Automated design of ligands to polypharmacological profiles
Open accessAbstract
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.
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- Authors
- Besnard, J., Ruda, G. F., Setola, V., Abecassis, K., Rodriguiz, R. M., Huang, X.-P., Norval, S., Sassano, M. F., Shin, A. I., Webster, L. A., Simeons, F. R. C., Stojanovski, L., Prat, A., Seidah, N. G., Constam, D. B., Bickerton, G. R., Read, K. D., Wetsel, W. C., Gilbert, I. H., Roth, B. L., & Hopkins, A. L.
- Affiliations
- University of Dundee (GB)
- University of North Carolina at Chapel Hill (US)
- Duke University (US)
- Montreal Clinical Research Institute (CA)
- École Polytechnique Fédérale de Lausanne (CH)
- Corresponding author
- Roth, Bryan L.
- Hopkins, Andrew L.
- ORCID
- Venue
- Nature
- Published
- 2012-12
- Volume
- 492
- Issue
- 7428
- Pages
- 215-220
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3653568
- OpenAlex
- W2034475831
- Cited by
- 832
- References
- 59
- Citations by year
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- FWCI
- 58.04
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
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- UNC Libraries
- Funders
- University of Dundee
- Wellcome Trust (WT 083481, 083481)
- National Institutes of Health
- Biotechnology and Biological Sciences Research Council (BB/J010510/1, BB/FOF/PF/15/09)
- National Institute of Mental Health (U19MH082441, MH082441, R01MH061887)
- National Institute on Drug Abuse (R01DA017204)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Medicine › Pharmacology › Cholinesterase and Neurodegenerative Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
- Keywords
- polypharmacology, multi-target drug design, G protein-coupled receptors, acetylcholinesterase inhibitors, target engagement, drug selectivity, adaptive design
- MeSH terms
- Pharmacological Phenomena, Animals, Automation, Female, Ligands, Male, Mice, Inbred C57BL, Models, Theoretical, Drug Design, Reproducibility of Results, Drug Delivery Systems, Mice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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