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Artificial Intelligence Recognizes β-Lapachone as an Allosteric 5- Lipoxygenase Inhibitor

submitted on 26.03.2018 and posted on 27.03.2018 by Gonçalo Bernardes, Tiago Rodrigues, Markus Werner, Jakob Roth, Eduardo H. G. da Cruz, Marta C. Marques, Susana A. Lobo, Andreas Koeberle, Francisco Corzana, Eufrânio N. da Silva Júnior, Oliver Werz

Chemical matter with often-discarded moieties entails opportunities for drug discovery. Relying on orthogonal ligand-centric machine learning methods, targets were consensually identified as potential counterparts for the fragment-like natural product β-lapachone. Resorting to a comprehensive range of biophysical and biochemical assays, the natural product was validated as a potent, ligand efficient, allosteric and reversible modulator of 5-lipoxygenase (5-LO). Moreover, we provide a rationale for 5-LO-inhibiting chemotypes inspired in the β-lapachone scaffold through a focused analogue library. This work demonstrates the power of artificial intelligence technologies to deconvolute complex phenotypic readouts of clinically relevant chemical matter, leverage natural product-based drug discovery, as an alternative and/or complement to chemoproteomics and as a viable approach for systems pharmacology studies.


FCT Portugal, European Commission, MRC, EPSRC, CNPq Brazil, Ministerio de Economia y Competitividad, CESGA, RSC, CAPES, FAPEMIG, Deutsche Forschungsgemeinschaft SFB1127 ChemBioSys, Royal Society and European Research Council.


Email Address of Submitting Author

Email Address(es) for Other Author(s)


Instituto de Medicina Molecular, Lisboa and Department of Chemistry, University of Cambridge


Portugal and UK

ORCID For Submitting Author


Declaration of Conflict of Interest

T.R. and G.J.L.B. are listed as inventors on a pending patent application related to technology described in this work.