Cocrystals of Praziquantel: Discovery by Network-Based Link Prediction

Cocrystallization has been promoted as an attractive early development tool as it can change the physicochemical properties of a target compound and possibly enable the purification of single enantiomers from racemic compounds. In general, the identification of adequate cocrystallization candidates (or coformers) is troublesome and hampers the exploration of the solid-state landscape. For this reason, several computational tools have been introduced over the last two decades. In this study, cocrystals of Praziquantel (PZQ), an anthelmintic drug used to treat schistosomiasis, are predicted with network-based link prediction and experimentally explored. Single crystals of 12 experimental cocrystal indications were grown and subjected to a structural analysis with single-crystal X-ray diffraction. This case study illustrates the power of the link-prediction approach and its ability to suggest a diverse set of new coformer candidates for a target compound when starting from only a limited number of known cocrystals.

Automated summary

Cocrystallization is considered an attractive early development tool that can alter the properties of a target compound and potentially isolate single enantiomers. However, finding suitable cocrystallization candidates has been a challenge, leading to the introduction of computational tools in the last two decades. This study highlights the efficacy of link prediction in suggesting new coformer candidates for a target compound based on a limited number of known cocrystals.