IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1002659.html
   My bibliography  Save this article

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

Author

Listed:
  • Tobias Sikosek
  • Erich Bornberg-Bauer
  • Hue Sun Chan

Abstract

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. Author Summary: Proteins are essential molecules for performing a majority of functions in all biological systems. These functions often depend on the three-dimensional structures of proteins. Here, we investigate a fundamental question in molecular evolution: how can proteins acquire new advantageous structures via mutations while not sacrificing their existing structures that are still needed? Some authors have suggested that the same protein may adopt two or more alternative structures, switch between them and thus perform different functions with each of the alternative structures. Intuitively, such a protein could provide an evolutionary compromise between conflicting demands for existing and new protein structures. Yet no theoretical study has systematically tackled the biophysical basis of such compromises during evolutionary processes. Here we devise a model of evolution that specifically recognizes protein molecules that can exist in several different stable structures. Our model demonstrates that proteins can indeed utilize multiple structures to satisfy conflicting evolutionary requirements. In light of these results, we identify data from known protein structures that are consistent with our predictions and suggest novel directions for future investigation.

Suggested Citation

  • Tobias Sikosek & Erich Bornberg-Bauer & Hue Sun Chan, 2012. "Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts," PLOS Computational Biology, Public Library of Science, vol. 8(9), pages 1-17, September.
  • Handle: RePEc:plo:pcbi00:1002659
    DOI: 10.1371/journal.pcbi.1002659
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002659
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002659&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1002659?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Walter Fontana & Peter Schuster, 1998. "Continuity in Evolution: On the Nature of Transition," Working Papers 98-04-030, Santa Fe Institute.
    2. Jeremy A. Draghi & Todd L. Parsons & Günter P. Wagner & Joshua B. Plotkin, 2010. "Mutational robustness can facilitate adaptation," Nature, Nature, vol. 463(7279), pages 353-355, January.
    3. David L. Des Marais & Mark D. Rausher, 2008. "Escape from adaptive conflict after duplication in an anthocyanin pathway gene," Nature, Nature, vol. 454(7205), pages 762-765, August.
    4. Claus O. Wilke & Jia Lan Wang & Charles Ofria & Richard E. Lenski & Christoph Adami, 2001. "Evolution of digital organisms at high mutation rates leads to survival of the flattest," Nature, Nature, vol. 412(6844), pages 331-333, July.
    5. Eric van Nimwegen & James P. Crutchfield & Martijn Huynen, 1999. "Neutral Evolution of Mutational Robustness," Working Papers 99-03-021, Santa Fe Institute.
    6. W. Fontana & P. Schuster, 1998. "Continuity in Evolution: On the Nature of Transitions," Working Papers ir98039, International Institute for Applied Systems Analysis.
    7. Guillaume Bouvignies & Pramodh Vallurupalli & D. Flemming Hansen & Bruno E. Correia & Oliver Lange & Alaji Bah & Robert M. Vernon & Frederick W. Dahlquist & David Baker & Lewis E. Kay, 2011. "Solution structure of a minor and transiently formed state of a T4 lysozyme mutant," Nature, Nature, vol. 477(7362), pages 111-114, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tobias Sikosek & Heinrich Krobath & Hue Sun Chan, 2016. "Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-27, June.
    2. Pengfei Tian & Robert B Best, 2020. "Exploring the sequence fitness landscape of a bridge between protein folds," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-19, October.
