Activity-based regulome profiling for the discovery of covalent transcription factor inhibitors

研究综述 人类基因组编码超过1，600种转录因子（TF），沿着有额外的转录因子。 辅因子、染色质调节因子和共同执行调节的结构蛋白质。 编码在核DNA中的指令。已知这些蛋白质的功能障碍 多种疾病，如癌症、炎症相关疾病和神经系统疾病。在癌症中， 这些蛋白质经常被扩增或过表达以驱动基因表达程序 促进各种类型的白血病、肉瘤和其他恶性肿瘤的发生和发展。 肿瘤的尽管这些蛋白质的重要性，TF已被认为是不可药用的，因为 在体外模拟其活性的挑战。我们已经解决了这些缺点， 实施细胞内功能蛋白质组学药物发现平台， 小分子对多种细胞和组织中与基因组结合的TF丰度的影响 类型该平台基于盐分离染色质提取，结合数据 独立分析质谱法（ChESS-DIA），这是最近报道的。在这 建议，我们调整这项技术，使共价小分子抑制剂的发现， 一种最近能够靶向以前无法治疗的KRAS的化学物质 蛋白首先，我们将比较几种不同的共价筛选方法在 结合ChESS-DIA蛋白质组分析，确定哪种策略最适合 复合发现还将建立计算工具， 共价命中化合物，并确定化合物：蛋白质加合物，形成后， 复合装订几种充分表征的共价抑制剂将用于验证 这些方法的准确性。通过经验证的共价筛选TF测定，我们将优化 使用完整蛋白质的二次测定以验证命中化合物可以标记靶蛋白质， 化学计量的特定方式。有了这些工具，我们将执行试点屏幕， 使用商业共价键的子集，证明检测在发现环境中的实用性。 复合图书馆这些化合物含有各种各样的反应弹头，这将 使我们能够了解优化测定的各种性能指标。此数据包 将使我们能够进行全面的内部筛选的化合物，目标塔卢斯的转录因子， 兴趣，并提供与生物技术公司的业务发展讨论的基础 以及对TF抑制感兴趣的制药公司。

RESEARCH SUMMARY The human genome encodes more than 1,600 transcription factors (TFs), along with additional cofactors, chromatin regulators, and structural proteins that collectively execute the regulatory instructions encoded within the nuclear DNA. Dysfunctions of these proteins are known to drive multiple diseases such as cancer, inflammation-related, and neurological conditions. In cancer, these proteins are frequently amplified or overexpressed to drive a gene expression program that facilitates the initiation and progression of various types of leukemia, sarcoma and other tumors. Despite the importance of these proteins, TFs have been considered undruggable due to challenges in modeling their activity in vitro. We have solved these shortcomings by implementing an in-cell functional proteomics drug discovery platform that quantifies the effects of small-molecules on the abundance of TF bound to the genome in a diversity of cell and tissue types. The platform is based on Chromatin Extraction by Salt Separation, coupled to Data Independent Analysis mass spectrometry (ChESS-DIA), which was recently reported. In this proposal, we adapt this technology to enable the discovery of covalent small molecule inhibitors, a type of chemistry that has recently enabled targeting of the previously undruggable KRAS protein. First, we will compare the efficacy of several different covalent screening approaches in combination with ChESS-DIA proteome analysis, determining which strategy is best for compound discovery. Computational tools will also be built to robustly identify functional covalent hit compounds, and to identify the compound:protein adducts that are formed upon compound binding. Several well-characterized covalent inhibitors will be used to validate the accuracy of these methods. With a validated covalent screening TF assay, we will then optimize a secondary assay using intact protein to verify that hit compounds can label target proteins in a stoichiometric, specific way. With these tools in hand, we will then perform a pilot screen to prove the assay’s utility in a discovery setting, using a subset of a commercial covalent compound library. These compounds contain a diverse array of reactive warheads, and this will allow us to understand various performance metrics of the optimized assay. This data package will enable us to perform full-scale internal screens for compounds that target Talus’ TFs of interest, as well as provide the foundation for business development discussions with biotech and pharmaceutical companies interested in TF inhibition.