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      Characterisation of B.1.1.7 and Pangolin coronavirus spike provides insights on the evolutionary trajectory of SARS-CoV-2.

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          Abstract

          The recent emergence of SARS-CoV-2 variants with increased transmission, pathogenesis and immune resistance has jeopardised the global response to the COVID-19 pandemic. Determining the fundamental biology of viral variants and understanding their evolutionary trajectories will guide current mitigation measures, future genetic surveillance and vaccination strategies. Here we examine virus entry by the B.1.1.7 lineage, commonly referred to as the UK/Kent variant. Pseudovirus infection of model cell lines demonstrate that B.1.1.7 entry is enhanced relative to the Wuhan-Hu-1 reference strain, particularly under low expression of receptor ACE2. Moreover, the entry characteristics of B.1.1.7 were distinct from that of its predecessor strain containing the D614G mutation. These data suggest evolutionary tuning of spike protein function. Additionally, we found that amino acid deletions within the N-terminal domain (NTD) of spike were important for efficient entry by B.1.1.7. The NTD is a hotspot of diversity across sarbecoviruses, therefore, we further investigated this region by examining the entry of closely related CoVs. Surprisingly, Pangolin CoV spike entry was 50–100 fold enhanced relative to SARS-CoV-2; suggesting there may be evolutionary pathways by which SARSCoV-2 may further optimise entry. Swapping the NTD between Pangolin CoV and SARS-CoV-2 demonstrates that changes in this region alone have the capacity to enhance virus entry. Thus, the NTD plays a hitherto unrecognised role in modulating spike activity, warranting further investigation and surveillance of NTD mutations.

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          Most cited references 65

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          SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

          Summary The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.
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            UCSF Chimera--a visualization system for exploratory research and analysis.

            The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
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              MUSCLE: multiple sequence alignment with high accuracy and high throughput.

               Robert Edgar (2004)
              We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                22 March 2021
                Affiliations
                [1 ]Division of Infection and Immunity, University College London, UK
                Author notes
                [a]

                These authors contributed equally to this work

                AUTHOR CONTRIBUTIONS

                Conceptualisation, J.G.; Methodology, J.G., M.J.M, C.F; Investigation, S.J.D, M.J.M, L.G.T, A-K.R, C.F, M.G, L.M, M.D.K, M.P; Resources, L.E.M; Writing, J.G. Funding Acquisition, J.G. L.E.M, C.J, G.J.T, M.B.R; Supervision J.G. L.E.M, C.J, G.J.T, M.B.R

                Article
                10.1101/2021.03.22.436468
                8010729
                33791702

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.

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