Multiple Recombination Events and Strong Purifying Selection at the Origin of SARS-CoV-2 Spike Glycoprotein Increased Correlated Dynamic Movements
Abstract
:1. Introduction
2. Results
2.1. Multiple Recombination Events and Purifying Selection Shaped SARS-CoV-2 S Glycoprotein
2.2. Long-Range Correlated Domain Motions are Common between SARS-CoV-2 and Ancestral CoVs of Bat and Pangolin
2.3. Long-Range Correlated Motions Peculiar of SARS-CoV-2 Involve the Newly Acquired Furin-Like Cleavage Site
2.4. Long-Range Correlated Motions Conserved in the Glycosylated SARS-CoV-2
3. Discussion
4. Materials and Methods
4.1. Genetic Data
4.2. Recombination and Selection Analyses
4.3. Structure Homology Modeling
4.4. Molecular Dynamics Simulation
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Glossary
CoV | Coronavirus |
COVID-19 | Coronavirus disease 2019 |
SARS | Severe acute respiratory syndrome |
SARS-CoV-2 | Severe acute respiratory syndrome coronavirus 2 |
Bat-CoV-RaTG13 | Bat coronavirus RaTG13 |
Pangolin-CoV-2017 | Pangolin coronavirus 2017 |
Pangolin-CoV-2019 | Pangolin coronavirus 2019 |
Bat-CoV-RmYN01 | Bat coronavirus RmYN01 |
Bat-CoV-RmYN02 | Bat coronavirus RmYN02 |
Bat-SL-CoV | Bat SARS-like coronavirus |
RBD | Receptor binding domain |
NTD | N-terminal domain |
CTD1 | C-terminal domain 1 |
CTD2 | C-terminal domain 2 |
CTD3 | C-terminal domain 3 |
MD | Molecular Dynamics |
ED | Essential dynamics |
ACE2 | Angiotensin-Converting Enzyme 2 |
FP | Fusion peptide |
RMSF | Root Mean Square Fluctuations |
References
- Fehr, A.R.; Perlman, S. Coronaviruses: An overview of their replication and pathogenesis. In Coronaviruses; Maier, H.J., Bickerton, E., Britton, P., Eds.; Methods in Molecular Biology; Volume 1282, Humana Press: New York, NY, USA, 2015; pp. 1–23. [Google Scholar] [CrossRef] [Green Version]
- Su, S.; Wong, G.; Shi, W.; Liu, J.; Lai, A.C.K.; Zhou, J.; Liu, W.; Bi, Y.; Gao, G.F. Epidemiology, Genetic Recombination, and Pathogenesis of Coronaviruses. Trends Microbiol. 2016, 24, 490–502. [Google Scholar] [CrossRef] [Green Version]
- Ferron, F.; Subissi, L.; De Morais, A.T.S.; Le, N.T.T.; Sevajol, M.; Gluais, L.; Decroly, E.; Vonrhein, C.; Bricogne, G.; Canard, B.; et al. Structural and molecular basis of mismatch correction and ribavirin excision from coronavirus RNA. Proc. Natl. Acad. Sci. USA 2018, 115, E162–E171. [Google Scholar] [CrossRef] [Green Version]
- Li, X.; Wang, W.; Zhao, X.; Zai, J.; Zhao, Q.; Li, Y.; Chaillon, A. Transmission dynamics and evolutionary history of 2019-nCoV. J. Med. Virol. 2020, 92, 501–511. [Google Scholar] [CrossRef]
- Denison, M.R.; Graham, R.L.; Donaldson, E.F.; Eckerle, L.D.; Baric, R.S. Coronaviruses: An RNA proofreading machine regulates replication fidelity and diversity. RNA Biol. 2011, 8, 270–279. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Korotkova, E.; Laassri, M.; Zagorodnyaya, T.; Petrovskaya, S.; Rodionova, E.; Cherkasova, E.; Gmyl, A.; Ivanova, O.E.; Eremeeva, T.P.; Lipskaya, G.Y.; et al. Pressure for Pattern-Specific Intertypic Recombination between Sabin Polioviruses: Evolutionary Implications. Viruses 2017, 9, 353. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Xiao, Y.; Rouzine, I.M.; Bianco, S.; Acevedo, A.; Goldstein, E.F.; Farkov, M.; Brodsky, L.; Andino, R. RNA Recombination Enhances Adaptability and Is Required for Virus Spread and Virulence. Cell Host Microbe 2016, 19, 493–503. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Graham, R.L.; Baric, R.S. Recombination, reservoirs, and the modular spike: Mechanisms of coronavirus cross-species transmission. J. Virol. 2010, 84, 3134–3146. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mavian, C.; Rife, B.D.; Dollar, J.J.; Cella, E.; Ciccozzi, M.; Prosperi, M.C.F.; Lednicky, J.; Morris, J.G.; Capua, I.; Salemi, M. Emergence of recombinant Mayaro virus strains from the Amazon basin. Sci. Rep. 2017, 7, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Casal, P.E.; Chouhy, D.; Bolatti, E.M.; Pérez, G.R.; Stella, E.J.; Giri, A.A. Evidence for homologous recombination in Chikungunya Virus. Mol. Phylogenet. Evol. 2015, 85, 68–75. [Google Scholar] [CrossRef]
