Targeting the Hsp90 interactome using in silico polypharmacology approaches

In recent years, polypharmacology has gained popularity in drug discovery. [1] Especially for complex diseases such as cancer, the ability of a drug to bind to and interfere with multiple targets provides new opportunities for therapeutic intervention In this article, we focus on Hsp90 and its interactome, whose pivotal role in survival and proliferation of cancer cells renders this array of targets particularly attractive polypharmacological drug design strategies. The primary goal of our work is the identification and selection of suitable target proteins from the interactome that might be combined with Hsp90 to explore and exploit a multi-target inhibition approach. This task is accomplished by applying computational methods to mine the structural and biological information associated with potential ligands in public databases and assess the degree of structural similarity between known inhibitors of different targets. Therefore, we propose an integrated ligand- and structure-based approach to select small molecules from databases suitable for consideration as multi-target inhibitors

The use of 2D fingerprint methods to support the assessment of structural similarity in orphan drug legislation.

In the European Union, medicines are authorised for some rare disease only if they are judged to be dissimilar to authorised orphan drugs for that disease. This paper describes the use of 2D fingerprints to show the extent of the relationship between computed levels of structural similarity for pairs of molecules and expert judgments of the similarities of those pairs. The resulting relationship can be used to provide input to the assessment of new active compounds for which orphan drug authorisation is being sought