Large-Scale Computational Screening Identifies First in Class Multitarget Inhibitor of EGFR Kinase and BRD4
Autor: | Stephan C. Schürer, Saurabh Mehta, Nagi G. Ayad, Stewart W. J. Ember, Bryce K. Allen, Ernst Schönbrunn |
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Rok vydání: | 2015 |
Předmět: |
Drug
BRD4 media_common.quotation_subject Antineoplastic Agents Cell Cycle Proteins Computational biology Bioinformatics Article Machine Learning 03 medical and health sciences 0302 clinical medicine Neoplasms Humans Medicine Molecular Targeted Therapy Epigenetics Protein Kinase Inhibitors 030304 developmental biology Therapeutic strategy media_common 0303 health sciences Virtual screening Multidisciplinary Kinase business.industry Nuclear Proteins Small molecule 3. Good health Bromodomain ErbB Receptors Molecular Docking Simulation 030220 oncology & carcinogenesis Drug Screening Assays Antitumor Transcriptome business Transcription Factors |
Zdroj: | Scientific Reports |
ISSN: | 2045-2322 |
Popis: | 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 therefore 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. |
Databáze: | OpenAIRE |
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