Biggs George S, Cawood Emma E, Vuorinen Aini, McCarthy William J, Wilders Harry, Riziotis Ioannis G, van der Zouwen Antonie J, Pettinger Jonathan, Nightingale Luke, Chen Peiling, Powell Andrew J, House David, Boulton Simon J, Skehel J Mark, Rittinger Katrin, Bush Jacob T
Crick-GSK Biomedical LinkLabs, GSK, Gunnels Wood Road, Stevenage, Hertfordshire, UK.
Molecular Structure of Cell Signalling Laboratory, The Francis Crick Institute, London, UK.
Nat Commun. 2025 Jan 2;16(1):73. doi: 10.1038/s41467-024-55057-5.
Identifying pharmacological probes for human proteins represents a key opportunity to accelerate the discovery of new therapeutics. High-content screening approaches to expand the ligandable proteome offer the potential to expedite the discovery of novel chemical probes to study protein function. Screening libraries of reactive fragments by chemoproteomics offers a compelling approach to ligand discovery, however, optimising sample throughput, proteomic depth, and data reproducibility remains a key challenge. We report a versatile, label-free quantification proteomics platform for competitive profiling of cysteine-reactive fragments against the native proteome. This high-throughput platform combines SP4 plate-based sample preparation with rapid chromatographic gradients. Data-independent acquisition performed on a Bruker timsTOF Pro 2 consistently identified ~23,000 cysteine sites per run, with a total of ~32,000 cysteine sites profiled in HEK293T and Jurkat lysate. Crucially, this depth in cysteinome coverage is met with high data completeness, enabling robust identification of liganded proteins. In this study, 80 reactive fragments were screened in two cell lines identifying >400 ligand-protein interactions. Hits were validated through concentration-response experiments and the platform was utilised for hit expansion and live cell experiments. This label-free platform represents a significant step forward in high-throughput proteomics to evaluate ligandability of cysteines across the human proteome.
确定针对人类蛋白质的药理探针是加速新型疗法发现的关键机遇。采用高内涵筛选方法来扩展可配体化蛋白质组,有望加快新型化学探针的发现,以研究蛋白质功能。通过化学蛋白质组学筛选反应性片段文库为配体发现提供了一种引人注目的方法,然而,优化样品通量、蛋白质组深度和数据重现性仍是一项关键挑战。我们报告了一种通用的、无标记定量蛋白质组学平台,用于针对天然蛋白质组对半胱氨酸反应性片段进行竞争性分析。这个高通量平台将基于SP4板的样品制备与快速色谱梯度相结合。在布鲁克timsTOF Pro 2上进行的数据非依赖型采集每次运行始终能鉴定出约23,000个半胱氨酸位点,在HEK293T和Jurkat裂解物中总共分析了约32,000个半胱氨酸位点。至关重要的是,这种对半胱氨酸组的覆盖深度伴随着高数据完整性,能够可靠地鉴定出被配体结合的蛋白质。在本研究中,在两种细胞系中筛选了80个反应性片段,鉴定出>400种配体 - 蛋白质相互作用。通过浓度 - 反应实验验证了命中结果,并将该平台用于命中结果扩展和活细胞实验。这个无标记平台代表了高通量蛋白质组学在评估整个人类蛋白质组中半胱氨酸的可配体化能力方面向前迈出的重要一步。