Identification and Biological Evaluation of CK2 Allosteric Fragments through Structure-Based Virtual Screening

Abstract

Casein kinase II (CK2) is considered as an attractive cancer therapeutic target, and recent efforts have been made to develop its ATP-competitive inhibitors. However, achieving selectivity with respect to related kinases remains challenging due to the highly conserved ATP-binding pocket of kinases. Allosteric inhibitors, by targeting the much more diversified allosteric site relative to the highly conserved ATP-binding pocket, might be a promising strategy with the enhanced selectivity and reduced toxicity than ATP-competitive inhibitors. The previous studies have highlighted the traditional serendipitousity of discovering allosteric inhibitors owing to the complicate allosteric modulation. In this current study, we identified the novel allosteric inhibitors of CK2α by combing structure-based virtual screening and biological evaluation methods. The structure-based pharmacophore model was built based on the crystal structure of CK2α-compound 15 complex. The ChemBridge fragment library was searched by evaluating the fit values of these molecules with the optimized pharmacophore model, as well as the binding affinity of the CK2α-ligand complexes predicted by Alloscore web server. Six hits forming the holistic interaction mechanism with the αD pocket were retained after pharmacophore- and Alloscore-based screening for biological test. Compound 3 was found to be the most potent non-ATP competitive CK2α inhibitor (IC50 = 13.0 μM) with the anti-proliferative activity on A549 cancer cells (IC50 = 23.1 μM). Our results provide new clues for further development of CK2 allosteric inhibitors as anti-cancer hits.

Chemical probes targeting the kinase CK2: a journey outside the catalytic box

“…97 However, there has been one report of an inhibitor that is proposed to bind in the αD site allosterically inhibiting CK2α. 98 Unfortunately, there is currently no structural data confirming that this compound binds in the αD site. Therefore, no reliable conclusions can be drawn from this data as to whether the αD site alone can be used as an allosteric site.…”

“…11) was identified as the most promising non-ATP competitive inhibitor of CK2α with an IC 50 of 13.0 μM and it was shown to stop the proliferation of A549 cancer cells (GI 50 of 23.1 μM). 98 The authors found that the IC 50 value did not depend on the concentration of ATP used and concluded that such a compound was acting via a non-ATP-competitive mechanism. Computational studies suggested the compound was binding in the αD pocket, 98 but this is still to be demonstrated experimentally.…”

Recent Advances in the Discovery of CK2 Allosteric Inhibitors: From Traditional Screening to Structure-Based Design

“…Competition experiments further confirmed that CAM4712 was the potent and selective allosteric inhibitor by binding in the αD pocket without facilitatingcellular uptake. Besides the above mentioned αD-site binding inhibitors CAM4066 and CAM4712, our group identified the novel allosteric inhibitors of CK2α using the pharmacophore model and Alloscore-based virtual screening of ChemBridge fragment library [39]. By considering the filtration of fit values > 2.5 with the αD pocket pharmacophore model, as well as the Alloscore value of 5.8, compound 11 combined with the uracil group was discovered to be an allosteric inhibitor of CK2α (IC50 = 13.0 μM), which is similar to that of CAM4712.…”

Understanding the P-Loop Conformation in the Determination of Inhibitor Selectivity Toward the Hepatocellular Carcinoma-Associated Dark Kinase STK17B

“…Despite the inspiring clinical benefits, kinase inhibitors are still encountered an unsurmountable challenge hallmarked by kinase selectivity profile. This is because that the vast majority of protein kinase inhibitors bind to the conserved ATP-binding site, leading to the poor selectivity of kinase inhibitors towards a unique kinase ( Wu et al, 2015 ; Chen et al, 2020 ; Li C. et al, 2020 ). For example, Davis et al (2011) have previously explored the interaction of 72 kinase inhibitors with 442 kinases representing >80% of the human catalytic protein kimome and found that the kinase inhibitor selectivity profile is relatively narrow, with 10%–40% of inhibitors interacting with >60% of kinases, and each inhibitor interacting with more than one kinase.…”