4.7 Article

Multiomics Identification of Potential Targets for Alzheimer Disease and Antrocin as a Therapeutic Candidate

期刊

PHARMACEUTICS
卷 13, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/pharmaceutics13101555

关键词

Alzheimer's disease; biomarker identification; in silico pharmacological analyses; antrocin; therapeutic innovation

资金

  1. Ministry of Education, Taipei Medical University [DP2-110-21121-03-C-09, DP2-110-21121-01-H-03-03]
  2. Ministry of Science and Technology [MOST110-2314-B-038-024]

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Alzheimer's disease is a common cause of neurodegenerative dementia, affecting nearly 50 million people worldwide. Despite challenges in early diagnosis and effective treatment, identifying essential genes and molecular pathways associated with the disease's pathogenesis may lead to potential treatments. Integrating differentially expressed genes from AD datasets has allowed for the identification of upregulated DEGs common in multiple datasets, offering insight into the molecular pathogenesis of AD.
Alzheimer's disease (AD) is the most frequent cause of neurodegenerative dementia and affects nearly 50 million people worldwide. Early stage diagnosis of AD is challenging, and there is presently no effective treatment for AD. The specific genetic alterations and pathological mechanisms of the development and progression of dementia remain poorly understood. Therefore, identifying essential genes and molecular pathways that are associated with this disease's pathogenesis will help uncover potential treatments. In an attempt to achieve a more comprehensive understanding of the molecular pathogenesis of AD, we integrated the differentially expressed genes (DEGs) from six microarray datasets of AD patients and controls. We identified ATPase H+ transporting V1 subunit A (ATP6V1A), BCL2 interacting protein 3 (BNIP3), calmodulin-dependent protein kinase IV (CAMK4), TOR signaling pathway regulator-like (TIPRL), and the translocase of outer mitochondrial membrane 70 (TOMM70) as upregulated DEGs common to the five datasets. Our analyses revealed that these genes exhibited brain-specific gene co-expression clustering with OPA1, ITFG1, OXCT1, ATP2A2, MAPK1, CDK14, MAP2K4, YWHAB, PARK2, CMAS, HSPA12A, and RGS17. Taking the mean relative expression levels of this geneset in different brain regions into account, we found that the frontal cortex (BA9) exhibited significantly (p < 0.05) higher expression levels of these DEGs, while the hippocampus exhibited the lowest levels. These DEGs are associated with mitochondrial dysfunction, inflammation processes, and various pathways involved in the pathogenesis of AD. Finally, our blood-brain barrier (BBB) predictions using the support vector machine (SVM) and LiCABEDS algorithm and molecular docking analysis suggested that antrocin is permeable to the BBB and exhibits robust ligand-receptor interactions with high binding affinities to CAMK4, TOMM70, and T1PRL. Our results also revealed good predictions for ADMET properties, drug-likeness, adherence to Lipinskis rules, and no alerts for pan-assay interference compounds (PAINS) Conclusions: These results suggest a new molecular signature for AD parthenogenesis and antrocin as a potential therapeutic agent. Further investigation is warranted.

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