Molecular Similarity for Drug Discovery, Target Prediction and Chemical Space Visualization

Similar drug molecules often have similar properties and activities. Therefore, quantifying molecular similarity is central to drug discovery and optimization. Here I review computational methods using molecular similarity measures developed in my group within the interdisciplinary network NCCR TransCure investigating the physiology, structural biology and pharmacology of ion channels and membrane transporters. We designed a 3D molecular shape and pharmacophore comparison algorithm to optimize weak and unselective inhibitors by scaffold hopping and discovered potent and selective inhibitors of the ion channels TRPV6 and TRPM4, of endocannabinoid membrane transport, and of the divalent metal transporters DMT1 and ZIP8. We predicted off-target effects by combining molecular similarity searches from different molecular fingerprints against target annotated compounds from the ChEMBL database. Finally, we created interactive chemical space maps reflect-ing molecular similarities to facilitate the selection of screening compounds and the analysis of screening results. These different tools are available online at https://gdb.unibe.ch/tools/.

Automated summary

Quantifying molecular similarity is crucial in drug discovery and optimization. This review focuses on computational methods developed in the NCCR TransCure interdisciplinary network for studying physiology, structural biology, and pharmacology of ion channels and membrane transporters. The review highlights the use of molecular similarity measures in scaffold hopping, predicting off-target effects, and creating chemical space maps.