- Norberg, P.; Roth, A.; Bergström, T. Genetic recombination of tick-borne flaviviruses among wild-type strains. Virology 2013, 440, 105–116. [Google Scholar] [CrossRef]
- Simon-Loriere, E.; Holmes, E.C. Why do RNA viruses recombine? Nat. Rev. Microbiol. 2011, 9, 617–626. [Google Scholar] [CrossRef] [PubMed]
- Onafuwa-Nuga, A.; Telesnitsky, A. The remarkable frequency of human immunodeficiency virus type 1 genetic recombination. Microbiol. Mol. Biol. Rev. 2009, 73, 451–480. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liu, P.; Jiang, J.-Z.; Wan, X.-F.; Hua, Y.; Li, L.; Zhou, J.; Wang, X.; Hou, F.; Chen, J.; Zou, J.; et al. Are pangolins the intermediate host of the 2019 novel coronavirus (SARS-CoV-2)? PLoS Pathog. 2020, 16, e1008421. [Google Scholar] [CrossRef] [PubMed]
- Li, X.; Giorgi, E.E.; Marichannegowda, M.H.; Foley, B.; Xiao, C.; Kong, X.-P.; Chen, Y.; Gnanakaran, S.; Korber, B.; Gao, F. Emergence of SARS-CoV-2 through recombination and strong purifying selection. Sci. Adv. 2020, 6, eabb9153. [Google Scholar] [CrossRef] [PubMed]
- Zhou, H.; Chen, X.; Hu, T.; Li, J.; Song, H.; Liu, Y.; Wang, P.; Liu, D.; Yang, J.; Holmes, E.C.; et al. A Novel Bat Coronavirus Closely Related to SARS-CoV-2 Contains Natural Insertions at the S1/S2 Cleavage Site of the Spike Protein. Curr. Biol. 2020, 30, 2196–2203.e3. [Google Scholar] [CrossRef]
- Tortorici, M.A.; Veesler, D. Structural insights into coronavirus entry. In Advances in Virus Research; Rey, F.A., Ed.; Academic Press: Cambridge, MA, USA, 2019; Chapter 4; Volume 105, pp. 93–116. [Google Scholar]
- Kosakovsky Pond, S.L.; Posada, D.; Gravenor, M.B.; Woelk, C.H.; Frost, S.D. GARD: A genetic algorithm for recombination detection. Bioinformatics 2006, 22, 3096–3098. [Google Scholar] [CrossRef] [Green Version]
- Kosakovsky Pond, S.L.; Posada, D.; Gravenor, M.B.; Woelk, C.H.; Frost, S.D.W. Automated phylogenetic detection of recombination using a genetic algorithm. Mol. Biol. Evol. 2006, 23, 1891–1901. [Google Scholar] [CrossRef]
- Murrell, B.; Weaver, S.; Smith, M.D.; Wertheim, J.O.; Murrell, S.; Aylward, A.; Eren, K.; Pollner, T.; Martin, D.P.; Smith, D.M.; et al. Gene-wide identification of episodic selection. Mol. Biol. Evol. 2015, 32, 1365–1371. [Google Scholar] [CrossRef] [Green Version]
- Kosakovsky Pond, S.L.; Frost, S.D.W. Not so different after all: A comparison of methods for detecting amino acid sites under selection. Mol. Biol. Evol. 2005, 22, 1208–1222. [Google Scholar] [CrossRef] [Green Version]
- Murrell, B.; Wertheim, J.O.; Moola, S.; Weighill, T.; Scheffler, K.; Kosakovsky Pond, S.L. Detecting individual sites subject to episodic diversifying selection. PLoS Genet. 2012, 8, e1002764. [Google Scholar] [CrossRef] [Green Version]
- Smith, M.D.; Wertheim, J.O.; Weaver, S.; Murrell, B.; Scheffler, K.; Kosakovsky Pond, S.L. Less is more: An adaptive branch-site random effects model for efficient detection of episodic diversifying selection. Mol. Biol. Evol. 2015, 32, 1342–1353. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pond, S.L.; Frost, S.D.W.; Muse, S.V. HyPhy: Hypothesis testing using phylogenies. Bioinformatics 2005, 21, 676–679. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lindorff-Larsen, K.; Piana, S.; Palmo, K.; Maragakis, P.; Klepeis, J.L.; Dror, R.O.; Shaw, D.E. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins 2010, 78, 1950–1958. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Amadei, A.; Linssen, A.B.; Berendsen, H.J. Essential dynamics of proteins. Proteins 1993, 17, 412–425. [Google Scholar] [CrossRef] [PubMed]
