Abstract LB-226: Discovery of small molecule Mcl-1 and Bfl-1 inhibitors

Cancer Research(2020)

引用 0|浏览4
暂无评分
摘要
Anti-apoptotic Bcl-2 family proteins are frequently overexpressed in various cancers and are established therapeutic targets. Cancer cells can either display dependence on individual or subsets of these pro-survival proteins, which gives therapeutic relevance to both selective and multimodal inhibitors. Selective Bcl-2, Bcl-xL, and Mcl-1 inhibitors are being evaluated clinically in a wide spectrum of cancers. Bfl-1 is another homologous anti-apoptotic protein with closest structural relation to Mcl-1, but drug discovery efforts on this protein have been limited to peptide inhibitors. There is increasing evidence of Bfl-1 being a viable therapeutic target, particularly in the context of drug resistance. Both Mcl-1 and Bfl-1 share the selective endogenous binding partner, Noxa, which highlights the relevance of these proteins being therapeutically co-inhibited, especially in cancers where they are commonly overexpressed together. Mcl-1 and Bfl-1 have emerged as key players in melanoma, associated with poor clinical responses to BRAF/MEK pathway inhibitors and cell death resistance, thus representing attractive new therapeutic targets.We report herein the structure-based design, synthesis, SAR, and biological characterization of dual inhibitors displaying equipotent binding to Mcl-1 and Bfl-1. This class of inhibitors was designed based on the validated hit molecule identified in our recently reported integrated high throughput and virtual screening study. Several co-crystal structures of these molecules were solved, which guided the structure-based design efforts and led to the optimization of compounds that bind both Mcl-1 and Bfl-1 with Ki values in the 100 nM range and >250-fold selectivity over Bcl-2/Bcl-xL. Direct binding of optimized inhibitors to the Mcl-1 and Bfl-1 proteins was validated by several biophysical methods, including HSQC-NMR, and bio-layer interferometry (BLI). Selectivity over Bcl-2/Bcl-xL was demonstrated on the cellular level by the ability to selectively bind endogenous Mcl-1 and Bfl-1 and disrupt interactions with Bim. On-target cellular activity was further confirmed using Eµ-Myc lymphoma cell lines, which stably overexpress individual anti-apoptotic Bcl-2 proteins with a strong survival dependence on each of these targets. Eµ-Myc cells overexpressing Mcl-1 and Bfl-1 showed dose-dependent cell death in response to treatment with the most potent compounds, while cells overexpressing Bcl-2 and Bcl-xL were not affected even at the highest tested concentration, further demonstrating the selective targeting of Mcl-1 and Bfl-1. With a selective set of chemical tools, we employed the BH3 profiling assay across a panel of melanoma cell lines in order to functionally dissect survival dependence. The obtained data suggests that melanoma cell lines mainly rely on Bcl-xL and Mcl-1, with certain cell lines displaying increased involvement of Bfl-1. Importantly, the vemurafenib resistant SK-MEL-239 melanoma cell line showed increased functional Mcl-1 and Bfl-1 dependence compared to the parental line. Overall, this work contributes to the drug discovery efforts of Bcl-2 family inhibitors and provides novel dual Mcl-1/Bfl-1 selective inhibitors. Further optimization of these dual inhibitors may provide valuable therapeutics to help combat acquired resistance in melanoma, where Mcl-1 and Bfl-1 play prominent functional roles, as determined by BH3 profiling. Citation Format: Karson J. Kump, Lei Miao, Ahmed A. Mady, Nurul H. Ansari, Uttar K. Shrestha, Yuting Yang, Mohan Pal, Chenzhong Liao, Andrej Perdih, Fardokht A. Abulwerdi, Krishnapriya Chinnaswamy, Jennifer L. Meagher, Jacob M. Carlson, May Khanna, Jeanne A. Stuckey, Zaneta Nikolovska-Coleska. Discovery of small molecule Mcl-1 and Bfl-1 inhibitors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-226.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要