Decoding Early Parkinson's: A Network-Based Approach to Drug Target Identification

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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 interpretation of drug-gene relationships. This limits 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 addresses these limitations by identifying potentially overlooked EOPD markers and suggesting relevant drug targets. DTI-Prox utilizes network proximity and node similarity to identify functionally relevant connections between drugs and genes. The constructed functional network's validity is further strengthened by statistically significant drug-target pairs. Finally, DTI-Prox prioritizes drug-target pairs based on shared pathway analysis, paving the way for target discovery, drug repurposing, and patient stratification strategies. This approach holds promise for advancing our understanding of EOPD treatment efficacy and potentially leading to improved therapeutic strategies.

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