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Mahdavi, B.

Publications and source records attributed to Mahdavi, B..

2 recordsLinked to original sources

SARS-CoV-2 Non-Structural Protein 1(NSP1) Mutation Virulence and Natural Selection: Evolutionary Trends in the Six Continents

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an unsegmented positivesense single-stranded RNA virus that belongs to the {beta}-coronavirus. This virus was the cause of a novel severe acute respiratory syndrome in 2019 (COVID-19) that emerged in Wuhan, China at the early stage of the pandemic and rapidly spread around the world. Rapid transmission and reproduction of SARS-CoV-2 threaten worldwide health with a high mortality rate from the virus. According to the significant role of non-structural protein 1 (NSP1) in inhibiting host mRNA translation, this study focuses on the link between amino acid sequences of NSP1 and alterations of them spreading around the world. The SARS-CoV-2 NSP1 protein sequences were analyzed and FASTA files were processed by Python language programming libraries. Reference sequences compared with each NSP1 sample to identify every mutation and categorize them were based on continents and frequencies. NSP1 mutations rate divided into continents were different. Based on continental studies, E87D in global vision and also in Europe notably increased. The E87D mutation has significantly risen especially in the last months of the study as the first frequent mutation observed. The remarkable mutations, H110Y and R24C, have the second and third frequencies, respectively. Based on this mutational information, despite NSP1 being a conserved sequence occurrence, these mutations change the rate of flexibility and stability of the NSP1 protein, which can eventually affect inhibiting the host translation. IMPORTANCEIn this study, we analyzed 6,510,947 sequences of non-structural protein 1 as a conserved region of SARS-CoV-2. According to the obtained results, 93.4819% of samples had no mutant regions on their amino acid sequences. Heat map data of mutational samples demonstrated high percentages of mutations that occurred in the region of 72 to 126 amino acids indicating a hot spot region of the protein. Increased rates of E87D, H110Y, and R24C mutations in the timeline of our study were reported as significant compared to available mutant samples. Analyzing the details of replacing amino acids in the most frequent E87D mutation reveals the role of this alteration in increasing molecule flexibility and destabilizing the structure of the protein.

bioinformatics↗

SARS2Mutant: SARS-CoV-2 Amino-Acid Mutation Atlas Database

The coronavirus disease 19 (COVID-19) is a highly pathogenic viral infection of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in the global pandemic of 2020.A lack of therapeutic and preventive approaches including drugs and vaccines, has quickly posed significant threats to world health. A comprehensive understanding of the evolution and natural selection of SARS-CoV-2 against the host interaction and symptoms at the phenotype level could impact the candidates strategies for the fight against this virus. SARS-CoV-2 Mutation (SARS2Mutant, http://sars2mutant.com/) is a database thatprovides comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete protein sequences. The structure of this database is designed to allow the users to search for the three different strategies among amino acid substitution mutations based on gene name, geographical zone or comparative analysis. Based on each strategy, five data types are available to the user: mutated sample frequencies, heat map of the mutated amino acid positions, timeline trend for mutation survivals and natural selections, and charts of changed amino acids and their frequencies. Due to the increase of virus protein sequence samples published daily showing the latest trends of current results, all sequences in the database are reanalyzed and updated monthly. The SARS-2Mutant database providescurrent analysis and updated data of mutation patterns and conserved regions, helpful in developing and designing targeted vaccines, primers and drug discoveries.

bioinformatics↗