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PLoS ONEBioinformaticsPeer-reviewed journal article

Structure-based drug repositioning explains ibrutinib as VEGFR2 inhibitor

Melissa F. AdasmeiD, Daniele ParisiiD, Kristien Van BelleiD, Sebastian SalentiniD, V. Joachim HauptiD, Gary S. Jennings, Jörg C. Heinrich, Jean HermaniD, Ben SprangersiD, Thierry LouatiD, Yves MoreauiD, Michael SchroederiD

PDFDOIPreprint

Abstract

Many drugs are promiscuous and bind to multiple targets. On the one hand, these targets may be linked to unwanted side effects, but on the other, they may achieve a combined desired effect (polypharmacology) or represent multiple diseases (drug repositioning). With the growth of 3D structures of drug-target complexes, it is today possible to study drug promiscuity at the structural level and to screen vast amounts of drug-target interactions to predict side effects, polypharmacological potential, and repositioning opportunities. Here, we pursue such an approach to identify drugs inactivating B-cells, whose dysregulation can function as a driver of autoimmune diseases. Screening over 500 kinases, we identified 22, whose knock out impeded the activation of B-cells. Among these 22 is the gene KDR, whose gene product VEGFR2 is a prominent cancer target with anti-VEGFR2 drugs on the market for over a decade. The main result of this paper is that structure-based drug repositioning for the identified kinase targets identified the cancer drug ibrutinib as micromolar VEGFR2 inhibitor with a very high therapeutic index in B-cell inactivation. These findings prove that ibrutinib is not only acting on the Brutons tyrosine kinase BTK, against which it was designed. Instead, it may be a polypharmacological drug, which additionally targets angiogenesis via inhibition of VEGFR2. Therefore ibrutinib carries potential to treat other VEGFR2 associated disease. Structure-based drug repositioning explains ibrutinibs anti VEGFR2 action through a specific pattern of interactions shared between BTK and VEGFR2. Overall, structure-based drug repositioning was able to predict these findings at a fraction of the time and cost of a conventional screen.

Citations
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FWCI
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top 8%

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