Polo-like kinase 1 (PLK1) plays vital roles in mitotic activities including G2/M transition, mitotic entry, and cytokinesis. PLK1 overexpression was observed in cancers and associated with poor prognosis. PLK1 inhibition was proven to hamper cancer hallmarks. In this research, a computational workflow named Docking-based Comparative Intermolecular Contacts Analysis (dbCICA) was employed to discover new PLK1 inhibitors. Eighty-two reported PLK1 inhibitors were fitted into the binding-pocket of a PLK1 crystallographic structure to specify their finest possible docking configurations. Optimal dbCICA models were utilized to create pharmacophores that were assessed by receiver operating characteristic (ROC) analysis and were employed for in-silico virtual screening of the National Cancer Institute database. The bioactivities of captured hits were evaluated via fluorescence-based kinase bioassay. Two promising hits were identified; 89 (NCI 37190) and 103 (NCI 1012) scored IC₅₀ values of 6.30 and 19.1 μM, respectively.

Polo 样激酶 1 (PLK1) 在有丝分裂活动中起着至关重要的作用，包括 G2/M 转换、有丝分裂进入和胞质分裂。在癌症中观察到 PLK1 过表达并与不良预后相关。PLK1 抑制被证明会阻碍癌症标志。在这项研究中，使用名为基于对接的比较分子间接触分析 (dbCICA) 的计算工作流程来发现新的 PLK1 抑制剂。82 种报道的 PLK1 抑制剂被装入 PLK1 晶体结构的结合袋中，以指定它们可能的最佳对接配置。最佳 dbCICA 模型用于创建药效团，这些药效团通过受试者工作特征 (ROC) 分析进行评估，并用于美国国家癌症研究所数据库的计算机虚拟筛选。通过基于荧光的激酶生物测定评估捕获的命中的生物活性。确定了两个有希望的点击；89 (NCI 37190)和103 (NCI 1012) 的IC ₅₀值分别为 6.30 和 19.1 μM。