In silico repurposing approach to elucidate novel drug treatments for multiple sclerosis

Resumen

Multiple Sclerosis (MS) is a chronic, neurodegenerative disease marked by demyelination of neurons, the formation of plaques in the central nervous system, and progressive neurological disability. Although treatments exist for relapsing forms of MS, there remains a significant unmet need for therapies that can promote myelin regeneration, improve patient quality of life, and slow disease progression. This thesis investigates in silico drug repurposing as a strategy for identifying novel therapeutic candidates for MS, leveraging hypotheses generated by the DRIVE platform, a network-based medicine tool that integrates phenotypic, biological, and pharmacological data to suggest potential drug-disease relationships.

Two distinct pathways from DRIVE were examined: the gene-disease-drug pathway and the gene-protein-drug pathway, from which paclitaxel and isotretinoin were selected as candidate compounds. A multi-step filtering process, including Gene Ontology-based filtering, proteinprotein interaction considerations, literature support, and structural availability, was used to prioritize the potential targets. Molecular docking was then conducted to evaluate the binding
affinity of drug-target pairs.

Among the final candidates, docking analysis suggested that NLRP3 may serve as an alternative and therapeutically relevant target of paclitaxel in the context of MS. While these findings are preliminary and require further validation through molecular dynamics simulations and experimental studies, this work demonstrates the potential of combining network medicine approaches with structure-based drug repurposing tools to discover new therapies for diseases such as MS.