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

Authors

DOI:

https://doi.org/10.2533/chimia.2022.1045

Keywords:

Chemical space, Drug discovery, Molecular similarity, Polypharmacology, Virtual screening

Abstract

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 reflecting 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/.

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Published

2022-12-21

How to Cite

[1]
J.-L. Reymond, Chimia 2022, 76, 1045, DOI: 10.2533/chimia.2022.1045.