**6. Computational drug repositioning**

Because of the costly, time-consuming, and complexity of De novo drug discovery, until now all proposed anti-COVID-19 drug candidates are repurposed drugs. Drug repurposing also known as drug re-tasking is a procedure of recognizing new therapeutic application(s) for previously approved, failed, investigational, and or already marketed drugs. Naturally, the drug-repurposing process is based on two fundamental principles including interdependence between different diseases and the confounding nature of drugs. Therefore, drug-repositioning approaches could be categorized into drug-based and disease-based strategies.

The drug-based strategies are vastly based on drug-related data and are used for better understanding the role of pharmacological properties and defining the possibility of defining new pharmaceutical capabilities. Despite the advantages of experimental drug repositioning, the fact that it was time consuming still remained as the main limitation for drug discovery, especially in a pandemic condition. Furthermore, conventional methods use small datasets and biological networks, which may lead to unreliable discoveries.

Nowadays, different computational methods have been introduced that can accelerate the drug-repositioning process [27]. In the next sections, the most common computational approaches for drug repositioning are propounded.
