Revealing cancer dependencies through inhibition of SLiM interactions using competitor peptides

短线性基序（SLiM）是一种优雅且空间高效的交互界面编码解决方案。因此，SLiM介导许多细胞功能，例如在动态复合物中指导配体结合，为修饰酶提供对接位点，通过募集泛素连接酶来控制蛋白质稳定性以及充当亚细胞定位信号。该项目将通过表达基因编码的竞争肽并表征特定SLiM竞争者的癌症亚型依赖性来评估抑制SLiM介导的蛋白质-蛋白质相互作用的治疗潜力。首先，将优化肽表达底盘以增强表达的肽与内源性SLiM的竞争。接下来，将构建表达所有经验证的SLiM肽（5，621个基序）的慢病毒文库并转导至癌细胞系。将在合并的竞争性生长测定中研究每种肽的作用。肽表型数据将与先前癌症基因依赖性研究的数据整合，以优先进行肽的深入验证。与基于CRISPR和RNAi的依赖性研究的蛋白质水平信息相反，这项研究将直接确定治疗干预的结合口袋。因此，SLiM依赖性筛选将为抑制SLiM结合口袋提供原理证明，并允许对小分子药物开发的靶点进行廉价、高通量和信息丰富的分类和优先级排序。在项目期间，研究人员将从酵母细胞周期的基础研究领域转向专注于癌症生物学的转化领域。他将通过在多个细胞系中使用高通量方法来扩展自己的技能，并通过管理项目、建立网络、与公众沟通和传播结果来提高自己的可转移技能。总之，这些技能将使他过渡到一个独立的研究人员。

Short Linear Motifs (SLiMs) are an elegant and spatially efficient solution for encoding interaction interfaces. Consequently, SLiMs mediate many cellular functions such as directing ligand binding in dynamic complexes, providing docking sites for modifying enzymes, controlling protein stability by recruiting ubiquitin ligases and acting as subcellular localization signals. This project will evaluate the therapeutic potential of inhibiting SLiM-mediated protein-protein interactions by expressing genetically encoded competitor peptides and characterising the cancer subtype dependencies of specific SLiM competitors. First, a peptide expression chassis will be optimized to potentiate competition of expressed peptides with endogenous SLiMs. Next, a lentiviral library expressing all validated SLiM peptides (5,621 motifs) will be constructed and transduced to cancer cell lines. The effect of each peptide will be studied in a pooled competitive growth assay. The peptide phenotype data will be integrated with data from prior cancer gene dependency studies to prioritise peptides for in-depth validation. In contrast to the protein level information of CRISPR- and RNAi-based dependency studies, this study will directly pinpoint a binding pocket for therapeutic intervention. Consequently, the SLiM dependency screen will provide proof of principle for the inhibition of SLiM-binding pockets and allow inexpensive, high-throughput and information-rich triage and prioritisation of targets for small molecule drug development. During the project, the researcher will switch from the basic research field of the yeast cell cycle to a translational field focusing on cancer biology. He will expand his skillset by working with high-throughput methods across multiple cell lines, and improve his transferable skills by managing the project, networking, communicating with the public and disseminating the results. Together, these skills will allow him to transition to an independent researcher.