Integrated fragment-based phenotypic screening and chemoproteomics for identification of novel small cell lung cancer-specific targets

基于片段的表型筛选和化学蛋白质组学相结合，用于鉴定新型小细胞肺癌特异性靶标

• 批准号: 10577507
• 负责人: Andrii Monastyrskyi
• 金额: $ 23.63万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-02 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10577507
• 关键词: ASCL1 gene; Accounting; Affinity; Alkynes; Apoptosis; Azides; BETA2 protein; Binding; Binding Sites; Biochemical; Biological; Biological Assay; CASP3 gene; Cancer Etiology; Cancer Patient; Cancer cell line; Cell Line; Cell Survival; Cells; Cessation of life; Characteristics; Chemicals; Chemistry; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Copper; Data; Databases; Dedications; Diazomethane; Disease; Dose; Drug Costs; Drug Targeting; Epithelium; Future; Genetic; IGF1R gene; Immunotherapy; Induction of Apoptosis; Informatics; Knowledge; Lead; Libraries; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Mass Spectrum Analysis; Mediating; Mining; Minor; Mission; Mutate; Non-Small-Cell Lung Carcinoma; Outcome; Patients; Pharmaceutical Chemistry; Pharmaceutical Preparations; Phenotype; Proteins; Proteomics; Public Health; RB1 gene; RNA Interference; Research; Risk; Role; Signal Transduction; Structure; TP53 gene; Technology; Therapeutic; Time; Translating; Treatment Failure; Tumor Suppressor Proteins; United States National Institutes of Health; Validation; Western Blotting; analog; cancer cell; cancer subtypes; cancer therapy; chemical association; chemoproteomics; chemotherapy; cycloaddition; cytotoxic; driver mutation; drug development; drug discovery; drug resistance development; druggable target; improved; in vivo; inhibitor; innovation; insight; loss of function mutation; lung cancer cell; molecular subtypes; new therapeutic target; novel; novel therapeutics; patient population; response; scaffold; screening; small cell lung carcinoma; small molecule; standard of care; success; targeted treatment; transcription factor

PROJECT ABSTRACT Despite major successes in lung cancer therapy over the last two decades, there are still many patients who do not receive any benefit from targeted or immunotherapies. This is particularly true for small cell lung cancer (SCLC), a recalcitrant cancer for which there are currently no effective targeted therapies. Although SCLC patients initially respond well to conventional chemo- and immune therapy, drug resistance develops rapidly illustrating the need for new therapeutic targets and drugs. Traditional drug discovery often prioritize known targets and operates in limited biological and chemical space. Smaller fragment-like compounds are significantly better suited to enter previously unrecognized binding sites thereby probing uncharted biological target space and identifying novel targets. We hypothesize that cell-based screening of fragment-like probe molecules combined with chemoproteomics for target identification will enable the simultaneous identification of (i) novel, highly SCLC- specific targets and (ii) new lead compounds as modulators of these targets. We propose to specifically interrogate SCLC cells in comparison to NSCLC and non-cancerous cells and screen a library of small fragment-like molecules. Combination with innovative proteomics technology can subsequently identify new actionable targets, which will be functionally validated and will serve as starting points for novel SCLC-specific drug discovery projects. Aim 1: To identify actionable targets and associated chemical hit compounds in SCLC vs NSCLC cancer cells. We will screen a 15,000 fragment-like compound library (~estimated to the equivalent of >100,000 lead-like compounds) in several SCLC, which represent different molecular subtypes, and control (NSCLC and non-cancerous lung epithelial) cell lines. The most SCLC-specific or SCLC subtype-specific hits will be validated regarding selective viability and apoptosis effects, also in combination with standard of care chemotherapy drugs. Aim 2: To identify and validate novel and selective, actionable targets in SCLC cells. Using a diverse panel of fragment-like compounds with ‘privileged’ BioCore motifs and SCLC-selective screening hits from Aim 1 we will perform mass spectrometry-based chemoproteomics through UV-mediated photocrosslinking and copper-catalyzed ‘click’ chemistry in SCLC cell lines. High confidence protein target candidates, based on comparison with control compounds/cell lines and DEPMAP database mining, will be validated using appropriate biochemical and signaling readouts, as well as RNAi- and CRISPR-based genetic modulation in an expanded cell line panel. Medicinal chemistry optimization of hits will be done by 1) chemoinformatic and structure-network similarity analysis and 2) synthesis of analogs based on the SAR of both library and synthesized compounds. Leads will be characterized using biochemical and cell-based binding assays (e.g. affinity-immunoblotting, SPR, nanoBRET). The expected outcome is the identification of novel SCLC- and/or SCLC subtype-specific targets and chemical starting points for dedicated drug discovery efforts that through further elucidation of the biological context and in vivo validation produce desperately needed new therapeutics for SCLC.

项目摘要 尽管过去二十年肺癌治疗取得了重大成功，但仍有许多患者接受肺癌治疗。 无法从靶向治疗或免疫治疗中获益，对于小细胞肺癌尤其如此。 （SCLC），一种顽固性癌症，目前尚无有效的靶向治疗方法。 患者最初对常规化疗和免疫治疗反应良好，耐药性迅速发展 说明对新治疗靶点和药物的需求 传统药物发现通常优先考虑已知的药物。 较小的碎片状化合物在有限的生物和化学空间中进行靶向和操作。 更适合进入以前未识别的结合位点，从而探测未知的生物目标空间 我们致力于基于细胞的片段样探针分子筛选。 利用化学蛋白质组学进行靶标鉴定将能够同时鉴定 (i) 新型、高度 SCLC- 特定目标和（ii）作为这些目标调节剂的新先导化合物我们建议专门询问。 SCLC 细胞与 NSCLC 和非癌细胞进行比较，并筛选小片段样文库 与创新的蛋白质组学技术相结合，可以随后识别出新的可操作的分子。 目标，这些目标将得到功能验证，并将作为新型 SCLC 特异性药物的起点 目标 1：确定 SCLC 与相关化学命中化合物。 我们将筛选 15,000 个片段样化合物库（~估计相当于 > 100,000 种铅样化合物）在多个 SCLC 中，代表不同的分子亚型，并对照 （NSCLC 和非癌性肺上皮细胞）细胞系最具 SCLC 特异性或 SCLC 亚型特异性。 将验证选择性活力和细胞凋亡效应，并结合护理标准 目标 2：识别和验证 SCLC 细胞中新颖的、选择性的、可操作的靶标。 具有“特权”BioCore 基序和 SCLC 选择性筛选命中的多种片段状化合物 从目标 1 开始，我们将通过紫外线介导的光交联进行基于质谱的化学蛋白质组学 SCLC 细胞系中铜催化的“点击”化学，基于高可信度蛋白质靶标候选物。 与对照化合物/细胞系和 DEPMAP 数据库挖掘的比较，将使用适当的方法进行验证 生化和信号读数，以及基于 RNAi 和 CRISPR 的遗传调节 细胞系面板。命中的药物化学优化将通过 1) 化学信息学和结构网络完成。 相似性分析和 2) 基于文库和合成化合物的 SAR 的类似物合成。 将使用生化和基于细胞的结合测定（例如亲和免疫印迹、SPR、 nanoBRET）的预期结果是识别新的 SCLC 和/或 SCLC 亚型特异性靶点。 专门的药物发现工作的化学起点，通过进一步阐明生物 背景和体内验证产生了急需的 SCLC 新疗法。