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Understanding diseases is difficult due to a lack of insight into the underlying biological mechanisms, resulting in imprecise treatments based solely on symptoms. Disease modules offer distinct perspectives on complex diseases and establish a basis for mechanistic drug repurposing. However, disease module inference does not pay attention to pathway annotations. Since drug repurposing aims to hint at biological pathways, this information is crucial and should be considered when exploring the underlying mechanisms within protein-protein interaction networks. Drugst.One, a versatile web tool for disease module visualization and drug repurposing, does not offer pathway enrichment and visualization. To enable the assessment of functionally connected subnetworks within these modules, we extended Drugst.One with functionality for investigating enriched pathways and the option to add closely connected nodes to the initial disease module. Our extension for Drugst.One supports genesets from KEGG, Reactome, and WikiPathways. The workflow can be initiated with Louvain clustering to perform pathway enrichment on the network clusters. The layout function arranges the nodes illustrating the cellular components of the module, thereby aiding in the identification of pivotal proteins within pathways. This advancement contrasts previous methods by providing a user-friendly approach for comprehensive pathway analysis and module refinement within the Drugst.One framework suited for expert curation. Contributing to the broader context of computational drug repurposing and disease module interpretation, this extension offers a streamlined approach for assessing pathway involvement and functional refinement within disease modules.
Spindler et al. (Thu,) studied this question.
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