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Peer-Reviewed Publication
Comput Struct Biotechnol J2026;31289-300.January 1, 2026Journal Article

Systematic discovery of disease-modifying targets by prediction from knowledge graph-based AI model and experimental validation: Parkinson's disease case.

Minyoung So1, Soo Jung Park2, Dongin Kim1, Seokjin Han1, Hee Jung Koo1, Taeyong Kim1, Min-Gi Shin2, Eun Jeong Lee2,3,4
1Standigm Inc., Seoul 06261, Republic of Korea.
2Department of Brain Science, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
3Department of Biomedical Science, Graduate School of Ajou University, Suwon 16499, South Korea.
4BK21 R&E Initiative for Advanced Precision Medicine, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
PubMed PMC DOI PDF

Abstract

The development of disease-modifying therapies (DMTs) for Parkinson's disease (PD) remains a critical unmet need. Despite extensive research efforts, no therapy capable of slowing or halting PD progression has been approved. Here, we apply a knowledge graph-based artificial intelligence (AI) framework, combined with subgraph-level enrichment-based re-prioritization, to identify novel PD-modifying…

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