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Protein structure and sequence re-analysis of 2019-nCoV genome does not indicate snakes as its intermediate host or the unique similarity between its spike protein insertions and HIV-1
Chengxin Zhang; Wei Zheng; Xiaoqiang Huang; Eric W Bell; Xiaogen Zhou; Yang Zhang.
Affiliation
  • Chengxin Zhang; Department of Computational Medicine and Bioinformatics, University of Michigan
  • Wei Zheng; Department of Computational Medicine and Bioinformatics, University of Michigan
  • Xiaoqiang Huang; Department of Computational Medicine and Bioinformatics, University of Michigan
  • Eric W Bell; Department of Computational Medicine and Bioinformatics, University of Michigan
  • Xiaogen Zhou; Department of Computational Medicine and Bioinformatics, University of Michigan
  • Yang Zhang; Department of Computational Medicine and Bioinformatics, University of Michigan
Preprint in English | bioRxiv | ID: ppbiorxiv-933135
ABSTRACT
As the infection of 2019-nCoV coronavirus is quickly developing into a global pneumonia epidemic, careful analysis of its transmission and cellular mechanisms is sorely needed. In this report, we re-analyzed the computational approaches and findings presented in two recent manuscripts by Ji et al. (https//doi.org/10.1002/jmv.25682) and by Pradhan et al. (https//doi.org/10.1101/2020.01.30.927871), which concluded that snakes are the intermediate hosts of 2019-nCoV and that the 2019-nCoV spike protein insertions shared a unique similarity to HIV-1. Results from our re-implementation of the analyses, built on larger-scale datasets using state-of-the-art bioinformatics methods and databases, do not support the conclusions proposed by these manuscripts. Based on our analyses and existing data of coronaviruses, we concluded that the intermediate hosts of 2019-nCoV are more likely to be mammals and birds than snakes, and that the "novel insertions" observed in the spike protein are naturally evolved from bat coronaviruses.
License
cc_by
Full text: Available Collection: Preprints Database: bioRxiv Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: bioRxiv Language: English Year: 2020 Document type: Preprint
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