- Grottesi, A.; Bešker, N.; Emerson, A.; Manelfi, C.; Beccari, A.R.; Frigerio, F.; Lindahl, E.; Cerchia, C.; Talarico, C. Computational Studies of SARS-CoV-2 3CLpro: Insights from MD Simulations. Int. J. Mol. Sci. 2020, 21, 5346. [Google Scholar] [CrossRef] [PubMed]
- He, J.; Tao, H.; Yan, Y.; Huang, S.-Y.; Xiao, Y. Molecular Mechanism of Evolution and Human Infection with SARS-CoV-2. Viruses 2020, 12, 428. [Google Scholar] [CrossRef] [Green Version]
- Wang, Q.; Zhang, Y.; Wu, L.; Niu, S.; Song, C.; Zhang, Z.; Lu, G.; Qiao, C.; Hu, Y.; Yuen, K.-Y.; et al. Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2. Cell 2020, 181, 894–904.e9. [Google Scholar] [CrossRef]
- Lan, J.; Ge, J.; Yu, J.; Shan, S.; Zhou, H.; Fan, S.; Zhang, Q.; Shi, X.; Wang, Q.; Zhang, L.; et al. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature 2020, 581, 215–220. [Google Scholar] [CrossRef] [Green Version]
- Bosch, B.J.; van der Zee, R.; de Haan, C.A.; Rottier, P.J. The coronavirus spike protein is a class I virus fusion protein: Structural and functional characterization of the fusion core complex. J. Virol. 2003, 77, 8801–8811. [Google Scholar] [CrossRef] [Green Version]
- Wrapp, D.; Wang, N.; Corbett, K.S.; Goldsmith, J.A.; Hsieh, C.-L.; Abiona, O.; Graham, B.S.; McLellan, J.S. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 2020, 367, 1260–1263. [Google Scholar] [CrossRef] [Green Version]
- Song, W.; Gui, M.; Wang, X.; Xiang, Y. Cryo-EM structure of the SARS coronavirus spike glycoprotein in complex with its host cell receptor ACE2. PLoS Pathog. 2018, 14, e1007236. [Google Scholar] [CrossRef] [PubMed]
- Belouzard, S.; Chu, V.C.; Whittaker, G.R. Activation of the SARS coronavirus spike protein via sequential proteolytic cleavage at two distinct sites. Proc. Natl. Acad. Sci. USA 2009, 106, 5871–5876. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gallagher, T.M.; Buchmeier, M.J. Coronavirus spike proteins in viral entry and pathogenesis. Virology 2001, 279, 371–374. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Simmons, G.; Zmora, P.; Gierer, S.; Heurich, A.; Pöhlmann, S. Proteolytic activation of the SARS-coronavirus spike protein: Cutting enzymes at the cutting edge of antiviral research. Antivir. Res. 2013, 100, 605–614. [Google Scholar] [CrossRef] [PubMed]
- Boni, M.F.; Lemey, P.; Jiang, X.; Lam, T.T.-Y.; Perry, B.W.; Castoe, T.A.; Rambaut, A.; Robertson, D.L. Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nat. Microbiol. 2020, 5, 1408–1417. [Google Scholar] [CrossRef] [PubMed]
- Tagliamonte, M.S.; Abid, N.; Ostrov, D.A.; Chillemi, G.; Pond, S.L.K.; Salemi, M.; Mavian, C. Recombination and purifying selection preserves covariant movements of mosaic SARS-CoV-2 protein S. bioRxiv 2020. [Google Scholar] [CrossRef]
- Posada, D.; Crandall, K.A. The effect of recombination on the accuracy of phylogeny estimation. J. Mol. Evol. 2002, 54, 396–402. [Google Scholar] [CrossRef]
- Schierup, M.H.; Hein, J. Consequences of recombination on traditional phylogenetic analysis. Genetics 2000, 156, 879–891. [Google Scholar]
- Shriner, D.; Nickle, D.C.; Jensen, M.A.; Mullins, J.I. Potential impact of recombination on sitewise approaches for detecting positive natural selection. Genet. Res. 2003, 81, 115–121. [Google Scholar] [CrossRef] [Green Version]
- Tsetsarkin, K.A.; Weaver, S.C. Sequential adaptive mutations enhance efficient vector switching by Chikungunya virus and its epidemic emergence. PLoS Pathog. 2011, 7, e1002412. [Google Scholar] [CrossRef] [Green Version]
