**1. Introduction**

Coronaviruses (CoVs) are positive-strand RNA viruses belonging to the order of *Nidovirales* including three families *Arteriviridae*, *Coronaviridae*, and *Roniviridae* [1]. Relied on the genetic studies, they classify CoVs into four genera as alpha, beta, gamma, and delta CoVs [2]. The diameter of CoVs is between 80 to 120 nm and their shapes are spherical. The fundamental structural proteins of CoVs are envelope (E), membrane (M), nucleocapsid (N), and spike (S) [1]. Its RNA genome composes of six to ten open reading frames (ORFs) [3].

The new studies will fill the knowledge gaps to reveal how the virus is evolving and adapting to new conditions. In recent years, the advanced findings on nucleic acid amplification technologies have been the reason for improving of automated DNA sequencing with the help of bioinformatics tools to characterize and classification of all kinds of infectious disease agents. One of the single-stranded RNA viruses, the Coronaviruses, has been classified using molecular tools. On sequence analysis, the genomes were identified by direct RNA extraction of the clinical

specimens isolated from nasopharyngeal aspirate or stool, as the template, since the viruses are non-cultivable [4–11]. The collection of SARS-CoV-2 sequences has been started in 2020 under the GISAID database. The analysis of viral genomes provided the preventing of possible viral mutations during *in vitro* viral replication. These provided data helped us to understand the virus, threatening the world health, at genomic and *in silico* levels, which gave rise to new experiments carried out in the laboratory. Protein function prediction methods mainly fall into sequence- and structure-based approaches. Using precisely important databases and tools relied on comparison for sequence, structural differentiation, and gene ontology enables us to find exact protein function annotation [12]. Given the destructive effect of the virus SARS-CoV-2 on human health and its contagious virulence, it has attracted the attention of researchers to find its efficiently curative method. We have realized that antiviral chemotherapy with small molecules for their properties as nucleoside analogs can identify new uncharacterized viral genes for producing antiviral drugs related to viral glycoproteins to cellular receptors, viral regulatory proteins. These drugs may block the synthesis and replication of the viral genome that induce the host immune response [13, 14].

These targeted regions can reduce the crucial function required for survival of the virus, by polymerase and/or protease assay enabled us getting of high throughput screening for identification of inhibitor small molecules and enzymes, which can be beneficial for the development of effective antiviral components and synthesized novel molecules [15]. Understanding of viral gene products could overcome the challenge of the development of antiviral drugs contributing to essential functions on the virus, with assays carried out *in vitro* considering molecular mechanisms involved in gene products and biochemical processes. New technology related to omics science is suggesting novel possibilities to find the right answers to inquiries resulting from unexplored pathogenic behavior of the virus. Bioinformatics promises to generate new knowledge on virus and host interaction that can help drive the efforts in more detail to the discovery and development of antiviral therapies [16]. Genomics, proteomics, and related technologies will also be beneficial in molecular virology as suited techniques and approaches for big data.

### **2. Bioinformatics and computational tools**

The progress in the fields of genomics and proteomics are encouraging biological studies on the virus. Genomic sequences and bioinformatics are also major tools in this field and quantities of raw data which has tremendously increased besides their complexity. Therefore, significant computational resources required to manage the volumes of data and their manipulation, researchers studying in these fields for any future drug discovery projects are using these new technologies. Bioinformatics resources (GISAID; NCBI) required to analyze the data, identify patterns and display the patterns help to investigators for understanding the problem, testing, and confirmation of their hypothesis in the laboratory to focus on prioritized compounds or genes [17]. Computational methods applied in the study of SARS-CoV-2 could be paved for the characterization of the virus collected from unique specimens and comparison with similar genomes resulted from sequence similarity. Comprehensively studied investigations on the characterization of the viruses to set a unique set of well-described genomes compared within each other have been reported [18]. Bioinformatics workflows and tools related to SARS-CoV-2 to the detection of potential drug targets and providing beneficial knowledge on

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

therapeutic strategies have also been recently acknowledged [19]. New bioinformatics tools applied to these genomes to test their ability and to predict the organization of viral genes involving coding capacity and the function of the viral proteins are commonly used [20]. These tools are assisting for the confirmation of transcriptional patterns, gene expression, and gene function which are essential studies earlier than *in vitro* studies not to lose time and labor cost [21].

Data relevant to the discovery of new drugs contain information related to biological function, chemical structure, and the biologic activity of small molecules that all findings can help for the searching for new compounds. Even the nature of this problem is inherently complex, bioinformatics is a useful tool to handle the volumes of data required with databases. Small molecule inhibitors could target the computational methods, suggesting aspects of the viral genomic property. Then they may be the reason for identification of the small molecules well-described with their biological effects, which could be used to probe for following of the cellular functions related to chemical structure, protein structure, biochemical activity, and biologic activity of the virus. As another branch of data mining on whole existing data shows a way for screening on inhibitory chemicals with known biochemical activities according to their chemical classes.
