Designing PPI inhibitors is challenging because they have distinct molecular properties and occupy regions of chemical space differently from conventional small-molecule drugs . For instance, PPI inhibitors are larger, more hydrophobic, have more aromatic rings, and have distinct three-dimensional conformations compared to traditional small-molecule drugs . In general, the properties of PPI inhibitors are significantly different from traditional drug candidates . In recent years, significant efforts have been made to develop PPI inhibitors , resulting in many PPI inhibitors in clinical trials (Figure ). An example is apabetalone, which has progressed to phase III clinical trials to prevent major adverse cardiovascular events in high-risk type 2 diabetes mellitus patients. Idasanutlin is being tested in clinical trials to treat neoplasia and leukemias . Another representative example is Venetoclax: a BCL-2 inhibitor approved for clinical use to treat chronic lymphocytic leukemia and certain types of small lymphocytic lymphoma (Figure ). Different compound databases of PPI inhibitors have been created. For example, TIMBAL , the Inhibitors of Protein-Protein Interaction Database (iPPI-DB) , the Fr-PPIChem, and the databases reviewed therein . This has been possible thanks to the use of computational techniques ,