Access to all possible and tangible compounds bearing a particular substructure benefits several application scenarios in modern drug discovery:
- Fragment-based drug discovery campaigns can mine relevant chemistry with the motif of a confirmed binder to efficiently select candidates for a follow-up.
- Typically, a QSAR analysis suggests a pharmacophore, which can then serve as a substructure to identify potential candidates to further investigate the pharmacological effects of decorated analogs.
- Machine learning and AI methods rely on relevant input. SpaceMACS and Motif Matcher retrieve compounds that are synthetically accessible and are therefore valuable sources for the creation of data sets.
- Sometimes we can't see the forest for the trees. As a medicinal chemist you might be surprised about the kind of results that may be retrieved as your next lead structure when searching in trillions of compounds or beyond.
The combination of access to the largest reservoirs of compounds and computational post-processing (e.g., docking, ligand-based methods, machine learning, you name it) can therefore significantly amplify the success rate of different research projects.