Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, Cornell University, Belfer Research Building, 5th floor, 413 E. 69th St., New York, NY, 10021, USA.
Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Mol Med. 2021 Sep 9;27(1):105. doi: 10.1186/s10020-021-00356-6.
Vaccination programs have been launched worldwide to halt the spread of COVID-19. However, the identification of existing, safe compounds with combined treatment and prophylactic properties would be beneficial to individuals who are waiting to be vaccinated, particularly in less economically developed countries, where vaccine availability may be initially limited.
We used a data-driven approach, combining results from the screening of a large transcriptomic database (L1000) and molecular docking analyses, with in vitro tests using a lung organoid model of SARS-CoV-2 entry, to identify drugs with putative multimodal properties against COVID-19.
Out of thousands of FDA-approved drugs considered, we observed that atorvastatin was the most promising candidate, as its effects negatively correlated with the transcriptional changes associated with infection. Atorvastatin was further predicted to bind to SARS-CoV-2's main protease and RNA-dependent RNA polymerase, and was shown to inhibit viral entry in our lung organoid model.
Small clinical studies reported that general statin use, and specifically, atorvastatin use, are associated with protective effects against COVID-19. Our study corroborrates these findings and supports the investigation of atorvastatin in larger clinical studies. Ultimately, our framework demonstrates one promising way to fast-track the identification of compounds for COVID-19, which could similarly be applied when tackling future pandemics.
全球已启动疫苗接种计划以遏制 COVID-19 的传播。然而,对于那些等待接种疫苗的人来说,如果能发现具有联合治疗和预防作用的现有安全化合物,将是有益的,尤其是在疫苗供应最初可能有限的欠发达国家。
我们采用了一种数据驱动的方法,将大规模转录组数据库(L1000)的筛选结果与分子对接分析相结合,并使用 SARS-CoV-2 进入的肺类器官模型进行体外测试,以鉴定具有针对 COVID-19 的潜在多模式特性的药物。
在考虑了数千种已批准的 FDA 药物后,我们观察到阿托伐他汀是最有前途的候选药物,因为它的作用与感染相关的转录变化呈负相关。阿托伐他汀进一步被预测可与 SARS-CoV-2 的主要蛋白酶和 RNA 依赖性 RNA 聚合酶结合,并在我们的肺类器官模型中显示出抑制病毒进入的作用。
一些小型临床研究报告称,他汀类药物的一般使用,特别是阿托伐他汀的使用,与 COVID-19 的保护作用有关。我们的研究证实了这些发现,并支持在更大的临床研究中对阿托伐他汀进行研究。最终,我们的框架展示了一种快速鉴定 COVID-19 化合物的有前途的方法,该方法也可应用于应对未来的大流行。