Development and repurposing of drugs against COVID-19 using artificial intelligence

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a lineage of Betacoronavirus, is the causative agent of COVID-19, which has caused millions of deaths and crippled economies around the world. Early detection and treatment of COVID-19 cases are crucial for containment and reduction in disease transmission. During an emergency such as a pandemic like COVID-19, when there is a lack of available treatment against a new disease, drug repurposing or repositioning can be an effective strategy to control the disease. Drug repositioning is cost-effective, minimizes failure in clinical trials, and obtains relatively speedy approval from regulatory authorities. Artificial intelligence (AI)-mediated drug repositioning treatment of COVID- 19 patients can speed up the management and medical care for the patients. AI, which includes cognitive computing, deep learning, convolutional neural networks, and machine learning, can identify potential antiviral drugs for treating a disease. The time frame for extracting essential facts, statistics, and evaluation of the existing preapproved and approved drugs using molecular descriptors can be reduced by AI technology. Based on experimental data, different supervised machine learning and deep learning algorithms are implemented as a part of AI strategies to identify the repurposable drug effectively. Screening of presently available drugs and the existing library of natural compounds or novel drug candidates for the treatments against COVID-19 can be based on protein-ligand or protein-peptide interactions, which are facilitated through machine learning and deep learning. Such screening reduces the frequency of failures that might occur in clinical trials. This chapter focuses on repurposing existing drugs using AI strategies, particularly in the context of SARS-CoV-2.