Research Article A New Informatics Framework for Evaluating the Codon Usage Metrics, Evolutionary Models and Phylogeographic Reconstruction of Tomato Yellow Leaf Curl Virus (TYLCV) in Different Regions of Asian Countries

Not AvailableTomato yellow leaf curl virus (TYLCV) is a major devastating viral disease, majorly affecting the tomato production globally. The disease is majorly transmitted by the Whitefly. The Begomovirus (TYLCV) having a six major protein coding genes, among them the C1/AC1 is evidently associated with viral replication. Owing to immense role of C1/AC1 gene, the present study is an initial effort to elucidate the factors shaping the codon usage bias and evolutionary pattern of TYLCV-C1/AC1 gene in five major Asian countries. Based on publicly available nucleotide sequence data the Codon usage pattern, Evolutionary and Phylogeographic reconstruction was carried out. The study revealed the presence of significant variation between the codon bias indices in all the selected regions. Implying that the codon usage pattern indices (eNC, CAI, RCDI, GRAVY, Aromo) are seriously affected by selection and mutational pressure, taking a supremacy in shaping the codon usage bias of viral gene. Further, the tMRCA age was 1853, 1939, 1855, 1944, 1828 for China, India, Iran, Oman and South Korea, respectively for TYLCV-C1/AC1 gene. The integrated analysis of Codon usage bias, Evolutionary rate and Phylogeography analysis in viruses signifies the positive role of selection and mutational pressure among the selected regions for TYLCV (C1/AC1) gene.Not Availabl

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Not AvailableBacillus anthracis is a Gram-positive spore-forming bacterium that causes the zoonotic disease: anthrax, an abrupt illness that disproportionately impacts grazing livestock and wild ruminants. The anthrax’s geographical reach despite years of research on anthrax epizootic and epidemics behaviour, till date remains to be elucidated. Existing therapeutics, however, are ineffective in combating this infectious disease, necessitating the development of a better vaccine to halt the pandemic using immunoinformatics approaches, this study intended to predict an efficient epitope for vaccine against the anthrax in animals and humans of the toxin genes such as cya, lef and pagA of B. anthracis against anthrax. The B-cell and T-cell epitopes were predicted utilizing various bioinformatics tools/software and docking analysis was performed. Consequently, it was found that the evaluated epitopes had no allegenicity, no toxicity and had high antigenicity that provides an effectual and most rapid technique to estimate peptide synthetic vaccines to impede the anthrax.Not Availabl

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Not AvailableKyasanur Forest Disease was ϐirst evolved in the Kyasanur forest, Karnataka. The transmission of the virus has occurred from the monkey to the human by the tick vector. On the early day of viral spread, the disease was restricted to the surrounded region of Kyasanur forest, Shimoga district. But in the present days, the disease has been spreading to neighboring districts and states as well. So, this study involves estimation of codon bias among the gene C, gene E, gene prM, and gene NS5 of the KFD virus and rate of evolution with phylogenetic analysis. The codon usage analysis has revealed the moderate codon bias among all the selected genes and the role of mutation pressure in genesC and E and natural selection in genes- prM and NS5. Also, the tMRCA age was 1942, 1982, 1975, and 1931 of genes- C, E, prM, and NS5, respectively, of the KFD virus. The integrated analysis of codon usage bias and evolutionary rate analysis signiϐies that both mutational pressure and natural selection among the selected genes of the KFD virusNot Availabl

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Not AvailableAngiotensin-converting enzyme 2 (ACE2) is a transmembrane protein that functions as a receptor for coronavirus spike protein. When spike protein fragments as the ligand binds with ACE2 protein, this ACE2 protein functions as a virus receptor, participating in the biological process known as the viral particle entry in the host cell. Hence, an in-silico study was carried out since it is faster and less expensive than trial and error methods based on experimental investigations. To study the effect of Acacia farnesiana phytochemicals on spike protein, molecular docking analyses were carried out. In this study, twelve phytochemicals from Acacia farnesiana have been selected as small molecules based on their ACEI and anti- inflammatory nature to evaluate molecular interaction between spike protein of SARSCoV2 with ACE2 of the human complex molecule. Gallic acid, methyl gallate, kaempferol, Rhamnocitrin, naringenin, apigenin, ellagic acid, ferulic acid, myricetin, Diosmetin, Caffeic acid, and Quercetin were chosen as competent natural compounds from Acacia farnesiana as potent small molecules against COVID-19 and further ADME analysis were carried out. The result indicated that due to the presence of ACEIs and anti-inflammatory phytochemicals in Acacia farnesiana, the bound structure of ACE2 and spike protein becomes unstable. Therefore, these natural compounds can show antiviral activity by destabilizing spike protein binding with the human host ACE2 receptor.Not Availabl

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Not AvailableThe outbreak of novel coronavirus strain (Covid-19) with a high pandemic threat has predict grave public health and economic concerns. This virus, originating from the Wuhan region in China has spread worldwide affecting millions with no registered persuasive targeted therapy. In this paper, we analyze the three important proteins encoded by the virus, envelope protein 5 × 29, RNA binding nucleocapsid protein 1SSK, and spike glycoprotein 6ACD, for an effective virion accumulation, and remdesivir was the first drug approved by the FDA and EMA for the treatment of COVID-19 cases that require hospitalization, there is still much controversy about its efficacy and also an alternative for novel phytochemicals, deoxynojirimycin, trigoneoside IB, and octanoic acid. The in-silico evaluations were conducted using the PyRx virtual screening tools which lead to the target based on high binding affinity. Trigoneoside IB, derived from Trigonella foenum-graecum (Fenugreek), showed the highest binding affinity and stable interaction with the amino acid residues present in active sites of Covid-19 proteins. Meanwhile, the other two compounds derived from Morus alba (Mulberry) and Morinda citrifolia (Noni), as well as the anti-HIV remdesivir drug exhibited good binding affinity and favorable ADME properties. Thereby offering scope for validation of the new therapeutic components for their in vitro and in vivo efficacy against the Covid-19 proteins.Not Availabl

