Swiss Federal Institute of Technology, Department of Chemistry & Applied Biosciences, 8093 Zürich, Switzerland.
Future Med Chem. 2011 Mar;3(4):415-24. doi: 10.4155/fmc.11.8.
De novo design of drug-like compounds with a desired pharmacological activity profile has become feasible through innovative computer algorithms. Fragment-based design and simulated chemical reactions allow for the rapid generation of candidate compounds as blueprints for organic synthesis.
We used a combination of complementary virtual-screening tools for the analysis of de novo designed compounds that were generated with the aim to inhibit inactive polo-like kinase 1 (Plk1), a target for the development of cancer therapeutics. A homology model of the inactive state of Plk1 was constructed and the nucleotide binding pocket conformations in the DFG-in and DFG-out state were compared. The de novo-designed compounds were analyzed using pharmacophore matching, structure-activity landscape analysis, and automated ligand docking. One compound was synthesized and tested in vitro.
The majority of the designed compounds possess a generic architecture present in known kinase inhibitors. Predictions favor kinases as targets of these compounds but also suggest potential off-target effects. Several bioisosteric replacements were suggested, and de novo designed compounds were assessed by automated docking for potential binding preference toward the inactive (type II inhibitors) over the active conformation (type I inhibitors) of the kinase ATP binding site. One selected compound was successfully synthesized as suggested by the software. The de novo-designed compound exhibited inhibitory activity against inactive Plk1 in vitro, but did not show significant inhibition of active Plk1 and 38 other kinases tested.
Computer-based de novo design of screening candidates in combination with ligand- and receptor-based virtual screening generates motivated suggestions for focused library design in hit and lead discovery. Attractive, synthetically accessible compounds can be obtained together with predicted on- and off-target profiles and desired activities.
通过创新的计算机算法，设计具有所需药理活性特征的类药化合物已成为可能。片段设计和模拟化学反应允许快速生成候选化合物，作为有机合成的蓝图。
我们使用了互补的虚拟筛选工具组合，用于分析旨在抑制无活性 Polo 样激酶 1（Plk1）的从头设计化合物，Plk1 是癌症治疗药物开发的靶点。构建了无活性 Plk1 的同源模型，并比较了 DFG-in 和 DFG-out 状态下的核苷酸结合口袋构象。使用药效团匹配、结构活性景观分析和自动配体对接分析从头设计的化合物。合成了一种化合物并进行了体外测试。
大多数设计的化合物都具有已知激酶抑制剂中存在的通用结构。预测倾向于将激酶作为这些化合物的靶点，但也提示可能存在脱靶效应。提出了几种生物等排替换，并用自动对接评估了从头设计的化合物，以评估它们对激酶 ATP 结合位点无活性（II 型抑制剂）构象的潜在结合偏好，而不是对活性构象（I 型抑制剂）的潜在结合偏好。根据软件建议，成功合成了一种选定的化合物。该从头设计的化合物在体外对无活性 Plk1 表现出抑制活性，但对活性 Plk1 和 38 种其他测试激酶没有显著抑制作用。
基于计算机的筛选候选物从头设计与基于配体和受体的虚拟筛选相结合，为有针对性的文库设计提供了有针对性的发现的动力建议。可以获得有吸引力的、可合成的化合物，并预测其潜在的脱靶和靶标特征以及所需的活性。
