الفهرس 
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Abstract
COVID-19 is a highly contagious illness caused by the SARS-CoV-2 virus which belongs to the coronavirus family. According to WHO the total number of COVID-19 confirmed cases were 167,510,005 including 3,477,917 deaths case and a 1.5% death rate. The SARS-CoV-2 virus is 81% similar to SARS-CoV, referring to the closest viruses from the same virus family, both SARS-CoV and MERS-CoV caused limited pandemics compared with that of SARS-CoV-2. The high rate of disease spreads and there is no definitive cure or vaccine to eradicate the disease, making the efforts of scientists and researchers multiply for a deeper understanding of how the disease spreads and infection occurs.
Bioinformatics is a computational tool used for many purposes of biological analysis, genome sequences and protein sequences analyzes are some of the most important analyzes that bioinformatics contributes to understanding many viruses and the diseases that caused by them and how to diagnose the disease and treat the infected ones. In this study python framework was used which is a bioinformatics tool, where it is ranked as one of the most popular programming languages and this is due to the variety of its features, for example, it is free and easy to learn, it appeared to have better character string manipulation capabilities than Perl. It provides lower-order sequencing methodologies, lower cost, and high precision.
Using the python framework, the genome and protein sequences of SARS-CoV-2, SARS-CoV and MERS-CoV were compared in China and the Middle East. The comparison revealed that SARS-CoV-2 tends to reduce GC content, the adhesion strength between S protein of SARS-CoV-2 is greater than that of SARS-CoV and MERS-CoV. E protein in MERS-CoV has a noticeable difference from that of SARS-CoV-2 and SARS-CoV. E protein and M protein have roles that are no less important than that of S protein in viral infection and replication. M protein is used as a marker in diagnostic tests. 1ab ORF protein and 1a ORF protein of SARS-CoV-2 have great similarity with that of SARS-CoV while they differ from that of MERS-CoV. Analysis of crystal structure of SARS-CoV-2 S
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protein RBD and SARS-CoV S protein RBD shows that the binding force between SARS-CoV-2 S protein and ACE2 receptor is greater than that of SARS-CoV due to the presence of water and hydrogen bonds also the high hydrophobicity effect of SARS-CoV-2.
A comparison has been made between SARS-CoV-2 in five different countries as follows, USA, France, Brazil, China, and the Middle East, they have great similarities and slightly different, this difference shows the geographical impact on the virus and the strength of its spread and mutation from one place to another. Understanding the structure of the virus and pathogenesis by comparing it to its closest viruses allows the researchers to find the best drugs to eliminate this epidemic, which has taken a huge toll on the lives and economies worldwide.
5.2 Conclusions and recommendations
In this era, bioinformatics is booming, where it raises researchers’ ability to understand and manage global challenges. Bioinformatics provides a huge amount of information about DNA, RNA, proteins, and the ecosystem. from its contribution to the eradication of the new pandemics and the discovery of new antibiotics, the roles of bioinformatics vary and its ability to make important contributions in the medical and research fields. Recent advances in bioinformatics and biological sciences have helped researchers to give greater attention to the role of bioinformatics in a larger field of coronaviruses research. Biopython is an open-source python tool of bioinformatics used for multiple purposes such as genome sequences analysis, sequences plotting and manipulation, cluster analysis, and population genetics. Using python framework is one of the best bioinformatics tools which provides lower-order sequencing methodologies and high precision. This high precise analysis that results from bioinformatics also contributes to making comparisons between some known viruses and their mutated counterparts that contribute strongly to the containment of a global pandemic such as the COVID-19 pandemic.
In conclusion, coronaviruses research literature supports the importance of bioinformatics as an effective tool in COVID-19 diagnosis and treatment and it refers to the importance of computational sciences in the medical field, python framework was recommended as a bioinformatics tool, where it is free and easy to learn, it appeared to have
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better character string manipulation capabilities than Perl. it provides lower-order sequencing methodologies, lower cost, and high precision, Python modules can be written in the python language also be written in other languages such as C. Data analysis of genomes and proteins of human coronaviruses refers to the crucial role of GC content in virus replication with lower energy consumption, most of the researchers’ attention is directed towards S protein and its role in the host cell penetration, but according to the results has been reached in this study, both M and E proteins were recommended to take the same research interest due to their significant roles in the viral infection and replication, the same goes for accessory proteins where some functions of accessory proteins are still not understood and require more studies where it was found that there are some functions of accessory proteins not involved directly in the virus replications inside the host cell but affect the pathogenesis. Crystal structure of S protein of SARS-COV-2 illustrates the interaction between S protein and the ACE2 of the host cell and the crucial role of hydrophobicity in S protein- ACE 2 interaction. Finally, this study hypothesizes that geographic organizing is the result of originator impacts happening as a result of and nearby advancement happening after long-distance dispersal. More studies are needed to describe how the differences affect the functions and pathogenesis of SARS-CoV-2. Based on this analysis it has been found that SARS-CoV-2 had the highest similarities with SARS-CoV and was less related to MERS-CoV.