Background

Since the beginning of the novel coronavirus (SARS-CoV-2) disease outbreak, there has been an increasing interest in finding a potential therapeutic agent for the disease. Considering the matter of time, the computational methods of drug repurposing offer the best chance of selecting one drug from a list of approved drugs for the life-threatening condition of COVID-19. The present systematic review aims to provide an overview of studies that have used computational methods for drug repurposing in COVID-19.

Methods

We undertook a systematic search in five databases and included original articles in English that applied computational methods for drug repurposing in COVID-19.

Results

Twenty-one original articles utilizing computational drug methods for COVID-19 drug repurposing were included in the systematic review. Regarding the quality of eligible studies, high-quality items including the use of two or more approved drug databases, analysis of molecular dynamic simulation, multi-target assessment, the use of crystal structure for the generation of the target sequence, and the use of AutoDock Vina combined with other docking tools occurred in about 52%, 38%, 24%, 48%, and 19% of included studies. Studies included repurposed drugs mainly against non-structural proteins of SARS-CoV2: the main 3C-like protease (Lopinavir, Ritonavir, Indinavir, Atazanavir, Nelfinavir, and Clocortolone), RNA-dependent RNA polymerase (Remdesivir and Ribavirin), and the papain-like protease (Mycophenolic acid, Telaprevir, Boceprevir, Grazoprevir, Darunavir, Chloroquine, and Formoterol). The review revealed the best-documented multi-target drugs repurposed by computational methods for COVID-19 therapy as follows: antiviral drugs commonly used to treat AIDS/HIV (Atazanavir, Efavirenz, and Dolutegravir Ritonavir, Raltegravir, and Darunavir, Lopinavir, Saquinavir, Nelfinavir, and Indinavir), HCV (Grazoprevir, Lomibuvir, Asunaprevir, Ribavirin, and Simeprevir), HBV (Entecavir), HSV (Penciclovir), CMV (Ganciclovir), and Ebola (Remdesivir), anticoagulant drug (Dabigatran), and an antifungal drug (Itraconazole).

Conclusions

The present systematic review provides a list of existing drugs that have the potential to influence SARS-CoV2 through different mechanisms of action. For the majority of these drugs, direct clinical evidence on their efficacy for the treatment of COVID-19 is lacking. Future clinical studies examining these drugs might come to conclude, which can be more useful to inhibit COVID-19 progression.

中文翻译：

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用于治疗 COVID-19 的计算药物发现和重新利用：系统评价

背景

自新型冠状病毒（SARS-CoV-2）疾病爆发以来，人们对寻找该疾病的潜在治疗剂越来越感兴趣。考虑到时间问题，药物再利用的计算方法提供了从批准药物列表中选择一种药物治疗危及生命的 COVID-19 的最佳机会。本系统综述旨在概述使用计算方法进行 COVID-19 药物再利用的研究。

方法

我们在五个数据库中进行了系统搜索，并收录了应用计算方法在 COVID-19 中重新利用药物的英文原创文章。

结果

系统评价中纳入了 21 篇利用计算药物方法进行 COVID-19 药物再利用的原创文章。关于合格研究的质量，高质量项目包括使用两个或多个批准的药物数据库、分子动力学模拟分析、多靶点评估、使用晶体结构生成靶点序列以及使用在纳入的研究中，AutoDock Vina 与其他对接工具结合使用的比例约为 52%、38%、24%、48% 和 19%。研究包括主要针对 SARS-CoV2 非结构蛋白的重新利用药物：主要的 3C 样蛋白酶（洛匹那韦、利托那韦、茚地那韦、阿扎那韦、奈非那韦和氯可龙）、RNA 依赖性 RNA 聚合酶（瑞德西韦和利巴韦林）和木瓜蛋白酶类蛋白酶（麦考酚酸、特拉匹韦、波普匹韦、格拉佐匹韦、达芦那韦、氯喹和福莫特罗）。该审查揭示了通过计算方法重新用于 COVID-19 治疗的记录最齐全的多靶点药物如下：常用于治疗 AIDS/HIV 的抗病毒药物（阿扎那韦、依非韦伦和多替拉韦、利托那韦、拉替拉韦和达芦那韦、洛匹那韦、沙奎那韦、奈非那韦和茚地那韦）、HCV（格拉佐瑞韦、洛米布韦、阿舒瑞韦、利巴韦林和西米普韦）、HBV（恩替卡韦）、HSV（喷昔洛韦）、CMV（更昔洛韦）和埃博拉病毒（瑞德西韦）、抗凝药物（达比加群）和抗真菌药物药物（伊曲康唑）。

结论

本系统综述提供了一系列可能通过不同作用机制影响 SARS-CoV2 的现有药物。对于这些药物中的大多数，缺乏其治疗 COVID-19 功效的直接临床证据。未来检查这些药物的临床研究可能会得出结论，这些药物对于抑制 COVID-19 的进展可能更有用。