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Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study

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Abstract

Activity cliffs (ACs) are defined as closely analogous compounds of significant affinity discrepancies against certain biotarget. In this paper we propose to use AC pair(s) for extracting valid binding pharmacophores through exposing corresponding protein complexes to stochastic deformation/relaxation followed by applying genetic algorithm/machine learning (GA-ML) for selecting optimal pharmacophore(s) that best classify a long list of inhibitors. We compared the performances of ligand-based and structure-based pharmacophores with counterparts generated by this newly introduced technique. Sphingosine kinase 1 (SPHK-1) was used as case study. SPHK-1 is a lipid kinase that plays pivotal role in the regulation of a variety of biological processes including, cell growth, apoptosis, and inflammation. The new approach proved to yield pharmacophore and ML models of comparable accuracies to established ligand-based and structure-based pharmacophores. The resulting pharmacophores and ML models were used to capture hits from the national cancer institute list of compounds and predict their bioactivity categories. Two hits of novel chemotypes showed selective and low micromolar inhibitory IC50 values against SPHK-1.

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Acknowledgements

The authors thank the Deanship of Scientific Research at the University of Jordan for funding this project. The authors are also indebted for the Science Research Fund / Jordan Ministry of Higher Education for their generous grant.

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, Faculty of Pharmacy, University of Jordan, Amman, 11942, Jordan

    Lubabah A. Mousa & Mutasem Taha

  2. Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, The Hashemite University, PO Box 330127, Zarqa, 13133, Jordan

    Ma’mon M. Hatmal

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  1. Lubabah A. Mousa
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Mousa, L.A., Hatmal, M.M. & Taha, M. Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study. J Comput Aided Mol Des 36, 39–62 (2022). https://doi.org/10.1007/s10822-021-00435-0

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