*6.5.1 Recent projects, challenges, and future prospects in molecular docking-based drug repositioning against COVID-19*

As a popular bioinformatics method, recently several types of research have been conducted to reposition approved drugs against COVID-19 by means of molecular docking. Despite similar aspects and methodology, the used software, subjected target and ligands can affect the outputs of molecular docking-based drug repositioning [54, 63]. In **Table 3**, some recently published works associated with molecular docking-based drug repurposing are presented. Based on our best knowledge, *SARS-CoV-2* main protease is the most popular target for drug discovery research due to the absence of closely related homologs in humans. Additionally, some host cell proteins such as Angiotensin-converting enzyme 2 (ACE2), Transmembrane Serine Protease 2 (TMPRSS2), Furin, Cathepsin L, Adaptor-Associated Kinase 1 (AAK1), and Two-Pore Channel (TPC2) have also been regarded for drug discovery against COVID-19. However, due to probable side effects, drug repurposing based on host cell targets received less attention.

*Evaluation of Drug Repositioning by Molecular Docking of Pharmaceutical Resources… DOI: http://dx.doi.org/10.5772/intechopen.101395*


#### **Table 3.**

*Recently published molecular docking-based drug repositioning research for introducing novel drugs against COVID-19.*

Regarding the subjected ligands evaluation of their anti-COVID-19 potentials, there are several choices, including approved standard drugs, approved natural products, plant secondary metabolites, and under investigation drugs. Due to the time-consuming approval drug process as well as unexpected side effects, drug repurposing based on the approved drugs database is highly recommended [69, 70]. Despite the advantages of in silico drug repositioning against COVID-19, due to differences between natural drug-target micro-environments and drug-target simulations, the discrepancy between the laboratory results and the simulation outputs is expected. Therefore, a recently mixed approach, which is the combination of computational and empirical methods is proposed to fast and accurate drug repositioning [5].
