IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0183057.html
   My bibliography  Save this article

Data-driven coarse graining of large biomolecular structures

Author

Listed:
  • Yi-Ling Chen
  • Michael Habeck

Abstract

Advances in experimental and computational techniques allow us to study the structure and dynamics of large biomolecular assemblies at increasingly higher resolution. However, with increasing structural detail it can be challenging to unravel the mechanism underlying the function of molecular machines. One reason is that atomistic simulations become computationally prohibitive. Moreover it is difficult to rationalize the functional mechanism of systems composed of tens of thousands to millions of atoms by following each atom’s movements. Coarse graining (CG) allows us to understand biological structures from a hierarchical perspective and to gradually zoom into the adequate level of structural detail. This article introduces a Bayesian approach for coarse graining biomolecular structures. We develop a probabilistic model that aims to represent the shape of an experimental structure as a cloud of bead particles. The particles interact via a pairwise potential whose parameters are estimated along with the bead positions and the CG mapping between atoms and beads. Our model can also be applied to density maps obtained by cryo-electron microscopy. We illustrate our approach on various test systems.

Suggested Citation

  • Yi-Ling Chen & Michael Habeck, 2017. "Data-driven coarse graining of large biomolecular structures," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-17, August.
  • Handle: RePEc:plo:pone00:0183057
    DOI: 10.1371/journal.pone.0183057
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0183057
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0183057&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0183057?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. Katherine Henzler-Wildman & Dorothee Kern, 2007. "Dynamic personalities of proteins," Nature, Nature, vol. 450(7172), pages 964-972, December.
    Full references (including those not matched with items on IDEAS)

    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. César Augusto F de Oliveira & Barry J Grant & Michelle Zhou & J Andrew McCammon, 2011. "Large-Scale Conformational Changes of Trypanosoma cruzi Proline Racemase Predicted by Accelerated Molecular Dynamics Simulation," PLOS Computational Biology, Public Library of Science, vol. 7(10), pages 1-7, October.
    2. Sean L Seyler & Avishek Kumar & M F Thorpe & Oliver Beckstein, 2015. "Path Similarity Analysis: A Method for Quantifying Macromolecular Pathways," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-37, October.
    3. Jonathan Schubert & Andrea Schulze & Chrisostomos Prodromou & Hannes Neuweiler, 2021. "Two-colour single-molecule photoinduced electron transfer fluorescence imaging microscopy of chaperone dynamics," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    4. Alistair Bailey & Andy van Hateren & Tim Elliott & Jörn M Werner, 2014. "Two Polymorphisms Facilitate Differences in Plasticity between Two Chicken Major Histocompatibility Complex Class I Proteins," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    5. Feiyu Zhao & Tao Zhang & Xiaodi Sun & Xiyun Zhang & Letong Chen & Hejun Wang & Jinze Li & Peng Fan & Liangxue Lai & Tingting Sui & Zhanjun Li, 2023. "A strategy for Cas13 miniaturization based on the structure and AlphaFold," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. Tobias Linder & Bert L de Groot & Anna Stary-Weinzinger, 2013. "Probing the Energy Landscape of Activation Gating of the Bacterial Potassium Channel KcsA," PLOS Computational Biology, Public Library of Science, vol. 9(5), pages 1-9, May.
    7. Markus Götz & Anders Barth & Søren S.-R. Bohr & Richard Börner & Jixin Chen & Thorben Cordes & Dorothy A. Erie & Christian Gebhardt & Mélodie C. A. S. Hadzic & George L. Hamilton & Nikos S. Hatzakis &, 2022. "A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    8. Jian-Hua Wang & Yu-Liang Tang & Zhou Gong & Rohit Jain & Fan Xiao & Yu Zhou & Dan Tan & Qiang Li & Niu Huang & Shu-Qun Liu & Keqiong Ye & Chun Tang & Meng-Qiu Dong & Xiaoguang Lei, 2022. "Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    9. Eugene Klyshko & Justin Sung-Ho Kim & Lauren McGough & Victoria Valeeva & Ethan Lee & Rama Ranganathan & Sarah Rauscher, 2024. "Functional protein dynamics in a crystal," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    10. Antony D. St-Jacques & Joshua M. Rodriguez & Matthew G. Eason & Scott M. Foster & Safwat T. Khan & Adam M. Damry & Natalie K. Goto & Michael C. Thompson & Roberto A. Chica, 2023. "Computational remodeling of an enzyme conformational landscape for altered substrate selectivity," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    11. Karain, Wael I., 2019. "Investigating large-amplitude protein loop motions as extreme events using recurrence interval analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 1-10.
    12. Kalyan S. Chakrabarti & Simon Olsson & Supriya Pratihar & Karin Giller & Kerstin Overkamp & Ko On Lee & Vytautas Gapsys & Kyoung-Seok Ryu & Bert L. Groot & Frank Noé & Stefan Becker & Donghan Lee & Th, 2022. "A litmus test for classifying recognition mechanisms of transiently binding proteins," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    13. Maciej Majewski & Adrià Pérez & Philipp Thölke & Stefan Doerr & Nicholas E. Charron & Toni Giorgino & Brooke E. Husic & Cecilia Clementi & Frank Noé & Gianni Fabritiis, 2023. "Machine learning coarse-grained potentials of protein thermodynamics," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    14. Jochen S Hub & Bert L de Groot, 2009. "Detection of Functional Modes in Protein Dynamics," PLOS Computational Biology, Public Library of Science, vol. 5(8), pages 1-13, August.
    15. Bryant Gipson & Mark Moll & Lydia E Kavraki, 2013. "SIMS: A Hybrid Method for Rapid Conformational Analysis," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-12, July.
    16. Oliver F. Harder & Sarah V. Barrass & Marcel Drabbels & Ulrich J. Lorenz, 2023. "Fast viral dynamics revealed by microsecond time-resolved cryo-EM," Nature Communications, Nature, vol. 14(1), pages 1-6, December.
    17. Dong Long & Rafael Brüschweiler, 2011. "In Silico Elucidation of the Recognition Dynamics of Ubiquitin," PLOS Computational Biology, Public Library of Science, vol. 7(4), pages 1-9, April.
    18. Wojciech Potrzebowski & Jill Trewhella & Ingemar Andre, 2018. "Bayesian inference of protein conformational ensembles from limited structural data," PLOS Computational Biology, Public Library of Science, vol. 14(12), pages 1-27, December.

    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:pone00:0183057. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.