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Discovery of a nanomolar glyoxalase-I inhibitor using integrated ligand-based pharmacophore modeling and molecular docking

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Abstract

The glyoxalase system, which is composed of two zinc metalloenzymes, glyoxalase I (GLO-I) and glyoxalase II (GLO-II) and a catalytic amount of GSH, has a pivotal role in the detoxification of cytotoxic methylglyoxal (MG), a glycolytic side product. Recent studies have revealed the overexpression of GLO-I in various cancer types such as breast carcinoma, invasive bladder, colon, prostate, and lung cancers. Consequently, GLO-I has become a validated target for the development of novel anticancer agents. In this study we were aiming to identify potent GLO-I inhibitors as potential candidates for the development of effective anticancer therapeutics using an integrated ligand- and structure-based drug design approach. A set of selective pharmacophore models was generated using an in-house tested set of flavonoids and used in virtual screening of Maybridge and Aldrich databases, collectively containing more than 64,000 compounds. Filtration of retained hits resulted in 362 compounds that were docked into the active site of the GLO-I enzyme. Then, the top 30% of docked compounds were visually inspected and 32 compounds were purchased and biologically evaluated. Five compounds showed good to excellent inhibitory activities with the most active one (compound 14, ID number ST018515) showing an IC50 of 336 nM. A high hit rate of actives implies the success of our approach. The five active compounds with considerable structural diversity were identified as novel leads that can be further optimized towards designing potent GLO-I inhibitors.

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Acknowledgements

The authors wish to thank the Deanship of Scientific Research at Jordan University of Science and Technology for financial support (grant number 20170276).

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Correspondence to Nizar A. Al-Shar’i.

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Al-Shar’i, N.A., Al-Rousan, E.K., Fakhouri, L.I. et al. Discovery of a nanomolar glyoxalase-I inhibitor using integrated ligand-based pharmacophore modeling and molecular docking. Med Chem Res 29, 356–376 (2020). https://doi.org/10.1007/s00044-019-02486-3

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Keywords

  • Glyoxalase-I
  • Zinc Binding
  • Anticancer
  • Ligand-based pharmacophore modeling
  • Molecular docking