- Tsetsarkin, K.A.; Chen, R.; Leal, G.; Forrester, N.; Higgs, S.; Huang, J.; Weaver, S.C. Chikungunya virus emergence is constrained in Asia by lineage-specific adaptive landscapes. Proc. Natl. Acad. Sci. USA 2011, 108, 7872–7877. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Andersen, K.G.; Rambaut, A.; Lipkin, W.I.; Holmes, E.C.; Garry, R.F. The proximal origin of SARS-CoV-2. Nat. Med. 2020, 26, 450–452. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Coutard, B.; Valle, C.; de Lamballerie, X.; Canard, B.; Seidah, N.G.; Decroly, E. The spike glycoprotein of the new coronavirus 2019-nCoV contains a furin-like cleavage site absent in CoV of the same clade. Antivir. Res. 2020, 176, 104742. [Google Scholar] [CrossRef] [PubMed]
- Zhao, P.; Praissman, J.L.; Grant, O.C.; Cai, Y.; Xiao, T.; Rosenbalm, K.E.; Aoki, K.; Kellman, B.P.; Bridger, R.; Barouch, D.H.; et al. Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor. Cell Host Microbe 2020, 28, 586–601.e6. [Google Scholar] [CrossRef] [PubMed]
- Casalino, L.; Gaieb, Z.; Goldsmith, J.A.; Hjorth, C.K.; Dommer, A.C.; Harbison, A.M.; Fogarty, C.A.; Barros, E.P.; Taylor, B.C.; McLellan, J.S.; et al. Beyond Shielding: The Roles of Glycans in the SARS-CoV-2 Spike Protein. ACS Cent. Sci. 2020, 6, 1722–1734. [Google Scholar] [CrossRef] [PubMed]
- Yan, R.; Zhang, Y.; Li, Y.; Xia, L.; Guo, Y.; Zhou, Q. Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2. Science 2020, 367, 1444–1448. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lai, A.L.; Millet, J.K.; Daniel, S.; Freed, J.H.; Whittaker, G.R. The SARS-CoV Fusion Peptide Forms an Extended Bipartite Fusion Platform that Perturbs Membrane Order in a Calcium-Dependent Manner. J. Mol. Biol. 2017, 429, 3875–3892. [Google Scholar] [CrossRef]
- Madu, I.G.; Roth, S.L.; Belouzard, S.; Whittaker, G.R. Characterization of a highly conserved domain within the severe acute respiratory syndrome coronavirus spike protein S2 domain with characteristics of a viral fusion peptide. J. Virol. 2009, 83, 7411–7421. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Millet, J.K.; Whittaker, G.R. Host cell entry of Middle East respiratory syndrome coronavirus after two-step, furin-mediated activation of the spike protein. Proc. Natl. Acad. Sci. USA 2014, 111, 15214–15219. [Google Scholar] [CrossRef] [Green Version]
- Katoh, K.; Standley, D.M. A simple method to control over-alignment in the MAFFT multiple sequence alignment program. Bioinformatics 2016, 32, 1933–1942. [Google Scholar] [CrossRef]
- Waterhouse, A.; Bertoni, M.; Bienert, S.; Studer, G.; Tauriello, G.; Gumienny, R.; Heer, F.T.; de Beer, T.A.P.; Rempfer, C.; Bordoli, L.; et al. SWISS-MODEL: Homology modelling of protein structures and complexes. Nucleic Acids Res. 2018, 46, W296–W303. [Google Scholar] [CrossRef] [Green Version]
- Madeira, F.; Park, Y.M.; Lee, J.; Buso, N.; Gur, T.; Madhusoodanan, N.; Basutkar, P.; Tivey, A.R.N.; Potter, S.C.; Finn, R.D.; et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019, 47, W636–W641. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Eswar, N.; Webb, B.; Marti-Renom, M.A.; Madhusudhan, M.S.; Eramian, D.; Shen, M.-Y.; Pieper, U.; Sali, A. Comparative protein structure modeling using Modeller. Curr. Protoc. Bioinform. 2006, 15, 5.6.1–5.6.30. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Webb, B.; Sali, A. Protein structure modeling with MODELLER. Methods Mol. Biol. 2014, 1137, 1–15. [Google Scholar] [CrossRef] [PubMed]
- Shen, M.-Y.; Sali, A. Statistical potential for assessment and prediction of protein structures. Protein Sci. 2006, 15, 2507–2524. [Google Scholar] [CrossRef] [Green Version]
- Sippl, M.J. Recognition of errors in three-dimensional structures of proteins. Proteins 1993, 17, 355–362. [Google Scholar] [CrossRef]
