**4. Drug discovery by means of omics data on SARS-CoV-2**

Genomics and proteomics are promising new areas affecting apparently whole biological fields with widespread data and tools provided by databases.

#### **Figure 1.**

*The experiment-based approach is activity-based repositioning of original drugs for new pharmacological indications based on experimental assays, which involves protein target-based and cell/organism-based screening* in vitro *and/or* in vivo *assays. These studies are followed with cell assay, animal model approach and clinical approach. Illustration was created with BioRender.com by the authors of this chapter.*

*Utilization from Computational Methods and Omics Data for Antiviral Drug Discovery… DOI: http://dx.doi.org/10.5772/intechopen.98319*

The DNA Data Bank of Japan (DDBJ)(https://www.ddbj.nig.ac.jp/), GISAID initiative (https://www.gisaid.org/), National Center for Biotechnology Information (The GenBank)(http://www.ncbi.nlm.nih.gov/) and The European Bioinformatics Institute (EMBL-EBI) (http://www.ebi.ac.uk/) are important resources to researchers as nucleotide databases provided on the web. Most functions in micro/ macro organism are directed by interactions of proteins and ligands. Hence, computational techniques comprising *in silico* techniques to predict the protein complex formed can be remarkably cheaper and quicker than experimental methods. They are being a guide for subsequent targeted experiments before initiating *in vitro* studies cause of their predictive capability. Predicting the binding possibilities of multiple proteins is critical for understanding their biological function in any target organism to design of drugs addressing the impairment of biological processes (**Figure 1**). Many solutions generated from a pair of static molecular structures with scoring function comprise the specific position of each atom, giving rise to the simulation of modeling that is seriously sensitive to the specific packing of atoms at the interface [31–33]. For modeling the protein, dynamics and correct protein arrangement are required, considering scoring functions related to the feature of docking poses using techniques such as molecular dynamics (MD) [34, 35].

### **5. Importance of drug discovery and molecular docking**

The docking method relies on steric complementarity at the protein–protein interface level. These interfaces are observed in co-crystallized complexes available in the Protein Data Bank (PDB). They have been the major driving force in the development of docking with the addition of physicochemical and statistics-based properties [36, 37].

Homology modeling and protein prediction analysis enables us to test different proteins on SARS-CoV-2 with various ligands. Analysis by protein-ligand docking servers (**Table 1**) is available for geometric shape complementarity score (GSC score) and approximate interface area (AI area). Additionally, different softwarebased tools for molecular dynamic analysis could be used. The interaction analysis of protein-ligand complexes and their amino acid position with bond distances calculated and visualized through the software provides an opportunity for molecular docking simulations. Protein docking servers can confirm the results within the protein and ligand [44]. They can get an insight into their all binding preferences within the active site of the protein and ligand (**Figure 2**).


#### **Table 1.**

*List of most commonly used protein-ligand softwares, comprising the updated ones.*

**Figure 2.** *Protein- ligand interaction illustration from Baysal et al. [13]. Arrows indicate the binding possibilities.*
