Bioinformatics Department, The Cyprus Institute of Neurology and Genetics, Cyprus.
The Cyprus School of Molecular Medicine, Cyprus.
Brief Bioinform. 2021 Nov 5;22(6). doi: 10.1093/bib/bbab114.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for coronavirus disease 2019 (COVID-19). Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs. Our approach resulted in a highly informed integrated drug shortlist by combining structural diversity filtering along with experts' curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src tyrosine kinase (bosutinib, dasatinib, cytarabine and saracatinib), which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflammatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action. Overall, this multiplex drug repurposing approach, developed and utilized herein specifically for SARS-CoV-2, can offer a rapid mapping and drug prioritization against any pathogen-related disease.
严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 大流行无疑是自 1918 年流感爆发以来最严重的全球卫生紧急事件。根据其进化轨迹，预计该病毒将作为一种地方性传染性呼吸道疾病存在，表现出季节性爆发。因此，尽管人们前所未有地团结一致，希望研制出一种能够广泛免疫的疫苗，但同样重要的是要找到针对 2019 年冠状病毒病 (COVID-19) 的有效预防和治疗方案。为此，我们从患者、细胞系和数据库中整理和分析了多源和多组学的公开可用数据，以推动多药物重新利用的计算方法。我们设计了一种基于网络的多组学数据整合方法，以确定与 COVID-19 最相关的最重要基因，并对确定的候选药物进行重新排序。我们的方法通过结合结构多样性过滤、专家策展以及对所示分子途径的药物靶点映射，对候选药物进行了高度信息整合，从而得出了一个高度综合的候选药物清单。除了最近提出的已经产生有希望结果的药物，如地塞米松和瑞德西韦，我们的清单还包括Src 酪氨酸激酶抑制剂（博舒替尼、达沙替尼、阿糖胞苷和沙卡替尼），它们似乎参与了 COVID-19 的多种病理生理机制。此外，我们还强调了一些特定的免疫调节剂和抗炎药物，如 dactolisib 和甲氨蝶呤，以及组蛋白去乙酰化酶抑制剂，如水杨酸和伏立诺他，它们在作用机制中可能具有有益的效果。总的来说，这种针对 SARS-CoV-2 的多药物重新利用方法可以快速针对任何与病原体相关的疾病进行药物筛选和优先级排序。
