Drug Design and Discovery Laboratory, Zewail City of Science and Technology, October Gardens, 6th of October City, Giza 12578, Egypt.
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, The British University in Egypt, Al-Sherouk City, Cairo-Suez Desert Road, Cairo 11837, Egypt.
Molecules. 2023 Jan 29;28(3):1296. doi: 10.3390/molecules28031296.
Fascin is an actin-bundling protein overexpressed in various invasive metastatic carcinomas through promoting cell migration and invasion. Therefore, blocking Fascin binding sites is considered a vital target for antimetastatic drugs. This inspired us to find new Fascin binding site blockers. First, we built an active compound set by collecting reported small molecules binding to Fascin's binding site 2. Consequently, a high-quality decoys set was generated employing DEKOIS 2.0 protocol to be applied in conducting the benchmarking analysis against the selected Fascin structures. Four docking programs, MOE, AutoDock Vina, VinaXB, and PLANTS were evaluated in the benchmarking study. All tools indicated better-than-random performance reflected by their pROC-AUC values against the Fascin crystal structure (PDB: ID 6I18). Interestingly, PLANTS exhibited the best screening performance and recognized potent actives at early enrichment. Accordingly, PLANTS was utilized in the prospective virtual screening effort for repurposing FDA-approved drugs (DrugBank database) and natural products (NANPDB). Further assessment via molecular dynamics simulations for 100 ns endorsed Remdesivir (DrugBank) and NANPDB3 (NANPDB) as potential binders to Fascin binding site 2. In conclusion, this study delivers a model for implementing a customized DEKOIS 2.0 benchmark set to enhance the VS success rate against new potential targets for cancer therapies.
Fascin 是一种肌动蛋白结合蛋白，在各种侵袭性转移性癌中通过促进细胞迁移和侵袭而上调表达。因此，阻断 Fascin 结合位点被认为是抗转移药物的一个重要靶点。这启发我们寻找新的 Fascin 结合位点阻断剂。首先，我们通过收集报道的与 Fascin 的结合位点 2 结合的小分子，构建了一个活性化合物集。随后，根据 DEKOIS 2.0 协议生成了高质量的诱饵集，用于针对选定的 Fascin 结构进行基准分析。在基准研究中评估了四个对接程序，MOE、AutoDock Vina、VinaXB 和 PLANTS。所有工具的 pROC-AUC 值均反映了其优于随机的性能，针对 Fascin 晶体结构（PDB：ID 6I18）。有趣的是，PLANTS 表现出最佳的筛选性能，并在早期富集时识别出有效成分。因此，在针对 FDA 批准药物（DrugBank 数据库）和天然产物（NANPDB）的前瞻性虚拟筛选工作中使用了 PLANTS。通过 100ns 的分子动力学模拟进一步评估，瑞德西韦（DrugBank）和 NANPDB3（NANPDB）被认为是 Fascin 结合位点 2 的潜在配体。总之，这项研究提供了一个实施定制化 DEKOIS 2.0 基准集的模型，以提高针对癌症治疗新的潜在靶点的 VS 成功率。
