IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v617y2023ics0378437123002261.html
   My bibliography  Save this article

Structural controllability to unveil hidden regulation mechanisms in Unfolded Protein Response: The role of network models

Author

Listed:
  • Luchetti, Nicole
  • Loppini, Alessandro
  • Matarrese, Margherita A.G.
  • Chiodo, Letizia
  • Filippi, Simonetta

Abstract

The Unfolded Protein Response is the cell mechanism for maintaining the balance of properly folded proteins in the endoplasmic reticulum, the specialized cellular compartment. Although it is largely studied from a biological point of view, much of the literature lacks a quantitative analysis of such a central signaling pathway. In this work, we aim to fill this gap by applying structural controllability analysis of complex networks to several Unfolded Protein Response networks to identify crucial nodes in the signaling flow. In particular, we first build different network models of the Unfolded Protein Response mechanism, relying on data contained in various protein–protein interaction databases. Then, we identify the driver nodes, essential for overall network control, i.e., the key proteins on which external stimulation may be optimally delivered to control network behavior. Our structural controllability analysis results show that the driver nodes commonly identified across databases match with known endoplasmic reticulum stress sensors. This potentially confirms that the theoretically identified drivers correspond to the biological key proteins associated with fundamental cellular activities and diseases. In conclusion, we prove that structural controllability is a reliable quantitative tool to investigate biological signaling pathways, and it can be potentially applied to networks more complex and less explored than Unfolded Protein Response.

