Potential targets and plausible drugs of Coronavirus infection caused by 2019-nCoV

Almasi, Faezeh; Mohammadipanah, Fatemeh

doi:10.22541/au.158766083.33108969

Cited by 2 publications

(1 citation statement)

References 68 publications

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“…Mouthwash containing sodium lauryl sulfate may be effective in preventing SARS-CoV-2 infection through the oral cavity (Sawa et al, 2021 ). The 18-kDa cytoplasmic protein procyclin A is an important cellular biomolecule required for RNA virus replication, and recent studies have shown that non-immunosuppressive analogs, such as alisporivir, inhibit the activity of procyclins (Almasi and Mohammadipanah, 2020 ). Saracatinib, sirolimus, and suramin have also been indicated as therapeutic agents for COVID-19 in recent studies (Romanelli and Mascolo, 2020 ; Salgado-Benvindo et al, 2020 ; Tatar et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

WLLP: A weighted reconstruction-based linear label propagation algorithm for predicting potential therapeutic agents for COVID-19

Chen

Lin²,

Xu³

et al. 2022

Front. Microbiol.

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The global coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV) has led to a huge health and economic crises. However, the research required to develop new drugs and vaccines is very expensive in terms of labor, money, and time. Owing to recent advances in data science, drug-repositioning technologies have become one of the most promising strategies available for developing effective treatment options. Using the previously reported human drug virus database (HDVD), we proposed a model to predict possible drug regimens based on a weighted reconstruction-based linear label propagation algorithm (WLLP). For the drug–virus association matrix, we used the weighted K-nearest known neighbors method for preprocessing and label propagation of the network based on the linear neighborhood similarity of drugs and viruses to obtain the final prediction results. In the framework of 10 times 10-fold cross-validated area under the receiver operating characteristic (ROC) curve (AUC), WLLP exhibited excellent performance with an AUC of 0.8828 ± 0.0037 and an area under the precision-recall curve of 0.5277 ± 0.0053, outperforming the other four models used for comparison. We also predicted effective drug regimens against SARS-CoV-2, and this case study showed that WLLP can be used to suggest potential drugs for the treatment of COVID-19.

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