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Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase

Author

Listed:
  • Federica Maschietto

    (Yale University)

  • Uriel N. Morzan

    (International Center for Theoretical Physics)

  • Florentina Tofoleanu

    (Yale University
    National Institutes of Health
    Treeline Biosciences)

  • Aria Gheeraert

    (ENSL, CNRS, Laboratoire de Chimie UMR 5182
    Università di Bologna)

  • Apala Chaudhuri

    (Yale University)

  • Gregory W. Kyro

    (Yale University)

  • Peter Nekrasov

    (Yale University)

  • Bernard Brooks

    (National Institutes of Health)

  • J. Patrick Loria

    (Yale University
    Yale University)

  • Ivan Rivalta

    (ENSL, CNRS, Laboratoire de Chimie UMR 5182
    Università di Bologna)

  • Victor S. Batista

    (Yale University)

Abstract

Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.

Suggested Citation

  • Federica Maschietto & Uriel N. Morzan & Florentina Tofoleanu & Aria Gheeraert & Apala Chaudhuri & Gregory W. Kyro & Peter Nekrasov & Bernard Brooks & J. Patrick Loria & Ivan Rivalta & Victor S. Batist, 2023. "Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37956-1
    DOI: 10.1038/s41467-023-37956-1
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    References listed on IDEAS

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    1. Harry G. Saavedra & James O. Wrabl & Jeremy A. Anderson & Jing Li & Vincent J. Hilser, 2018. "Dynamic allostery can drive cold adaptation in enzymes," Nature, Nature, vol. 558(7709), pages 324-328, June.
    2. João P. Pisco & Cesira de Chiara & Kamila J. Pacholarz & Acely Garza-Garcia & Roksana W. Ogrodowicz & Philip A. Walker & Perdita E. Barran & Stephen J. Smerdon & Luiz Pedro S. de Carvalho, 2017. "Uncoupling conformational states from activity in an allosteric enzyme," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    3. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    4. Shaoyong Lu & Xinheng He & Zhao Yang & Zongtao Chai & Shuhua Zhou & Junyan Wang & Ashfaq Ur Rehman & Duan Ni & Jun Pu & Jinpeng Sun & Jian Zhang, 2021. "Activation pathway of a G protein-coupled receptor uncovers conformational intermediates as targets for allosteric drug design," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    5. Jian Wang & Abha Jain & Leanna R. McDonald & Craig Gambogi & Andrew L. Lee & Nikolay V. Dokholyan, 2020. "Mapping allosteric communications within individual proteins," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    6. Shiou-Ru Tzeng & Charalampos G. Kalodimos, 2009. "Dynamic activation of an allosteric regulatory protein," Nature, Nature, vol. 462(7271), pages 368-372, November.
    7. Jan Philip Wurm & Sihyun Sung & Andrea Christa Kneuttinger & Enrico Hupfeld & Reinhard Sterner & Matthias Wilmanns & Remco Sprangers, 2021. "Molecular basis for the allosteric activation mechanism of the heterodimeric imidazole glycerol phosphate synthase complex," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    8. Jolliffe, Ian, 2022. "A 50-year personal journey through time with principal component analysis," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    9. Zenita Adhireksan & Giulia Palermo & Tina Riedel & Zhujun Ma & Reyhan Muhammad & Ursula Rothlisberger & Paul J. Dyson & Curt A. Davey, 2017. "Allosteric cross-talk in chromatin can mediate drug-drug synergy," Nature Communications, Nature, vol. 8(1), pages 1-11, April.
    10. Hesam N. Motlagh & James O. Wrabl & Jing Li & Vincent J. Hilser, 2014. "The ensemble nature of allostery," Nature, Nature, vol. 508(7496), pages 331-339, April.
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