Large-Scale Computational Screening Identifies First in Class Multitarget Inhibitor of EGFR Kinase and BRD4
Inhibition of cancer-promoting kinases is an established therapeutic strategy for the treatment of many cancers, although resistance to kinase inhibitors is common. One way to overcome resistance is to target orthogonal cancer-promoting pathways. Bromo and Extra-Terminal (BET) domain proteins, which belong to the family of epigenetic readers, have recently emerged as promising therapeutic targets in multiple cancers. The development of multitarget drugs that inhibit kinase and BET proteins
... fore may be a promising strategy to overcome tumor resistance and prolong therapeutic efficacy in the clinic. We developed a general computational screening approach to identify novel dual kinase/bromodomain inhibitors from millions of commercially available small molecules. Our method integrated machine learning using big datasets of kinase inhibitors and structure-based drug design. Here we describe the computational methodology, including validation and characterization of our models and their application and integration into a scalable virtual screening pipeline. We screened over 6 million commercially available compounds and selected 24 for testing in BRD4 and EGFR biochemical assays. We identified several novel BRD4 inhibitors, among them a first in class dual EGFR-BRD4 inhibitor. Our studies suggest that this computational screening approach may be broadly applicable for identifying dual kinase/BET inhibitors with potential for treating various cancers. Kinase inhibitors have been identified for the treatment of various cancers 1,2 . However, compensatory mechanisms diminish the long-term efficacy of these inhibitors 3 . Drug resistance is often observed in the clinic as rapidly dividing cancer cells are able to avoid inhibition by a single targeted therapy through a variety of mechanisms 4 . The resistance of tumors toward kinase-directed therapeutics is often accompanied by a distinct change in signaling network composition through adaptive kinome reprogramming, allowing the tumor to elude effects of the drug and manifest resistance 5 . An established strategy to improve the durability of clinical responses to targeted therapies is to simultaneously inhibit multiple cancer-driving kinases. However, discovering kinase inhibitors with an appropriate multitarget profile has been challenging and necessitated the application of combination therapies, which can pose major clinical development challenges 6-9 . We therefore sought a strategy to identify single agent polypharmacological 1 compounds with the ability to target multiple cancer promoting pathways, but that does not rely on inhibiting multiple kinases. We chose to target epidermal growth factor receptor (EGFR) along with the epigenetic reader bromodomain-containing protein 4 (BRD4). EGFR is a receptor tyrosine kinase (RTK) that is amplified or mutated in several cancers and is the subject of intensive drug discovery efforts 10-12 . Similarly, BET bromodomain proteins have recently emerged as possible drug targets in multiple cancers. BET proteins are epigenetic readers that primarily recognize acetylated lysine residues on histones, and function in regulating gene transcription 13 . Their role in modulating chromatin structure is important for proper cellular function and expression of genes involved in multiple signaling pathways. BET proteins have been implicated in cancer cell proliferation by controlling the activity of various oncogenes required for cell cycle progression 14 . BRD4 is possibly the best-characterized BET protein, which contains two regions that bind acetylated lysine residues termed bromodomains, Bromodomain 1 (BRD4(1)) and Bromodomain 2 (BRD4 (2) ). Both domains bind to acetylated histones primarily through interactions in the ZA loop and BC loop-helix junctions of BRD4(1) and BRD4(2) 15 . Highly selective small molecules are able to displace these bromodomains from chromatin; thereby reducing transcription of oncogenes, such as MYC. Several small molecule BRD4 inhibitors have been developed, which show efficacy in reducing growth of multiple tumors in vivo and are in clinical trials for the treatment of solid tumors 16, 17 . Thus, BRD4 is a promising drug target for the treatment of various cancers. Interestingly, some known kinase inhibitors potently inhibit BRD4, suggesting that the therapeutic efficacy of these compounds may be due in part to BRD4 inhibition 18, 19 . In addition, use of the BRD4 inhibitor JQ1 in combination with the EGFR inhibitor lapatinib has been shown to suppress lapatinib-induced kinome reprogramming in ERBB2+ breast cancer cells, where other kinase inhibitor combinations could not 5 . This knowledge-based rationale is also supported by data from the Library of Integrated Network-based Cellular Signatures (LINCS, http://www.lincsproject.org/). We show that transcriptional response signatures of known EGFR and BRD4 compounds are distinct from one another as well as from a background population, suggesting that EGFR and BRD4 inhibitors utilize orthogonal signaling networks and different transcription factors, therefore supporting the idea of prolonged efficacy and reduced resistance when using a compound that targets both proteins. To identify such dual inhibitors we describe a large-scale computational screening pipeline, which leads to the discovery of novel BRD4 inhibitors and a first in class multitarget EGFR and BRD4 inhibitor. We suggest that this virtual screening protocol can be adopted across the human Kinome for identifying dual kinase-BRD4 inhibitors.