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Lon, J. R.

Publications and source records attributed to Lon, J. R..

4 recordsLinked to original sources

Molecular dynamics simulation study of effects of key mutations in SARS-CoV-2 on protein structures

SARS-CoV-2 has been spreading rapidly since 2019 and has produced large-scale mutations in the genomes. The mutation in genes may lead to changes in protein structure, which would have a great impact on the epidemiological characteristics. In this study, we selected the key mutations of SARS-CoV-2 from a real-time monitoring tool, including D614G, A222V, N501Y, T716I, S982A, D1118H of spike (S) protein, and performed molecular dynamics (MD) simulations on single-site mutant D614G, double-site mutant D614G&A222V and penta-site mutant N501Y&D614G&T716I&S982A&D1118H to investigate their effects on protein structure and stability using molecular dynamics (MD) simulations. The results suggested that D614G improved the stability of S protein, while D614G&A222V and N501Y&D614G&T716I&S982A&D1118H showed an increased solvent accessible surface area and they might enhance the ability of protein to react with the outside environment. Our findings could complement the mechanistic link between genotype--phenotype--epidemiological characteristics in the study of SARS-CoV-2. We also found no significant difference between the antigenicity of S protein and the mutants through Ellipro, which may reference for vaccine development and application.

bioinformatics

Real-time monitoring epidemic trends and key mutations in SARS-CoV-2 evolution by an automated tool

With the global epidemic of SARS-CoV-2, it is important to monitor the variation, haplotype subgroup epidemic trends and key mutations of SARS-CoV-2 over time effectively, which is of great significance to the development of new vaccines, the update of therapeutic drugs, and the improvement of detection reagents. The AutoVEM tool developed in the present study could complete all mutations detections, haplotypes classification, haplotype subgroup epidemic trends and key mutations analysis for 131,576 SARS-CoV-2 genome sequences in 18 hours on a 1 core CPU and 2G internal storage computer. Through haplotype subgroup epidemic trends analysis of 131,576 genome sequences, the great significance of the previous 4 specific sites (C241T, C3037T, C14408T and A23403G) was further revealed, and 6 new mutation sites of highly linked (T445C, C6286T, C22227T, G25563T, C26801G and G29645T) were discovered for the first time that might be related to the infectivity, pathogenicity or host adaptability of SARS-CoV-2. In brief, we proposed an integrative method and developed an efficient automated tool to monitor haplotype subgroup epidemic trends and screen out the key mutations in the evolution of SARS-CoV-2 over time for the first time, and all data could be updated quickly to track the prevalence of previous key mutations and new key mutations because of high efficiency of the tool. In addition, the idea of combinatorial analysis in the present study can also provide a reference for the mutation monitoring of other viruses.

genomics

Evolution and molecular characteristics of SARS-CoV-2 genome

ObjectivesTo reveal epidemic trend and possible origins of SARS-CoV-2 by exploring its evolution and molecular characteristics based on a large number of genomes since it has infected millions of people and spread quickly all over the world. MethodsVarious evolution analysis methods were employed. ResultsThe estimated Ka/Ks ratio of SARS-CoV-2 is 1.008 or 1.094 based on 622 or 3624 SARS-CoV-2 genomes, and the time to the most recent common ancestor (tMRCA) was inferred in late September 2019. Further 9 key specific sites of highly linkage and four major haplotypes H1, H2, H3 and H4 were found. The Ka/Ks, detected population size and development trends of each major haplotype showed H3 and H4 subgroups were going through a purify evolution and almost disappeared after detection, indicating H3 and H4 might have existed for a long time, while H1 and H2 subgroups were going through a near neutral or neutral evolution and globally increased with time. Notably the frequency of H1 was generally high in Europe and correlated to death rate (r>0.37). ConclusionsIn this study, the evolution and molecular characteristics of more than 16000 genomic sequences provided a new perspective for revealing epidemiology of SARS-CoV-2.

bioinformatics

Prediction and Evolution of B Cell Epitopes of Surface Protein in SARS-CoV-2

The discovery of epitopes is helpful to the development of SARS-CoV-2 vaccine. The sequences of the surface protein of SARS-CoV-2 and its proximal sequences were obtained by BLAST, the sequences of the whole genome of SARS-CoV-2 were obtained from the GenBank. Based on the NCBI Reference Sequence: NC_045512.2, the conformational and linear B cell epitopes of the surface protein were predicted separately by various prediction methods. Furthermore, the conservation of the epitopes, the adaptability and other evolutionary characteristics were also analyzed. 7 epitopes were predicted, including 5 linear epitopes and 2 conformational epitopes, one of the linear and one of the conformational were coincide. The epitope D mutated easily, but the other epitopes were very conservative and the epitope C was the most conservative. It is worth mentioning that all of the 6 dominated epitopes were absolutely conservative in nearly 1000 SARS-CoV-2 genomes, and they deserved further study. The findings would facilitate the vaccine development, had the potential to be directly applied on the treatment in this disease, but also have the potential to prevent the possible threats caused by other types of coronavirus.

bioinformatics