprehensive Central Nervous System (CNS)-focused network medicine framework integrating machine-learning-validated BBB penetration prediction (95.7% accuracy, 0.992 AUC-ROC), modality-specific tractability assessment, and transparent evidence classification to identify viable drug repurposing candidates. CNS-specific pre-filtering refined 24,474 DGIdb compounds to 8247 CNS-relevant drugs, analyzed through multi-dimensional network scoring and systematic pharmaceutical property assessment. Modality stratification generated separate rankings for small molecules (3667 candidates), peptides (73 candidates), and biologics (3 candidates), acknowledging distinct BBB penetration mechanisms. Analysis revealed 64.8% of small molecules achieving Class I (Highly Tractable) status, with 83.6% demonstrating favorable BBB penetration. Plerixafor emerged as the top-ranked small molecule (score: 1.170), while trofinetide achieved the highest peptide ranking (score: 1.387), though classified as speculative, pending AD-specific validation. Successful identification of the FDA-approved AD therapeutics memantine and donepezil among the top candidates validated the computational performance, while the predominance of mechanistic evidence classifications (86.7%) highlighted that network predictions represent hypothesis-generating tools requiring systematic experimental validation rather than definitive therapeutic recommendations. The framework bridges computational predictions with pharmaceutical development requirements, providing actionable prioritization for systematic preclinical investigation addressing AD intervention. Full article
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