Suggested Citation

  • Luchetti, Nicole & Loppini, Alessandro & Matarrese, Margherita A.G. & Chiodo, Letizia & Filippi, Simonetta, 2023. "Structural controllability to unveil hidden regulation mechanisms in Unfolded Protein Response: The role of network models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
  • Handle: RePEc:eee:phsmap:v:617:y:2023:i:c:s0378437123002261
    DOI: 10.1016/j.physa.2023.128671
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123002261
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2023.128671?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kathryn Tunyasuvunakool & Jonas Adler & Zachary Wu & Tim Green & Michal Zielinski & Augustin Žídek & Alex Bridgland & Andrew Cowie & Clemens Meyer & Agata Laydon & Sameer Velankar & Gerard J. Kleywegt, 2021. "Highly accurate protein structure prediction for the human proteome," Nature, Nature, vol. 596(7873), pages 590-596, August.
    2. Liu, Suling & Xu, Qiong & Chen, Aimin & Wang, Pei, 2020. "Structural controllability of dynamic transcriptional regulatory networks for Saccharomyces cerevisiae," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. John Jumper & Richard Evans & Alexander Pritzel & Tim Green & Michael Figurnov & Olaf Ronneberger & Kathryn Tunyasuvunakool & Russ Bates & Augustin Žídek & Anna Potapenko & Alex Bridgland & Clemens Me, 2021. "Highly accurate protein structure prediction with AlphaFold," Nature, Nature, vol. 596(7873), pages 583-589, August.
    4. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
    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. Deyun Qiu & Jinxin V. Pei & James E. O. Rosling & Vandana Thathy & Dongdi Li & Yi Xue & John D. Tanner & Jocelyn Sietsma Penington & Yi Tong Vincent Aw & Jessica Yi Han Aw & Guoyue Xu & Abhai K. Tripa, 2022. "A G358S mutation in the Plasmodium falciparum Na+ pump PfATP4 confers clinically-relevant resistance to cipargamin," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    2. Shuo-Shuo Liu & Tian-Xia Jiang & Fan Bu & Ji-Lan Zhao & Guang-Fei Wang & Guo-Heng Yang & Jie-Yan Kong & Yun-Fan Qie & Pei Wen & Li-Bin Fan & Ning-Ning Li & Ning Gao & Xiao-Bo Qiu, 2024. "Molecular mechanisms underlying the BIRC6-mediated regulation of apoptosis and autophagy," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    3. Kristy Rochon & Brianna L. Bauer & Nathaniel A. Roethler & Yuli Buckley & Chih-Chia Su & Wei Huang & Rajesh Ramachandran & Maria S. K. Stoll & Edward W. Yu & Derek J. Taylor & Jason A. Mears, 2024. "Structural basis for regulated assembly of the mitochondrial fission GTPase Drp1," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    4. Fan Lu & Liang Zhu & Thomas Bromberger & Jun Yang & Qiannan Yang & Jianmin Liu & Edward F. Plow & Markus Moser & Jun Qin, 2022. "Mechanism of integrin activation by talin and its cooperation with kindlin," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    5. Martin F. Peter & Christian Gebhardt & Rebecca Mächtel & Gabriel G. Moya Muñoz & Janin Glaenzer & Alessandra Narducci & Gavin H. Thomas & Thorben Cordes & Gregor Hagelueken, 2022. "Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    6. Jutta Diessl & Jens Berndtsson & Filomena Broeskamp & Lukas Habernig & Verena Kohler & Carmela Vazquez-Calvo & Arpita Nandy & Carlotta Peselj & Sofia Drobysheva & Ludovic Pelosi & F.-Nora Vögtle & Fab, 2022. "Manganese-driven CoQ deficiency," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    7. Alexander Kroll & Sahasra Ranjan & Martin K. M. Engqvist & Martin J. Lercher, 2023. "A general model to predict small molecule substrates of enzymes based on machine and deep learning," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    8. Lisa-Marie Appel & Vedran Franke & Johannes Benedum & Irina Grishkovskaya & Xué Strobl & Anton Polyansky & Gregor Ammann & Sebastian Platzer & Andrea Neudolt & Anna Wunder & Lena Walch & Stefanie Kais, 2023. "The SPOC domain is a phosphoserine binding module that bridges transcription machinery with co- and post-transcriptional regulators," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    9. Maciej K. Kocylowski & Hande Aypek & Wolfgang Bildl & Martin Helmstädter & Philipp Trachte & Bernhard Dumoulin & Sina Wittösch & Lukas Kühne & Ute Aukschun & Carolin Teetzen & Oliver Kretz & Botond Ga, 2022. "A slit-diaphragm-associated protein network for dynamic control of renal filtration," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    10. Michael A. Longo & Sunetra Roy & Yue Chen & Karl-Heinz Tomaszowski & Andrew S. Arvai & Jordan T. Pepper & Rebecca A. Boisvert & Selvi Kunnimalaiyaan & Caezanne Keshvani & David Schild & Albino Bacolla, 2023. "RAD51C-XRCC3 structure and cancer patient mutations define DNA replication roles," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    11. Zachary C. Drake & Justin T. Seffernick & Steffen Lindert, 2022. "Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    12. Leonardo Betancurt-Anzola & Markel Martínez-Carranza & Marc Delarue & Kelly M. Zatopek & Andrew F. Gardner & Ludovic Sauguet, 2023. "Molecular basis for proofreading by the unique exonuclease domain of Family-D DNA polymerases," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    13. Karin Vogel & Tobias Bläske & Marie-Kristin Nagel & Christoph Globisch & Shane Maguire & Lorenz Mattes & Christian Gude & Michael Kovermann & Karin Hauser & Christine Peter & Erika Isono, 2022. "Lipid-mediated activation of plasma membrane-localized deubiquitylating enzymes modulate endosomal trafficking," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    14. Robin Anger & Laetitia Pieulle & Meriam Shahin & Odile Valette & Hugo Guenno & Artemis Kosta & Vladimir Pelicic & Rémi Fronzes, 2023. "Structure of a heteropolymeric type 4 pilus from a monoderm bacterium," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    15. Jie Li & Haonan Zhang & Dongyu Li & Ya-Jun Liu & Edward A. Bayer & Qiu Cui & Yingang Feng & Ping Zhu, 2023. "Structure of the transcription open complex of distinct σI factors," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    16. Yi C. Zeng & Meghna Sobti & Ada Quinn & Nicola J. Smith & Simon H. J. Brown & Jamie I. Vandenberg & Renae M. Ryan & Megan L. O’Mara & Alastair G. Stewart, 2023. "Structural basis of promiscuous substrate transport by Organic Cation Transporter 1," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    17. Niraj Kumar & Shivani Sharma & Prem S. Kaushal, 2024. "Cryo- EM structure of the mycobacterial 70S ribosome in complex with ribosome hibernation promotion factor RafH," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    18. Marietta S. Kaspers & Vivian Pogenberg & Christian Pett & Stefan Ernst & Felix Ecker & Philipp Ochtrop & Michael Groll & Christian Hedberg & Aymelt Itzen, 2023. "Dephosphocholination by Legionella effector Lem3 functions through remodelling of the switch II region of Rab1b," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    19. Kang Yu & Chenhui Huang & Futang Wan & Cailing Jiang & Juan Chen & Xiuping Li & Feng Wang & Jian Wu & Ming Lei & Yiqun Wu, 2023. "Structural insights into pathogenic mechanism of hypohidrotic ectodermal dysplasia caused by ectodysplasin A variants," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    20. Artur Meller & Michael Ward & Jonathan Borowsky & Meghana Kshirsagar & Jeffrey M. Lotthammer & Felipe Oviedo & Juan Lavista Ferres & Gregory R. Bowman, 2023. "Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

    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:eee:phsmap:v:617:y:2023:i:c:s0378437123002261. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.