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Simple Summary: Coronaviruses are serious pathogens for both humans and animals. The name corona was designated because of the crown-like spikes on their surface. Currently, seven coronaviruses have been identified, such as 229E, NL63, OC43, HKU1, MERS-CoV, SARS-CoV, and SARS-CoV-2. Sometimes, animal coronaviruses infect humans and evolve due to genetic mutations, interspecies transmission, host adaptations, and favorable conditions. The main objective of this study was to analyze the genetic diversity and predict the emergence of new variants with novel properties. It has been reported that the spike protein gene plays an important role in host cell attachment and entry into host cells. The S gene has the highest mutation/deletion and is the most utilized target for vaccine/antiviral development. In this work, we discussed the genetic diversity, phylogenetic relationship, and recombination patterns of selected HCoVs with an emphasis on the newly emerged SARS-CoV-2 and MERS-CoV. The findings of this study showed that MERS-CoV and SARS-CoV-2 have significant sequence identities with the selected HCoVs. The phylogenetic and recombination results concluded that new variants may emerge in the future with novel properties that infect both humans and animals. This information will be helpful for global society to design and develop an effective vaccine and disease management strategy. Human coronaviruses (HCoVs) are seriously associated with respiratory diseases in humans and animals. The first human pathogenic SARS-CoV emerged in 2002–2003. The second was MERS-CoV, reported from Jeddah, the Kingdom of Saudi Arabia, in 2012, and the third one was SARS-CoV-2, identified from Wuhan City, China, in late December 2019. The HCoV-Spike (S) gene has the highest mutation/insertion/deletion rate and has been the most utilized target for vaccine/antiviral development. In this manuscript, we discuss the genetic diversity, phylogenetic relationships, and recombination patterns of selected HCoVs with emphasis on the S protein gene of MERS-CoV and SARS-CoV-2 to elucidate the possible emergence of new variants/strains of coronavirus in the near future. The findings showed that MERS-CoV and SARS-CoV-2 have significant sequence identity with the selected HCoVs. The phylogenetic tree analysis formed a separate cluster for each HCoV. The recombination pattern analysis showed that the HCoV-NL63-Japan was a probable recombinant. The HCoV-NL63-USA was identified as a major parent while the HCoV-NL63-Netherland was identified as a minor parent. The recombination breakpoints start in the viral genome at the 142 nucleotide position and end at the 1082 nucleotide position with a 99% CI and Bonferroni-corrected p-value of 0.05. The findings of this study provide insightful information about HCoV-S gene diversity, recombination, and evolutionary patterns. Based on these data, it can be concluded that the possible emergence of new strains/variants of HCoV is imminent. [ABSTRACT FROM AUTHOR]

The global pandemic of coronavirus disease 2019 (COVID 19) is reported to have started in Wuhan City, Hebei Province, China. It has spread rapidly all over the world, including Saudi Arabia, having a severe health emergency. This new virus was named as the 2019 novel coronavirus (2019-nCoV), and now severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on previous practice and phylogenetic and taxonomic investigations. SARS-CoV-2 belongs to the family of Coronaviridae, Betacoronavirus, Sarbecovirus subgenus, genome β. Throughout the COVID 19 pandemic, several strains of SARS-CoV-2 have been recognized around the world. The SARS-CoV-2 variants have caused significant morbidity and mortality worldwide and in Saudi Arabia as well. The rate at which COVID-19 spread across borders and affected countries has highlighted the significance of health care systems to nations and global operations. This review focuses on the origin, epidemiology, pathophysiology, transmission, and the impact of this disease, while highlighting the knowledge about SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has stressed the global health system to a significant level, which has not only resulted in high morbidity and mortality but also poses a threat for future pandemics. This situation warrants efforts to develop novel therapeutics to manage SARS-CoV-2 in specific and other emerging viruses in general. This study focuses on SARS-CoV2 RNA-dependent RNA polymerase (RdRp) mutations collected from Saudi Arabia and their impact on protein structure and function. The Saudi SARS-CoV-2 RdRp sequences were compared with the reference Wuhan, China RdRp using a variety of computational and biophysics-based approaches. The results revealed that three mutations—A97V, P323I and Y606C—may affect protein stability, and hence the relationship of protein structure to function. The apo wild RdRp is more dynamically stable with compact secondary structure elements compared to the mutants. Further, the wild type showed stable conformational dynamics and interaction network to remdesivir. The net binding energy of wild-type RdRp with remdesivir is -50.76 kcal/mol, which is more stable than the mutants. The findings of the current study might deliver useful information regarding therapeutic development against the mutant RdRp, which may further furnish our understanding of SARS-CoV-2 biology. [ABSTRACT FROM AUTHOR]

The virus that begins from Wuhan China, known as COVID-19 or coronavirus is still a huge panic for humans around the globe. The elimination of this virus from our society needs proper attentions to follows the rule suggested by World Health Organization (WHO). A vast literature on the modeling of this infection in various perspective is available. In the present work, we design a new mathematical model for COVID-19 pandemic by utilizing the real infected cases reported from Kingdom of Saudi Arabia. Initially, we formulate the model with the help of classical integer order nonlinear differential equations. The treatment class is considered the model to analyze the impact of treatment on the disease dynamics. The Caputo-Fabrizio derivative with the non-singular exponential kernel is applied in order to reformulate the proposed COVID-19 transmission model with a fractional order. The biologically important parameter called the basic reproductive number is investigated both theoretically and numerically. The estimated values of R 0 for the selected period are approximated to be 1.63. Further, by making use of the Picard Lindelöf theorem we provide the existence and uniqueness of the COVID-19 fractional epidemic model. Moreover, the fractional model is solved numerically and a number of simulation results are depicted using the real estimated parameters. The impact of various model parameters and memory index are shown graphically. We conclude that the fractional order epidemic models are more appropriate and provide deep insights into the disease dynamics. [ABSTRACT FROM AUTHOR]

The recent coronavirus outbreak from Wuhan China in late 2019 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in a global pandemic of coronavirus-19 disease (COVID-19). Understating the underlying mechanism of the pathogenesis of coronavirus infection is important not only because it will help in accurate diagnosis and treatment of the infection but also in the production of effective vaccines. The infection begins when SARS-CoV-2 enters the cells through binding of its envelope glycoprotein to angiotensin-converting enzyme2 (ACE2). Gene variations of ACE2 and microRNA (miR)-196 are associated with viral infection and other diseases. The present study investigated the association of the ACE2 rs4343 G>A and miR-196a2 rs11614913 C>T gene polymorphisms with severity and mortality of COVID-19 using amplification refractory mutation system PCR in 117 COVID-19 patients and 103 healthy controls from three regions of Saudi Arabia. The results showed that ACE2 rs4343 GA genotype was associated with severity of COVID-19 (OR=2.10, P-value 0.0028) and ACE2 rs4343 GA was associated with increased mortality with OR=3.44, P-value 0.0028. A strong correlation between the ACE2 rs4343 G>A genotype distribution among COVID-19 patients was reported with respect to their comorbid conditions including sex (P<0.023), coronary artery disease (P<0.0001), oxygen saturation <60 mm Hg (P<0.0009) and antiviral therapy (0.003). The results also showed that the CT genotype and T allele of the miR-196a2 rs11614913 C>T were associated with decreased risk to COVID-19 with OR=0.76, P=0.006 and OR=0.54, P=0.005, respectively. These results need to be validated with future molecular genetic studies in a larger sample size and different populations. [ABSTRACT FROM AUTHOR]