- Wiederstein, M.; Sippl, M.J. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007, 35, W407–W410. [Google Scholar] [CrossRef] [Green Version]
- Benkert, P.; Biasini, M.; Schwede, T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 2011, 27, 343–350. [Google Scholar] [CrossRef]
- Benkert, P.; Künzli, M.; Schwede, T. QMEAN server for protein model quality estimation. Nucleic Acids Res. 2009, 37, W510–W514. [Google Scholar] [CrossRef] [Green Version]
- Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera—A visualization system for exploratory research and analysis. J. Comput. Chem. 2004, 25, 1605–1612. [Google Scholar] [CrossRef] [Green Version]
- Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual molecular dynamics. J. Mol. Graph. 1996, 14, 33–38. [Google Scholar] [CrossRef]
- Korber, B.; Myers, G. Signature pattern analysis: A method for assessing viral sequence relatedness. AIDS Res. Hum. Retroviruses 1992, 8, 1549–1560. [Google Scholar] [CrossRef] [PubMed]
- Watanabe, Y.; Allen, J.D.; Wrapp, D.; McLellan, J.S.; Crispin, M. Site-specific glycan analysis of the SARS-CoV-2 spike. Science 2020, 369, 330–333. [Google Scholar] [CrossRef]
- Shajahan, A.; Supekar, N.T.; Gleinich, A.S.; Azadi, P. Deducing the N- and O- glycosylation profile of the spike protein of novel coronavirus SARS-CoV-2. Glycobiology 2020, 30, 981–988. [Google Scholar] [CrossRef]
- Maier, J.A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K.E.; Simmerling, C. ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J. Chem. Theory Comput. 2015, 11, 3696–3713. [Google Scholar] [CrossRef] [Green Version]
- Kirschner, K.N.; Yongye, A.B.; Tschampel, S.M.; González-Outeiriño, J.; Daniels, C.R.; Foley, B.L.; Woods, R.J. GLYCAM06: A generalizable biomolecular force field. Carbohydrates. J. Comput. Chem. 2008, 29, 622–655. [Google Scholar] [CrossRef] [Green Version]
- Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926–935. [Google Scholar] [CrossRef]
- Abraham, M.J.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J.C.; Hess, B.; Lindahl, E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015, 1–2, 19–25. [Google Scholar] [CrossRef] [Green Version]
- Bussi, G.D.; Donadio, D.; Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 2007, 126, 014101. [Google Scholar] [CrossRef] [Green Version]
- Darden, T.; York, D.; Pedersen, L. Particle mesh Ewald: An N log(N) method for Ewald sums in large systems. J. Chem. Phys. 1993, 98, 10089–10092. [Google Scholar] [CrossRef] [Green Version]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Tagliamonte, M.S.; Abid, N.; Borocci, S.; Sangiovanni, E.; Ostrov, D.A.; Kosakovsky Pond, S.L.; Salemi, M.; Chillemi, G.; Mavian, C. Multiple Recombination Events and Strong Purifying Selection at the Origin of SARS-CoV-2 Spike Glycoprotein Increased Correlated Dynamic Movements. Int. J. Mol. Sci. 2021, 22, 80. https://doi.org/10.3390/ijms22010080
Tagliamonte MS, Abid N, Borocci S, Sangiovanni E, Ostrov DA, Kosakovsky Pond SL, Salemi M, Chillemi G, Mavian C. Multiple Recombination Events and Strong Purifying Selection at the Origin of SARS-CoV-2 Spike Glycoprotein Increased Correlated Dynamic Movements. International Journal of Molecular Sciences. 2021; 22(1):80. https://doi.org/10.3390/ijms22010080
Chicago/Turabian StyleTagliamonte, Massimiliano S., Nabil Abid, Stefano Borocci, Elisa Sangiovanni, David A. Ostrov, Sergei L. Kosakovsky Pond, Marco Salemi, Giovanni Chillemi, and Carla Mavian. 2021. "Multiple Recombination Events and Strong Purifying Selection at the Origin of SARS-CoV-2 Spike Glycoprotein Increased Correlated Dynamic Movements" International Journal of Molecular Sciences 22, no. 1: 80. https://doi.org/10.3390/ijms22010080