A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

Ge, Yiyue; Tian, Tingzhong; Huang, Suling; Wan, Fangping; Li, Jingxin; Li, Shuya; Yang, Hui; Hong, Lixiang; Wu, Nian; Yuan, Enming; Cheng, Lili; Lei, Yipin; Shu, Hantao; Feng, Xiaolong; Jiang, Ziyuan; Cheng, Ying; Guo, Xiling; Cui, Lunbiao; Liang, Xiao; Zeng, Li; Yang, Chunhao; Miao, Ze‐Hong; Tang, Haidong; Chen, Ligong; Zeng, Hainian; Zhao, Dan; Zhu, Fengcai; Shen, Xiaoxia; Zeng, Jianyang

doi:10.1101/2020.03.11.986836

Cited by 156 publications

(183 citation statements)

References 81 publications

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“…We identified 14 key studies that detailed the antiviral activity of 72 compounds [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] Table 1.…”

Section: Identified Papers and Methodsmentioning

confidence: 99%

Prioritisation of potential anti-SARS-CoV-2 drug repurposing opportunities based on ability to achieve adequate plasma and target site concentrations derived from their established human pharmacokinetics

Arshad

Pertinez

Box

et al. 2020

Preprint

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There is a rapidly expanding literature on the in vitro antiviral activity of drugs that may be repurposed for therapy or chemoprophylaxis against SARS-CoV-2. However, this has not been accompanied by a comprehensive evaluation of the ability of these drugs to achieve target plasma and lung concentrations following approved dosing in humans. Moreover, most publications have focussed on 50% maximum effective concentrations (EC50), which may be an insufficiently robust indicator of antiviral activity because of marked differences in the slope of the concentration-response curve between drugs. Accordingly, in vitro anti-SARS-CoV-2 activity data was digitised from all available publications up to 13 th April 2020 and used to recalculate an EC90 value for each drug. EC90 values were then expressed as a ratio to the achievable maximum plasma concentrations (Cmax) reported for each drug after administration of the approved dose to humans (Cmax/EC90 ratio). Only 14 of the 56 analysed drugs achieved a Cmax/EC90 ratio above 1 meaning that plasma Cmax concentrations exceeded those necessary to inhibit 90% of SARS-CoV-2 replication. A more in-depth assessment of the putative agents tested demonstrated that only nitazoxanide, nelfinavir, tipranavir (boosted with ritonavir) and sulfadoxine achieved plasma concentrations above their reported anti-SARS-CoV-2 activity across their entire approved dosing interval at their approved human dose. For all drugs reported, the unbound lung to plasma tissue partition coefficient (KpUlung) was also simulated and used along with reported Cmax and fraction unbound in plasma to derive a lung Cmax/EC50 as a better indicator of potential human efficacy (lung Cmax/EC90 ratio was also calculable for a limited number of drugs). Using this parameter hydroxychloroquine, chloroquine, mefloquine, atazanavir (boosted with ritonavir), tipranavir (boosted with ritonavir), ivermectin, azithromycin and lopinavir (boosted with ritonavir) were all predicted to achieve lung concentrations over 10-fold higher than their reported EC50. This analysis was not possible for nelfinavir because insufficient data were available to calculate KpUlung but nitozoxanide and sulfadoxine were also predicted to exceed their reported EC50 by 3.1-and 1.5-fold in lung, respectively. The antiviral activity data reported to date have been acquired under different laboratory conditions across multiple groups, applying variable levels of stringency. However, this analysis may be used to select potential candidates for further clinical testing, while deprioritising compounds which are unlikely to attain target concentrations for antiviral activity. Future studies should focus on EC90 values and discuss findings in the context of achievable exposures in humans, especially within target compartments such as the lung, in order to maximise the potential for success of proposed human clinical trials.

