Rosell-Hidalgo Alicia, Moore Anthony L, Ghafourian Taravat
Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, United Kingdom.
Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, United Kingdom.
Toxicology. 2023 Feb;485:153412. doi: 10.1016/j.tox.2022.153412. Epub 2022 Dec 28.
There is increasing evidence that links mitochondrial off-target effects with organ toxicities. For this reason, predictive strategies need to be developed to identify mitochondrial dysfunction early in the drug discovery process. In this study, as a major mechanism of mitochondrial toxicity, first, the inhibitory activity of 35 compounds against succinate-cytochrome c reductase (SCR) was investigated. This in vitro study led to the generation of consistent experimental data for a diverse range of compounds, including pharmaceutical drugs and fungicides. Next, molecular docking and protein-ligand interaction fingerprinting (PLIF) analysis were used to identify significant residues and protein-ligand interactions for the Q site of complex III and Q site of complex II. Finally, this data was used for the development of QSAR models using a regression-based approach to highlight structural and chemical features that might be responsible for SCR inhibition. The statistically validated QSAR models from this work highlighted the importance of low aqueous solubility, low ionisation, fewer 6-membered rings and shorter hydrocarbon alkane chains in the molecular structure for increased inhibition of SCR, hence mitochondrial toxicity. PLIF analysis highlighted two key residues for inhibitory activity of the Q site of complex III: His 161 as H-bond acceptor and Pro 270 for arene interactions. Currently, there are limited structure-activity models published in the scientific literature for the prediction of mitochondrial toxicity. We believe this study helps shed light on the chemical space for the inhibition of mitochondrial electron transport chain (ETC).
越来越多的证据表明线粒体脱靶效应与器官毒性有关。因此,需要制定预测策略,以便在药物发现过程的早期识别线粒体功能障碍。在本研究中,作为线粒体毒性的主要机制,首先研究了35种化合物对琥珀酸 - 细胞色素c还原酶(SCR)的抑制活性。这项体外研究为包括药物和杀菌剂在内的多种化合物生成了一致的实验数据。接下来,使用分子对接和蛋白质 - 配体相互作用指纹图谱(PLIF)分析来确定复合物III的Q位点和复合物II的Q位点的重要残基和蛋白质 - 配体相互作用。最后,利用这些数据,采用基于回归的方法开发QSAR模型,以突出可能导致SCR抑制的结构和化学特征。这项工作中经过统计验证的QSAR模型强调了分子结构中低水溶性、低电离性、较少的六元环和较短的烃链烷烃链对于增强SCR抑制从而导致线粒体毒性的重要性。PLIF分析突出了复合物III的Q位点抑制活性的两个关键残基:作为氢键受体的His 161和用于芳烃相互作用的Pro 270。目前,科学文献中发表的用于预测线粒体毒性的构效模型有限。我们相信这项研究有助于阐明抑制线粒体电子传递链(ETC)的化学空间。