Antivirals for Monkeypox Virus: Proposing an Effective Machine/Deep Learning Framework

Abstract

Monkeypox is one of the infectious viruses which caused morbidity and mortality problems in these years. Despite its danger to public health, there is no approved drug to stand and handle Monkeypox. On the other hand, drug repurposing is a promising screening method for the low-cost introduction of approved drugs for emerging diseases and viruses which utilizes computational methods. Therefore, drug repurposing is a promising approach to suggesting approved drugs for the monkeypox virus. This paper proposes a computational framework for monkeypox antiviral prediction. To do this, we have geenrated a new virus-antiviral dataset. Moreover, we applied several machine learning and one deep learning method for virus-antiviral prediction. The suggested drugs by the learning methods have been investigated using docking studies. To the best of our knowledge, this work is the first work to study deep learning methods for the prediction of monkeypox antivirals. The screening results confirm that Tilorone, Valacyclovir, Ribavirin, Favipiravir, and Baloxavir marboxil are effective drugs for monkeypox treatment.