In silico identification of potential druggable binding sites on CIN85 SH3 domain

Protein-protein interactions (PPIs) play a pivotal role in the regulation of many physiological processes. The dysfunction of some PPIs interactions led to the alteration of different biological pathways causing various diseases including cancer. In this context, the inhibition of PPIs represents an attractive strategy for the design of new antitumoral agents. In recent years, computational approaches were successfully used to study the interactions between proteins, providing useful hints for the design of small molecules able to modulate PPIs. Targeting PPIs presents several challenges mainly due to the large and flat binding surface that lack the typical binding pockets of traditional drug targets. Despite these hurdles, substantial progress has been made in the last decade resulting in the identification of PPI modulators where some of them even found clinical use. This study focuses on MUC1-CIN85 PPI which is involved in the migration and invasion of cancer cells. Particularly, we investigated the presence of druggable binding sites on the CIN85 surface which provided new insights for the structure-based design of novel MUC1-CIN85 PPI inhibitors as anti-metastatic agents.