Deargen, predicted a drug with high potential for treatment of a new coronavirus (2019-nCoV) using the deep-learning technology based AI model MT-DTI. The work is published on the BioRxiv.
The number of people infected with the novel coronavirus from Wuhan, China (2019-nCoV) has been rising steadily, with the latest reported number of cases surpassing 20,000 (at least)—far exceeding the toll of the 2003 SARS epidemic.
Multiple companies have already reported working on vaccine production, including a collaboration between the mRNA company Moderna and the National Institute of Allergy and Infectious Diseases (NIAID), a branch of NIH. But, even quick vaccine development may be too slow to catch up with a growing outbreak.
So we used our pretrained deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI) to identify commercially available drugs that could act on viral proteins of 2019-nCoV.
The result showed that atazanavir, an antiretroviral medication used to treat and prevent the human immunodeficiency virus (HIV), is the best chemical compound, followed by efavirenz, ritonavir, and dolutegravir.
Following the release of the preprint, further predictions for remdesivir, a medication approved by the Drug Review and Evaluation Center (CDE) under the Chinese national Agency for Pharmaceutical Affairs (NMPA) on February 2, showed high efficacy result for 2019-nCoV.
The work is published in the article “Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2), through a drug-target interaction deep learning model” posted on the Science Direct.
You can read whole article through the under button.
We hope our prediction results may support and helpful to experimental therapy options for China and other countries identified 2019-nCoV infection.