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“…We identified 14 key studies that detailed the antiviral activity of 72 compounds [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] Table 1.…”

Section: Identified Papers and Methodsmentioning

confidence: 99%

Prioritisation of potential anti-SARS-CoV-2 drug repurposing opportunities based on ability to achieve adequate plasma and target site concentrations derived from their established human pharmacokinetics

Arshad

Pertinez

Box

et al. 2020

Preprint

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“…Currently, there are many drug candidates in clinical use or undergoing clinical trials worldwide to treat COVID-19. For example, poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218 is in phase 1 clinical trial (Ge et al, 2020). Remdesivir, which was originally developed for the treatment of the Ebola outbreak, was given to a patient in the United States causing the recovery of a patient from the severely ill category (Al-Tawfiq et al, 2020;Gao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Potential Inhibitors of SARS-CoV-2 Main Protease (M<sup>pro</sup>) Identified from the Library of FDA Approved Drugs Using Molecular Docking Studies

Verma¹,

Kapoor²,

S³

et al. 2020

Preprint

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Corona Virus Infectious Disease-2019 (COVID-19) outbreak originated recently at Wuhan, China in December 2019. It has already spread rapidly to more than 200 countries and has been declared a pandemic by WHO. It is caused by a beta-coronavirus named as SARS-CoV-2. There is no definitive cure, either drug or vaccine, to treat or prevent this viral disease. Recently, the crystal structure of the main protease Mpro has been determined. Mpro is responsible for the proteolytic maturation of the polyprotein essential for the viral replication and transcription, which makes it an important drug target. The discovery of new drug molecules may take years before getting to the clinics. So, considering urgency we performed molecular docking studies using FDA approved drugs to identify molecules that could potentially bind to the substrate-binding site and inhibit SARS-CoV-2 main protease (Mpro). We used the Glide module in Schrodinger software suite to perform molecular docking studies followed by MM-GBSA based energy calculations to score the hit molecules. Molecular docking and manual analysis suggest that several drugs may bind and potentially inhibit Mpro. We also performed molecular simulations studies for selected compounds to evaluate protein-drug interactions. Interestingly, we observed only one antiviral compound, Adefovir, in the top50 list of compounds. Considering bioavailability, lesser toxicity, route of administration some of the top-ranked drugs including lumefantrine (antimalarial), dipyridamole (coronary vasodilator), dihydroergotamine (used for treating migraine), hexoprenaline (anti- asthmatic), riboflavin (vitamin B2) and pantethine (vitamin B5) may be taken forward for further in vitro and in vivo experiments to investigate their therapeutic potential.

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“…A number of biomedical studies have already applied ML techniques in their work on surveillance, trends, and clinical predictors for the ongoing pandemic (e.g., Alimadadi et al, 2020;Carrillo-Larco & Castillo-Cara, 2020;Ge et al, 2020;Kim et al, 2020;Kumar et al, 2020;Rao and Vazquez, 2020;Yan et al, 2020). Our novel application of ML methods to available coronavirus abstracts, including those about COVID-19, offers insights into the themes of COVID-19 research that overlap with studies about other coronaviruses.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Maps Research Needs in COVID-19 Literature

Doanvo

Qian

Ramjee

et al. 2020

Preprint

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Manually assessing the scope of the thousands of publications on the COVID-19 (coronavirus disease 2019) pandemic is an overwhelming task. Shortcuts through metadata analysis (e.g., keywords) assume that studies are properly tagged. However, machine learning approaches can rapidly survey the actual text of coronavirus abstracts to identify research overlap between COVID-19 and other coronavirus diseases, research hotspots, and areas warranting exploration. We propose a fast, scalable, and reusable framework to parse novel disease literature. When applied to the COVID-19 Open Research Dataset (CORD-19), dimensionality reduction suggested that COVID-19 studies to date are primarily clinical-, modeling-or field-based, in contrast to the vast quantity of laboratory-driven research for other (non-COVID-19) coronavirus diseases. Topic modeling also indicated that COVID-19 publications have thus far focused primarily on public health, outbreak reporting, clinical care, and testing for coronaviruses, as opposed to the more limited number focused on basic microbiology, including pathogenesis and transmission.

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A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

Cited by 156 publications

References 81 publications

Prioritisation of potential anti-SARS-CoV-2 drug repurposing opportunities based on ability to achieve adequate plasma and target site concentrations derived from their established human pharmacokinetics

Prioritisation of potential anti-SARS-CoV-2 drug repurposing opportunities based on ability to achieve adequate plasma and target site concentrations derived from their established human pharmacokinetics

Potential Inhibitors of SARS-CoV-2 Main Protease (M<sup>pro</sup>) Identified from the Library of FDA Approved Drugs Using Molecular Docking Studies

Machine Learning Maps Research Needs in COVID-19 Literature

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