Automated design of ligands to polypharmacological profiles.
The clinical efficacy and safety of a drug is determined by its activity profile across many proteins in the proteome. However, designing drugs with a specific multi-target profile is both complex and difficult. Therefore methods to design drugs rationally a priori against profiles of several proteins would have immense value in drug discovery. Here we describe a new approach for the automated design of ligands against profiles of multiple drug targets. The method is demonstrated by the evolution of an approved acetylcholinesterase inhibitor drug into brain-penetrable ligands with either specific polypharmacology or exquisite selectivity profiles for G-protein-coupled receptors. Overall, 800 ligand-target predictions of prospectively designed ligands were tested experimentally, of which 75% were confirmed to be correct. We also demonstrate target engagement in vivo. The approach can be a useful source of drug leads when multi-target profiles are required to achieve either selectivity over other drug targets or a desired polypharmacology.
Duke Scholars
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- Reproducibility of Results
- Pharmacological Phenomena
- Models, Theoretical
- Mice, Inbred C57BL
- Mice
- Male
- Ligands
- General Science & Technology
- Female
- Drug Design
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Reproducibility of Results
- Pharmacological Phenomena
- Models, Theoretical
- Mice, Inbred C57BL
- Mice
- Male
- Ligands
- General Science & Technology
- Female
- Drug Design