Evidence-based successful example of a structure-based approach for the prediction of designer fentanyl-like molecules

Giuseppe Floresta, Valeria Catalani, Vincenzo Abbate

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Abstract

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.
Original languageEnglish
Article number100143
Pages (from-to)1-6
Number of pages6
JournalEmerging Trends in Drugs, Addictions and Health
Volume4
Early online date1 Mar 2024
DOIs
Publication statusE-pub ahead of print - 1 Mar 2024

Keywords

  • Designer fentanyl-like molecules
  • Fentanyl
  • New psychoactive substances
  • Novel synthetic opioids
  • Opioid binding affinity
  • QSAR
  • µOR

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