    3. Evandro Ferrada, 2014. "The Amino Acid Alphabet and the Architecture of the Protein Sequence-Structure Map. I. Binary Alphabets," PLOS Computational Biology, Public Library of Science, vol. 10(12), pages 1-20, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miguel A Fortuna & Luis Zaman & Charles Ofria & Andreas Wagner, 2017. "The genotype-phenotype map of an evolving digital organism," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-20, February.
    2. Proulx, Stephen R., 2011. "The rate of multi-step evolution in Moran and Wright–Fisher populations," Theoretical Population Biology, Elsevier, vol. 80(3), pages 197-207.
    3. Rendel, Mark D., 2011. "Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes," Theoretical Population Biology, Elsevier, vol. 79(1), pages 12-18.
    4. Campos, Paulo R.A & Adami, Christoph & Wilke, Claus O, 2002. "Optimal adaptive performance and delocalization in NK fitness landscapes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 304(3), pages 495-506.
    5. Krishnendu Chatterjee & Andreas Pavlogiannis & Ben Adlam & Martin A Nowak, 2014. "The Time Scale of Evolutionary Innovation," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-7, September.
    6. Elizabeth Aston & Alastair Channon & Charles Day & Christopher G Knight, 2013. "Critical Mutation Rate Has an Exponential Dependence on Population Size in Haploid and Diploid Populations," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-11, December.
    7. James P. Crutchfield & Erik van Nimwegen, 1999. "The Evolutionary Unfolding of Complexity," Working Papers 99-02-015, Santa Fe Institute.
    8. Jan Cupal & Stephan Kopp & Peter F. Stadler, 1999. "RNA Space Shape Technology," Working Papers 99-03-022, Santa Fe Institute.
    9. Roger D Kouyos & Gabriel E Leventhal & Trevor Hinkley & Mojgan Haddad & Jeannette M Whitcomb & Christos J Petropoulos & Sebastian Bonhoeffer, 2012. "Exploring the Complexity of the HIV-1 Fitness Landscape," PLOS Genetics, Public Library of Science, vol. 8(3), pages 1-9, March.
    10. Evandro Ferrada, 2014. "The Amino Acid Alphabet and the Architecture of the Protein Sequence-Structure Map. I. Binary Alphabets," PLOS Computational Biology, Public Library of Science, vol. 10(12), pages 1-20, December.
    11. Bårbel M. R. Stadler & Peter F. Stadler & Peter R. Wills, 2001. "Evolution in Systems of Ligation-Based Replicators," Working Papers 01-09-052, Santa Fe Institute.
    12. Christian M. Reidys & Peter F. Stadler, 1998. "Neutrality in Fitness Landscapes," Working Papers 98-10-089, Santa Fe Institute.
    13. Sam F Greenbury & Steffen Schaper & Sebastian E Ahnert & Ard A Louis, 2016. "Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-27, March.
    14. Arturo Marín & Héctor Tejero & Juan Carlos Nuño & Francisco Montero, 2013. "The Advantage of Arriving First: Characteristic Times in Finite Size Populations of Error-Prone Replicators," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    15. Capitán, José A. & Aguirre, Jacobo & Manrubia, Susanna, 2015. "Dynamical community structure of populations evolving on genotype networks," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 99-106.
    16. Rigato, Emanuele & Fusco, Giuseppe, 2020. "A heuristic model of the effects of phenotypic robustness in adaptive evolution," Theoretical Population Biology, Elsevier, vol. 136(C), pages 22-30.
    17. Alicia Sanchez-Gorostiaga & Djordje Bajić & Melisa L Osborne & Juan F Poyatos & Alvaro Sanchez, 2019. "High-order interactions distort the functional landscape of microbial consortia," PLOS Biology, Public Library of Science, vol. 17(12), pages 1-34, December.
    18. Alexander J. Stewart & Joshua B. Plotkin, 2015. "The Evolvability of Cooperation under Local and Non-Local Mutations," Games, MDPI, vol. 6(3), pages 1-20, July.
    19. Lukas Aufinger & Johann Brenner & Friedrich C. Simmel, 2022. "Complex dynamics in a synchronized cell-free genetic clock," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    20. Zeina Shreif & Vipul Periwal, 2014. "A Network Characteristic That Correlates Environmental and Genetic Robustness," PLOS Computational Biology, Public Library of Science, vol. 10(2), pages 1-23, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1002659. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.