Bioinformatics Department, The Cyprus Institute of Neurology and Genetics, Nicosia 2370, Cyprus.
Experimental Pharmacology Laboratory, Medical School, University of Cyprus, Nicosia 2115, Cyprus.
Int J Mol Sci. 2024 May 13;25(10):5319. doi: 10.3390/ijms25105319.
In the area of drug research, several computational drug repurposing studies have highlighted candidate repurposed drugs, as well as clinical trial studies that have tested/are testing drugs in different phases. To the best of our knowledge, the aggregation of the proposed lists of drugs by previous studies has not been extensively exploited towards generating a dynamic reference matrix with enhanced resolution. To fill this knowledge gap, we performed weight-modulated majority voting of the modes of action, initial indications and targeted pathways of the drugs in a well-known repository, namely the Drug Repurposing Hub. Our method, Democracy, exploits this pile of information and creates frequency tables and, finally, a disease suitability score for each drug from the selected library. As a testbed, we applied this method to a group of neurodegenerative diseases (Alzheimer's, Parkinson's, Huntington's disease and Multiple Sclerosis). A super-reference table with drug suitability scores has been created for all four neurodegenerative diseases and can be queried for any drug candidate against them. Top-scored drugs for Alzheimer's Disease include agomelatine, mirtazapine and vortioxetine; for Parkinson's Disease, they include apomorphine, pramipexole and lisuride; for Huntington's, they include chlorpromazine, fluphenazine and perphenazine; and for Multiple Sclerosis, they include zonisamide, disopyramide and priralfimide. Overall, Democracy is a methodology that focuses on leveraging the existing drug-related experimental and/or computational knowledge rather than a predictive model for drug repurposing, offering a quantified aggregation of existing drug discovery results to (1) reveal trends in selected tracks of drug discovery research with increased resolution that includes modes of action, targeted pathways and initial indications for the investigated drugs and (2) score new candidate drugs for repurposing against a selected disease.
在药物研究领域,有几项计算药物再利用研究强调了候选再利用药物,以及在不同阶段测试/正在测试药物的临床试验研究。据我们所知,以前的研究对这些提议的药物清单的聚合并没有被广泛利用,以生成具有增强分辨率的动态参考矩阵。为了填补这一知识空白,我们对药物再利用中心等知名知识库中的药物作用模式、初始适应症和靶向途径进行了加权多数投票。我们的方法 Democracy 利用了这一堆信息,并为所选库中的每种药物创建了频率表,最终为每种药物创建了疾病适宜性评分。作为一个测试平台,我们将该方法应用于一组神经退行性疾病(阿尔茨海默病、帕金森病、亨廷顿病和多发性硬化症)。为所有四种神经退行性疾病创建了具有药物适宜性评分的超级参考表,并可针对任何候选药物对其进行查询。针对阿尔茨海默病的高评分药物包括阿戈美拉汀、米氮平和文拉法辛;针对帕金森病的药物包括阿扑吗啡、普拉克索和溴隐亭;针对亨廷顿病的药物包括氯丙嗪、氟奋乃静和奋乃静;针对多发性硬化症的药物包括佐米曲坦、丙吡胺和吡罗昔康。总的来说,Democracy 是一种专注于利用现有药物相关实验和/或计算知识的方法,而不是药物再利用的预测模型,它提供了对现有药物发现结果的量化聚合,以(1)揭示选定药物发现研究轨道的趋势,分辨率更高,包括所研究药物的作用模式、靶向途径和初始适应症,(2)针对选定疾病对新候选药物进行再利用评分。