Evidence-based successful example of a structure-based approach for the prediction of designer fentanyl-like molecules
In 2019, we published three innovative quantitative structure-activity relationship models (QSAR) for predicting the affinity of mu-opioid receptor (µOR) ligands. The three different models were then combined to produce a consensus model used to explore the chemical landscape of 3000 virtual fentany...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Emerging Trends in Drugs, Addictions, and Health |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667118224000023 |
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| Summary: | In 2019, we published three innovative quantitative structure-activity relationship models (QSAR) for predicting the affinity of mu-opioid receptor (µOR) ligands. The three different models were then combined to produce a consensus model used to explore the chemical landscape of 3000 virtual fentanyl-like structures, also generated by us by a theoretical scaffold-hopping approach to explore potential novel active substances and predict their activity. Interestingly, five years have passed, and some of the virtual predicted compounds have been identified/reported to e.g. the EU Early Warning System or the United Nations Office on Drugs and Crime, thus confirming our warning hypothesis that new emerging drugs from our screen would find way to the market. |
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| ISSN: | 2667-1182 |