Network based approach for drug target identification in early onset Parkinson’s disease

Despite the abundance of large-scale molecular and drug-response data, current research on early-onset Parkinson's disease (EOPD) markers often lacks mechanistic interpretations of drug-gene relationships, limiting our understanding of how drugs exert their therapeutic effects. While existing studies provide valuable EOPD markers, the mechanisms by which targeted drugs act remain poorly understood. We propose DTI-Prox, a novel workflow that identifies potentially overlooked EOPD markers and suggests relevant drug targets. DTI-Prox employs network proximity to measure how closely connected a drug and gene are within a biological network. Additionally, node similarity, which assesses the functional resemblance between network nodes, reveals meaningful drug-gene connections. DTI-Prox identifies 417 novel drug-target pairs and four previously unreported EOPD markers (PTK2B, APOA1, A2M, and BDNF), demonstrating significant pathway enrichment in neurodegenerative processes. Notably, shared pathway analysis shows that prioritized drugs such as Amantadine, Apomorphine, Atropine, Benztropine, Biperiden, Bromocriptine, Cabergoline, Carbidopa, and Citalopram, currently used for other conditions, interact with key EOPD-associated diagnostic markers, suggesting their potential for drug repurposing. The constructed functional network's validity is reinforced by statistically significant drug-target pairs. The findings provide new insights into EOPD drug mechanisms and identify promising therapeutic candidates, potentially leading to more effective, personalized treatment approaches for EOPD patients.

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Publication Details

Journal
Scientific Reports
Published
2025-03-27
DOI
https://doi.org/10.1038/s41598-024-83178-w
Citations
1
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
1.39
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article

Network based approach for drug target identification in early onset Parkinson’s disease

Mrittika Chakraborty, Ashmita Dey, Ujjwal Maulik, Sanghamitra Bandyopadhyay
1 citations
Scientific Reports
Parkinson's Disease Mechanisms and Treatments
1.39
article

Network based approach for drug target identification in early onset Parkinson’s disease

Mrittika Chakraborty, Ashmita Dey, Ujjwal Maulik, Sanghamitra Bandyopadhyay
article en
1 citations

Abstract

Despite the abundance of large-scale molecular and drug-response data, current research on early-onset Parkinson's disease (EOPD) markers often lacks mechanistic interpretations of drug-gene relationships, limiting our understanding of how drugs exert their therapeutic effects. While existing studies provide valuable EOPD markers, the mechanisms by which targeted drugs act remain poorly understood. We propose DTI-Prox, a novel workflow that identifies potentially overlooked EOPD markers and suggests relevant drug targets. DTI-Prox employs network proximity to measure how closely connected a drug and gene are within a biological network. Additionally, node similarity, which assesses the functional resemblance between network nodes, reveals meaningful drug-gene connections. DTI-Prox identifies 417 novel drug-target pairs and four previously unreported EOPD markers (PTK2B, APOA1, A2M, and BDNF), demonstrating significant pathway enrichment in neurodegenerative processes. Notably, shared pathway analysis shows that prioritized drugs such as Amantadine, Apomorphine, Atropine, Benztropine, Biperiden, Bromocriptine, Cabergoline, Carbidopa, and Citalopram, currently used for other conditions, interact with key EOPD-associated diagnostic markers, suggesting their potential for drug repurposing. The constructed functional network's validity is reinforced by statistically significant drug-target pairs. The findings provide new insights into EOPD drug mechanisms and identify promising therapeutic candidates, potentially leading to more effective, personalized treatment approaches for EOPD patients.

Scientific ReportsVol. 15(1)
Jadavpur University (IN), Indian Statistical Institute (IN)
Good health and well-being
Openalex Percentile: Top 22%
Parkinson's Disease Mechanisms and Treatments
1.39
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