Ivanov S M, Lagunin A A, Poroikov V V
Institute of Biomedical Chemistry, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia.
Institute of Biomedical Chemistry, Moscow, Russia.
Biomed Khim. 2024 Dec;70(6):403-412. doi: 10.18097/PBMC20247006403.
Major depressive disorder (MDD) is one of the most common diseases affecting millions of people worldwide. The use of existing antidepressants in many cases does not allow achieving stable remission, probably due to insufficient understanding of pathological mechanisms. This indicates the need for the development of more effective drugs based on in-depth understanding of MDD's pathophysiology. Since the high costs and long duration of the development of new drugs, the drug repositions may be the promising alternative. In this study we have applied the recently developed DIGEP-Pred approach to identify drugs that induce changes in expression of genes associated with the etiopathogenesis of MDD, followed by identification of their potential MDD-related targets and molecular mechanisms of the antidepressive effects. The applied approach included the following steps. First, using structure-activity relationships (SARs) we predicted drug-induced gene expression changes for 3690 worldwide approved drugs. Disease enrichment analysis applied to the predicted genes allowed to identify drugs that significantly altered expression of known MDD-related genes. Second, potential drug targets, which are probable master regulators responsible for drug-induced gene expression changes, have been identified through the SAR-based prediction and network analysis. Only those drugs whose potential targets were clearly associated with MDD according to the published data, were selected for further analysis. Third, since potential new antidepressants must distribute into brain tissues, drugs with an oral route of administration were selected and their blood-brain barrier permeability was estimated using available experimental data and in silico predictions. As a result, we identified 19 drugs, which can be potentially repurposed for the MDD treatment. These drugs belong to various therapeutic categories, including adrenergic/dopaminergic agents, antiemetics, antihistamines, antitussives, and muscle relaxants. Many of these drugs have experimentally confirmed or predicted interactions with well-known MDD-related protein targets such as monoamine (serotonin, adrenaline, dopamine) and acetylcholine receptors and transporters as well as with less trivial targets including galanin receptor type 3 (GALR3), G-protein coupled estrogen receptor 1 (GPER1), tyrosine-protein kinase JAK3, serine/threonine-protein kinase ULK1. Importantly, that the most of 19 drugs act on two or more MDD-related targets, which may produce the stronger action on gene expression changes and achieve a potent therapeutic effect. Thus, the revealed 19 drugs may represent the promising candidates for the treatment of MDD.
重度抑郁症(MDD)是影响全球数百万人的最常见疾病之一。在许多情况下,使用现有的抗抑郁药无法实现稳定的缓解,这可能是由于对病理机制的理解不足。这表明需要在深入了解MDD病理生理学的基础上开发更有效的药物。由于新药开发成本高且耗时长,药物重新定位可能是一种有前景的替代方法。在本研究中,我们应用了最近开发的DIGEP-Pred方法来识别可诱导与MDD病因相关基因表达变化的药物,随后确定其潜在的MDD相关靶点和抗抑郁作用的分子机制。所应用的方法包括以下步骤。首先,利用构效关系(SARs)预测了全球3690种已批准药物的药物诱导基因表达变化。对预测基因进行疾病富集分析,以确定能显著改变已知MDD相关基因表达的药物。其次,通过基于SAR的预测和网络分析,确定了可能是药物诱导基因表达变化的主要调节因子的潜在药物靶点。根据已发表的数据,仅选择那些潜在靶点与MDD明显相关的药物进行进一步分析。第三,由于潜在的新型抗抑郁药必须分布到脑组织中,因此选择了口服给药的药物,并利用现有实验数据和计算机预测评估它们的血脑屏障通透性。结果,我们确定了19种药物,它们有可能重新用于MDD的治疗。这些药物属于不同的治疗类别,包括肾上腺素能/多巴胺能药物、止吐药、抗组胺药、镇咳药和肌肉松弛剂。其中许多药物已通过实验证实或预测与众所周知的MDD相关蛋白靶点相互作用,如单胺(血清素、肾上腺素、多巴胺)和乙酰胆碱受体及转运体,以及与不太常见的靶点相互作用,包括3型甘丙肽受体(GALR3)、G蛋白偶联雌激素受体1(GPER1)、酪氨酸蛋白激酶JAK3、丝氨酸/苏氨酸蛋白激酶ULK1。重要的是,这19种药物中的大多数作用于两个或更多与MDD相关的靶点,这可能对基因表达变化产生更强的作用,并实现有效的治疗效果。因此,所揭示的这19种药物可能是治疗MDD的有前景的候选药物。