Molecular descriptors have been used to characterize and predict the functions of small molecules, including inhibitors of protein–protein interactions (iPPIs). Such molecules are valuable to investigate disease pathways and as starting points for drug discovery endeavors. iPPIs tend to bind at the surface of macromolecules and the design of such compounds remains challenging. Here, we report on our investigation of a pool of interpretable molecular descriptors for solvent-exposed and buried co-crystallized ligands. Several descriptors were found to be significantly different between the two classes and were further exploited using machine-learning approaches. This work could open new perspectives for the rational design of focused libraries enriched in new types of small drug-like molecules that could be used to prevent PPIs.

Analysis of solvent-exposed and buried co-crystallized ligands: a case study to support the design of novel protein–protein interaction inhibitors

Trisciuzzi, Daniela;Nicolotti, Orazio;
2019-01-01

Abstract

Molecular descriptors have been used to characterize and predict the functions of small molecules, including inhibitors of protein–protein interactions (iPPIs). Such molecules are valuable to investigate disease pathways and as starting points for drug discovery endeavors. iPPIs tend to bind at the surface of macromolecules and the design of such compounds remains challenging. Here, we report on our investigation of a pool of interpretable molecular descriptors for solvent-exposed and buried co-crystallized ligands. Several descriptors were found to be significantly different between the two classes and were further exploited using machine-learning approaches. This work could open new perspectives for the rational design of focused libraries enriched in new types of small drug-like molecules that could be used to prevent PPIs.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/227155
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