Conventional drug discovery requires identifying a protein target believed to be important for
disease mechanism and screening compounds for those that beneficially alter the target’s function.
While this approach has been an effective one for decades, recent data suggest that its continued
success is limited largely owing to the essential irreducibility of biologically complex systems that
govern disease phenotype to a single primary disease driver. Moreover, bioinformatic analysis
suggests that each approved drug can theoretically bind to ~32 targets, supporting the notion that
many existing drugs can be repurposed for the treatment of (many) other diseases. Network
medicine, a new discipline that applies network science and systems biology to the analysis of
complex biological systems and disease, offers a novel approach to overcoming these limitations of
conventional drug discovery, and dissecting the complexity implicit in the pluripotency of many drug
compounds. Using the comprehensive protein-protein interaction network (interactome) as the
template through which subnetworks that govern specific diseases are identified; potential disease
drivers are unveiled; and the effect of repurposed drugs, identified from network features,
physicochemical compound features, and machine learning- and artificial intelligence-based
analyses, are studied. This approach to drug discovery offers new and exciting unbiased
possibilities for advancing our knowledge of disease mechanisms and precision therapeutics.
27/10/2022
27 ottobre 2022, alle ore 11.00, Aula A del
Dipartimento di Chimica e tecnologie del farmaco (Edificio CU019)