Department of Molecular Biology & Microbiology, Case Western Reserve University, Cleveland, Ohio, USA.
Atomwise Inc., San Francisco, California, USA.
J Cell Mol Med. 2023 Nov;27(22):3553-3564. doi: 10.1111/jcmm.17973. Epub 2023 Oct 20.
Approximately 40% of people will get cancer in their lifetime in the US, and 20% are predicted to die from the condition when it is invasive and metastatic. Targeted screening for drugs that interact with proteins that drive cancer cell growth and migration can lead to new therapies. We screened molecular libraries with the AtomNet® AI-based drug design tool to identify compounds predicted to interact with the cytoplasmic domain of protein tyrosine phosphatase mu. Protein tyrosine phosphatase mu (PTPmu) is proteolytically downregulated in cancers such as glioblastoma generating fragments that stimulate cell survival and migration. Aberrant nuclear localization of PTPmu intracellular fragments drives cancer progression, so we targeted a predicted drug-binding site between the two cytoplasmic phosphatase domains we termed a D2 binding pocket. The function of the D2 domain is controversial with various proposed regulatory functions, making the D2 domain an attractive target for the development of allosteric drugs. Seventy-five of the best-scoring and chemically diverse computational hits predicted to interact with the D2 binding pocket were screened for effects on tumour cell motility and growth in 3D culture as well as in a direct assay for PTPmu-dependent adhesion. We identified two high-priority hits that inhibited the migration and glioma cell sphere formation of multiple glioma tumour cell lines as well as aggregation. We also identified one activator of PTPmu-dependent aggregation, which was able to stimulate cell migration. We propose that the PTPmu D2 binding pocket represents a novel regulatory site and that inhibitors targeting this region may have therapeutic potential for treating cancer.
在美国,大约 40%的人在一生中会患上癌症,20%的人预计会死于侵袭性和转移性癌症。针对与驱动癌细胞生长和迁移的蛋白质相互作用的药物进行靶向筛选,可以带来新的治疗方法。我们使用基于 AtomNet®人工智能的药物设计工具筛选了分子文库,以鉴定出预测与蛋白酪氨酸磷酸酶 μ 的细胞质结构域相互作用的化合物。蛋白酪氨酸磷酸酶 μ (PTPmu) 在癌症中如脑胶质瘤被蛋白水解下调,产生刺激细胞存活和迁移的片段。PTPmu 细胞内片段的异常核定位驱动癌症进展,因此我们针对两个细胞质磷酸酶结构域之间的一个预测药物结合位点进行了靶向研究,我们将其称为 D2 结合口袋。D2 结构域的功能存在争议,有多种提出的调节功能,这使得 D2 结构域成为开发变构药物的有吸引力的靶标。我们对 75 个评分最高、化学多样性最大的计算命中物进行了筛选,以检测它们对肿瘤细胞在 3D 培养中的迁移和生长以及 PTPmu 依赖性粘附的直接测定中的影响。我们确定了两个高优先级的命中物,它们抑制了多种神经胶质瘤肿瘤细胞系的迁移和神经胶质瘤细胞球体形成以及聚集。我们还鉴定了一种 PTPmu 依赖性聚集的激活剂,它能够刺激细胞迁移。我们提出 PTPmu D2 结合口袋代表一个新的调节位点,针对该区域的抑制剂可能具有治疗癌症的潜力。