Rodríguez-Martínez Alejandro, Giraldo-Ruiz Lucía, Ramos María C, Luque Irene, Ribeiro Diogo, Postigo-Corrales Fátima, Alburquerque-González Begoña, Montoro-García Silvia, Arroyo-Rodríguez Ana Belén, Conesa-Zamora Pablo, Hurtado Ana María, Luengo-Gil Ginés, Pérez-Sánchez Horacio
Structural Bioinformatics and High Performance Computing Research Group (BIO-HPC), UCAM Universidad Católica de Murcia (UCAM), HiTech Innovation Hub, Murcia, 30107, Spain.
Health Sciences PhD Program, Universidad Católica de Murcia UCAM, Campus de los Jerónimos nº135, Guadalupe, Murcia, 30107, Spain.
Sci Rep. 2025 Apr 28;15(1):14906. doi: 10.1038/s41598-025-96457-x.
Metastasis is one of the leading causes of cancer-related death worldwide. Fascin, a protein that bundles actin filaments to produce protrusions in cancer cells, plays a significant role in the enhancement of cell migration. This protein has been shown that the overexpression of this protein is related to the appearance of different types of cancer, such as colorectal cancer. In this study, we conducted in silico screening of the Enamine library, a compound library with a broad chemical space. Using a ligand-based virtual screening approach based on the pharmacophore model of G2, we identified the predicted inhibitors. First, these compounds were validated by physicochemical analysis. Differential scanning calorimetry (DSF) was used to study the binding between the predicted compounds and fascin protein, followed by an F-actin bundling assay to determine which compounds inhibited the bundling function of fascin. Z1362873773, which exhibited binding to fascin and inhibited F-actin bundling, was further tested in cell cultures to assess its effects on cancer cell viability and migration as well as in organoid models to evaluate potential cytotoxicity. Finally, we established a protocol that can be applied to discover anti-fascin agents from diverse compound libraries. A new molecule has been identified with considerable fascin inhibitory and migration-arresting capacity, which may lead to the development of new therapies to treat cancer.
转移是全球癌症相关死亡的主要原因之一。Fascin是一种能将肌动蛋白丝捆绑在一起从而在癌细胞中产生突起的蛋白质，在增强细胞迁移方面发挥着重要作用。已有研究表明，这种蛋白质的过表达与不同类型癌症的出现有关，比如结直肠癌。在本研究中，我们对Enamine文库进行了计算机模拟筛选，这是一个具有广阔化学空间的化合物文库。我们基于G2的药效团模型，采用基于配体的虚拟筛选方法，确定了预测的抑制剂。首先，通过物理化学分析对这些化合物进行验证。利用差示扫描量热法（DSF）研究预测化合物与Fascin蛋白之间的结合，随后进行F-肌动蛋白捆绑试验，以确定哪些化合物抑制Fascin的捆绑功能。对表现出与Fascin结合并抑制F-肌动蛋白捆绑的Z1362873773，进一步在细胞培养中进行测试，以评估其对癌细胞活力和迁移的影响，同时在类器官模型中评估其潜在的细胞毒性。最后，我们建立了一种可用于从不同化合物文库中发现抗Fascin药物的方案。已鉴定出一种具有相当强的Fascin抑制和迁移阻滞能力的新分子，这可能会促成治疗癌症的新疗法的开发。