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Not AvailableCrimean-Congo hemorrhagic fever (CCHF) virus is one among the major zoonosis viral diseases that use the Hyalomma ticks as their transmission vector to cause viral infection to the human and mammalian community. The fatality of infectious is high across the world especially in Africa, Asia, Middle East, and Europe. This study regarding codon usage bias of S, M, and L segments of the CCHF virus pertaining to the host Homo sapiens, reveals in-depth information about the evolutionary characteristics of CCHFV. Relative Synonymous Codon Usage (RSCU), Effective number of codons (ENC) were calculated, to determine the codon usage pattern in each segment. Correlation analysis between Codon adaptation index (CAI), GRAVY (Hydrophobicity), AROMO (Aromaticity), and nucleotide composition revealed bias in the codon usage pattern. There was no strong codon bias found among any segments of the CCHF virus, indicating both the factors i.e., natural selection and mutational pressure shapes the codon usage biasNot Availabl

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Not AvailableBackground and Aim: Pestivirus, a genus of the Flaviviridae family, comprises viruses that affect bovines, sheep, and pigs. Symptoms, including hemorrhagic syndromes, abortion, respiratory complications, and deadly mucosal diseases, are produced in infected animals, which cause huge economic losses to the farmers. Bovine viral diarrhea virus-1, bovine viral diarrhea virus-2, classical swine fever virus, border disease virus, Bungowannah, Hobi-like, and atypical porcine pestivirus belonging to the Pestivirus genus were selected for the study. This study aimed to estimate the codon usage bias and the rate of evolution using the glycoprotein E2 gene. Furthermore, codon usage bias analysis was performed using publicly available nucleotide sequences of the E2 gene of all seven Pestiviruses. These nucleotide sequences might elucidate the disease epidemiology and facilitate the development of designing better vaccines. Materials and Methods: Coding sequences of the E2 gene of Pestiviruses A (n = 89), B (n = 60), C (n = 75), D (n = 10), F (n = 07), H (n = 52), and K (n = 85) were included in this study. They were analyzed using different methods to estimate the codon usage bias and evolution. In addition, the maximum likelihood and Bayesian methodologies were employed to analyze a molecular dataset of seven Pestiviruses using a complete E2 gene region. Results: The combined analysis of codon usage bias and evolutionary rate analysis revealed that the Pestiviruses A, B, C, D, F, H, and K have a codon usage bias in which mutation and natural selection have played vital roles. Furthermore, while the effective number of codons values revealed a moderate bias, neutrality plots indicated the natural selection in A, B, F, and H Pestiviruses and mutational pressure in C, D, and K Pestiviruses. The correspondence analysis revealed that axis-1 significantly contributes to the synonymous codon usage pattern. In this study, the evolutionary rate of Pestiviruses B, H, and K was very high. The most recent common ancestors of all Pestivirus lineages are 1997, 1975, 1946, 1990, 2004, 1990, and 1990 for Pestiviruses A, B, C, D, F, H, and K, respectively. This study confirms that both mutational pressure and natural selection have played a significant role in codon usage bias and evolutionary studies. Conclusion: This study provides insight into the codon usage bias and evolutionary lineages of pestiviruses. It is arguably the first report of such kind. The information provided by the study can be further used to elucidate the respective host adaptation strategies of the viruses. In turn, this information helps study the epidemiology and control methods of pestivirusesNot Availabl

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Not AvailableCOVID-19 is the deadliest pandemic, with over 18.2 million people infected with the SARS-CoV-2 virus by August 2, 2021 resulting in human deaths and economic losses. A number of countries have formulated control measures in order to prevent the spread of the virus. However, it is unknown when the outbreak will subside in different countries around the world. The role of predicting the COVID-19 trend is extremely difficult. Indian government has made disease outbreak analysis a priority in order to implement necessary healthcare measures to reduce the impact of this deadly pandemic on human health and country’s economics. The time series data for COVID-19 disease was collected from the website www.covid19india.org and were analyzed using a periodic regression model using the data from 22nd Janaury March 2020 to 01st Febraury 2021 the estimated number of cases until 27 July, 2021 was predicted to develop a stochastic model using periodic regression and were documented in top 10 highly infected states in India. The analysis revealed a increasing pattern for the number of reporting cases in the early days of prediction and decreasing trend for the number of reporting cases in the later days of prediction, which could decrease in future days in Karnataka, West Bengal, Uttar Pradesh, Telangana, Bihar and Haryana states. However, in Madhya Pradesh, Andhra Pradesh, Maharashtra and Tamil Nadu states showed a rapid phase of rise in disease incidence, which is likely to infect a larger population and suggests the disease's pandemic existence over a duration. Our model emphasizes the importance of ongoing and continuous efforts that are in place in all states to minimize occurrence of new cases of infections, so as to potentially improving India's economic wealth with the available resourcesNot Availabl