分子片段法快速识别早期研究成果和随后的引物优化是药物发现的一个挑战。为了应对这个挑战，我们创建了一个被称为“DOTS”的策略，将分子动力学模拟、基于计算机的库设计（化学“点”）、编码的药物化学反应、约束对接和自动化化合物评估相结合。为了验证其效用，我们将“DOTS”策略应用于具有挑战性的靶点syntenin，它是一种包含PDZ结构域的蛋白质和肿瘤学靶点。在这里，我们描述了创建了一种针对syntenin第二个PDZ结构域的亚微摩尔级“最佳”的小分子抑制剂，并在癌细胞实验中验证了其有效性。我们DOTS方法的成功关键在于在早期研究成果中集成蛋白质构象采样和在优化过程中对设计化合物进行合成可行性排名。这种方法可以广泛应用于其他已知三维结构的蛋白质靶点，以快速识别和优化化合物作为化学探针和治疗候选。

The rapid identification of early hits by fragment-based approaches and subsequent hit-to-lead optimization represents a challenge for drug discovery. To address this challenge, we created a strategy called "DOTS" that combines molecular dynamic simulations, computer-based library design (chemoDOTS) with encoded medicinal chemistry reactions, constrained docking, and automated compound evaluation. To validate its utility, we applied our DOTS strategy to the challenging target syntenin, a PDZ domain containing protein and oncology target. Herein, we describe the creation of a "best-in-class" sub-micromolar small molecule inhibitor for the second PDZ domain of syntenin validated in cancer cell assays. Key to the success of our DOTS approach was the integration of protein conformational sampling during hit identification stage and the synthetic feasibility ranking of the designed compounds throughout the optimization process. This approach can be broadly applied to other protein targets with known 3D structures to rapidly identify and optimize compounds as chemical probes and therapeutic candidates.