Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi, China, School of Chemical engineering, Dalian University of Technology, Dalian, Liaoning, China, Beijing University of Chinese Medicine, ChaoYang District, Beijing, China and School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
College of Life Science, Northwest A & F University, Yangling, Shaanxi, 712100, China; Center of Bioinformatics, Northwest A & F University, Yangling, Shaanxi, China.
Brief Bioinform. 2017 Mar 1;18(2):321-332. doi: 10.1093/bib/bbw018.
Designing maximally selective ligands that act on individual drug targets with high binding affinity has been the central dogma of drug discovery and development for the past two decades. However, many low-affinity drugs that aim for several targets at the same time are found more effective than the high-affinity binders when faced with complex disease conditions, such as cancers, Alzheimer's disease and cardiovascular diseases. The aim of this study was to appreciate the importance and reveal the features of weak-binding drugs and propose an integrated strategy for discovering them. Weak-binding drugs can be characterized by their high dissociation rates and transient interactions with their targets. In addition, network topologies and dynamics parameters involved in the targets of weak-binding drugs also influence the effects of the drugs. Here, we first performed a dynamics analysis for 33 elementary subgraphs to determine the desirable topology and dynamics parameters among targets. Then, by applying the elementary subgraphs to the mitogen-activated protein kinase (MAPK) pathway, several optimal target combinations were obtained. Combining drug-target interaction prediction with molecular dynamics simulation, we got two potential weak-binding drug candidates, luteolin and tanshinone IIA, acting on these targets. Further, the binding affinity of these two compounds to their targets and the anti-inflammatory effects of them were validated through in vitro experiments. In conclusion, weak-binding drugs have real opportunities for maximum efficiency and may show reduced adverse reactions, which can offer a bright and promising future for new drug discovery.
在过去的二十年中，设计对单个药物靶标具有高结合亲和力的最大选择性配体一直是药物发现和开发的核心原则。然而，在面对复杂的疾病情况（如癌症、阿尔茨海默病和心血管疾病）时，许多同时针对多个靶标的低亲和力药物比高亲和力结合剂更有效。本研究旨在重视弱结合药物的重要性并揭示其特征，并提出发现它们的综合策略。弱结合药物的特征是其解离率高，与靶标短暂相互作用。此外，弱结合药物靶标中涉及的网络拓扑结构和动力学参数也会影响药物的效果。在这里，我们首先对 33 个基本子图进行了动力学分析，以确定靶标中理想的拓扑结构和动力学参数。然后，通过将基本子图应用于丝裂原活化蛋白激酶（MAPK）途径，获得了几个最佳的靶标组合。通过将药物-靶标相互作用预测与分子动力学模拟相结合，我们得到了两种潜在的弱结合药物候选物，木犀草素和丹参酮 IIA，它们作用于这些靶标。此外，通过体外实验验证了这两种化合物与其靶标的结合亲和力和抗炎作用。总之，弱结合药物具有实现最大效率的真正机会，并且可能显示出减少的不良反应，这为新药发现提供了光明而有前途的未来。
