Privileged Substructures to Modulate Protein–Protein Interactions

Given
the difficulties to identify chemical probes that can modulate protein–protein
interactions (PPIs), actors in the field have started to agree on
the necessity to use PPI-tailored screening chemical collections.
However, which type of scaffolds may promote the binding of compounds
to PPI targets remains unclear. In this big data analysis, we have
identified a list of privileged chemical substructures that are most
often observed within inhibitors of PPIs. Using molecular frameworks
as a way to perceive chemical substructures with the combination of
an experimental and a machine-learning based predicted data set of
iPPI compounds, we propose a list of privileged substructures in the
form of scaffolds and chemical moieties that can be substantially
chemically functionalized and do not present any toxicophore nor pan-assay
interference (PAINS) alerts. We think that such chemical guidance
will be valuable for medicinal chemists in their attempt to identify
initial quality chemical probes on PPI targets.