Guariento Sara, Bruno Olga, Fossa Paola, Cichero Elena
Department of Pharmacy, University of Genoa, Viale Benedetto XV, 3, 16132, Genoa, Italy.
Mol Divers. 2016 Feb;20(1):77-92. doi: 10.1007/s11030-015-9631-1. Epub 2015 Aug 20.
PDE4 inhibitors have been largely studied because of their promising therapeutic effects concerning inflammation and neurodegenerative dysfunctions, such as depression, schizophrenia and Alzheimer's diseases. In this context, the PDE4B isoform proved to be particularly involved in the activation of inflammatory responses, while the PDE4D subfamily is more associated with neuropathologies. The clinical use of PDE4 inhibitors was restricted by the presence of prominent side effects probably due to their non-specific action across the different isoforms. Therefore, this work deals with the development of 3D-QSAR models, supported by molecular docking studies, to identify the key requirements underlying selective PDE4B or PDE4D inhibition. The results highlighted the ligand-based approach as a promising tool to guide the rational design of novel PDE4 inhibitors endowed with high affinity and selectivity profiles. The alignment of compound 1-85 and the model A statistical results are depicted.
由于磷酸二酯酶4(PDE4)抑制剂在治疗炎症和神经退行性疾病(如抑郁症、精神分裂症和阿尔茨海默病)方面具有潜在的治疗效果,因此人们对其进行了大量研究。在这种情况下,PDE4B亚型被证明特别参与炎症反应的激活,而PDE4D亚家族则与神经病理学更相关。PDE4抑制剂的临床应用受到显著副作用的限制,这可能是由于它们对不同亚型的非特异性作用。因此,这项工作致力于开发3D-QSAR模型,并辅以分子对接研究,以确定选择性抑制PDE4B或PDE4D的关键要求。结果突出了基于配体的方法作为一种有前途的工具,可指导设计具有高亲和力和选择性的新型PDE4抑制剂。展示了化合物1-85的比对和模型A的统计结果。