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

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BORIS DOI
10.48350/177637
Publisher DOI
10.2533/chimia.2022.1045
Description
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/.
Date of Publication
2022-12-21
Publication Type
Magazine Article
Subject(s)
500 - Science::570 - Life sciences; biology
500 - Science::540 - Chemistry
600 - Technology::610 - Medicine & health
Language(s)
en
Contributor(s)
Reymond, Jean-Louisorcid-logo
DCBP Gruppe Prof. Reymond
Departement für Chemie, Biochemie und Pharmazie (DCBP) Universität Bern
Additional Credits
DCBP Gruppe Prof. Reymond
Series
CHIMIA
Publisher
Swiss Chemical Society
ISSN
0009-4293
Access(Rights)
open.access
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