While Myc is an essential regulator of growth in normal cells, it is also frequently associated with cancer progression, therapy-resistance and lethal outcomes in most human cancers. In prostate cancer (PCa), Myc transcription factors are implicated in the pathogenesis and progression of the full spectrum of PCa, from adenocarcinoma to advanced castration-resistant and neuroendocrine phenotypes. Though a high-value therapeutic target, clinically approved anti-Myc drugs have yet to be discovered. To elicit its oncogenic effects, Myc must form a heterodimer with its partner Max, which together bind DNA and activate transcription of a spectrum of target genes that promote cell growth, proliferation, metabolism, and apoptosis while blocking differentiation. In this study, we identified a binding site on the DNA-binding domain of the structurally ordered Myc-Max complex and employed a computer-aided rational drug discovery approach to identify small molecules that effectively inhibit Myc-Max functionality. A large-scale virtual screening protocol implementing structure-based methodologies was utilized to select a set of top-ranked compounds that were subsequently evaluated experimentally and characterized mechanistically for their ability to inhibit Myc-Max transcriptional activity and subsequent downstream functions, to reduce viability in PCa cell lines, disrupt protein-DNA interactions and to induce apoptosis as their mechanism of action. Among compounds identified that effectively inhibit Myc-Max activity with low to mid-micromolar range potency and no or minimal generic cytotoxicity, VPC-70067, a close analog of the previously identified Myc inhibitor 10058-F4, served as proof-of-concept that our in silico drug discovery strategy performed as expected. Compound VPC-70063, of a chemically different scaffold, was the best performer in a panel of in vitro assays, and the forerunner for future hit-to-lead optimization efforts. These findings lay a foundation for developing more potent, specific and clinically optimized Myc-Max inhibitors that may serve as promising therapeutics, alone or in combination with current anti-cancer treatments, for treatment of specific phenotypes or heterogeneous tumors.
Keywords: Computer-aided drug discovery; Myc-max; Prostate cancer; Protein-DNA interactions; Small molecule inhibitors.
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