IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0283364.html
   My bibliography  Save this article

Molecular dynamics of the ERRγ ligand-binding domain bound with agonist and inverse agonist

Author

Listed:
  • Santanu Sasidharan
  • Kamalakannan Radhakrishnan
  • Jun-Yeong Lee
  • Prakash Saudagar
  • Vijayakumar Gosu
  • Donghyun Shin

Abstract

Estrogen-related receptor gamma (ERRγ), the latest member of the ERR family, does not have any known reported natural ligands. Although the crystal structures of the apo, agonist-bound, and inverse agonist-bound ligand-binding domain (LBD) of ERRγ have been solved previously, their dynamic behavior has not been studied. Hence, to explore the intrinsic dynamics of the apo and ligand-bound forms of ERRγ, we applied long-range molecular dynamics (MD) simulations to the crystal structures of the apo and ligand-bound forms of the LBD of ERRγ. Using the MD trajectories, we performed hydrogen bond and binding free energy analysis, which suggested that the agonist displayed more hydrogen bonds with ERRγ than the inverse agonist 4-OHT. However, the binding energy of 4-OHT was higher than that of the agonist GSK4716, indicating that hydrophobic interactions are crucial for the binding of the inverse agonist. From principal component analysis, we observed that the AF-2 helix conformation at the C-terminal domain was similar to the initial structures during simulations, indicating that the AF-2 helix conformation is crucial with respect to the agonist or inverse agonist for further functional activity of ERRγ. In addition, we performed residue network analysis to understand intramolecular signal transduction within the protein. The betweenness centrality suggested that few of the amino acids are important for residue signal transduction in apo and ligand-bound forms. The results from this study may assist in designing better therapeutic compounds against ERRγ associated diseases.

Suggested Citation

  • Santanu Sasidharan & Kamalakannan Radhakrishnan & Jun-Yeong Lee & Prakash Saudagar & Vijayakumar Gosu & Donghyun Shin, 2023. "Molecular dynamics of the ERRγ ligand-binding domain bound with agonist and inverse agonist," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-18, April.
  • Handle: RePEc:plo:pone00:0283364
    DOI: 10.1371/journal.pone.0283364
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0283364
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0283364&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0283364?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. H. Jeong & S. P. Mason & A.-L. Barabási & Z. N. Oltvai, 2001. "Lethality and centrality in protein networks," Nature, Nature, vol. 411(6833), pages 41-42, May.
    2. Andrzej M. Brzozowski & Ashley C. W. Pike & Zbigniew Dauter & Roderick E. Hubbard & Tomas Bonn & Owe Engström & Lars Öhman & Geoffrey L. Greene & Jan-Åke Gustafsson & Mats Carlquist, 1997. "Molecular basis of agonism and antagonism in the oestrogen receptor," Nature, Nature, vol. 389(6652), pages 753-758, October.
    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. Giorgio Jansen & Tanda Qi & Vito Latora & Grigoris D. Amoutzias & Daniela Delneri & Stephen G. Oliver & Giuseppe Nicosia, 2024. "Minimisation of metabolic networks defines a new functional class of genes," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Henrieta Hlisníková & Ida Petrovičová & Branislav Kolena & Miroslava Šidlovská & Alexander Sirotkin, 2020. "Effects and Mechanisms of Phthalates’ Action on Reproductive Processes and Reproductive Health: A Literature Review," IJERPH, MDPI, vol. 17(18), pages 1-37, September.
    3. Wilhelm, Thomas & Hollunder, Jens, 2007. "Information theoretic description of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 385-396.
    4. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    5. Chung-Yen Yu & Yung-Ting Chuang & Hsi-Peng Kuan, 2017. "Understanding Faculty Collaboration and Productivity: A Case Study," Asian Social Science, Canadian Center of Science and Education, vol. 13(3), pages 1-1, March.
    6. Octavio Martínez & M Humberto Reyes-Valdés, 2018. "On an algorithmic definition for the components of the minimal cell," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-35, June.
    7. Pei Wang & Shunjie Chen & Sijia Yang, 2022. "Recent Advances on Penalized Regression Models for Biological Data," Mathematics, MDPI, vol. 10(19), pages 1-24, October.
    8. Haigang Zhang & Chengji Zhao & Hui Na, 2020. "Enhanced Biodegradation of Phthalic Acid Esters’ Derivatives by Plasticizer-Degrading Bacteria ( Burkholderia cepacia , Archaeoglobus fulgidus , Pseudomonas aeruginosa ) Using a Correction 3D-QSAR Mod," IJERPH, MDPI, vol. 17(15), pages 1-17, July.
    9. Jordán, Ferenc, 2022. "The network perspective: Vertical connections linking organizational levels," Ecological Modelling, Elsevier, vol. 473(C).
    10. P.B., Divya & Lekha, Divya Sindhu & Johnson, T.P. & Balakrishnan, Kannan, 2022. "Vulnerability of link-weighted complex networks in central attacks and fallback strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    11. Nadadoor Venkat R. & Ben-Zvi Amos & Shah Sirish L., 2011. "Inferring Gene Networks using Robust Statistical Techniques," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-30, May.
    12. repec:plo:pcbi00:1004574 is not listed on IDEAS
    13. Mustafa C. Camur & Thomas Sharkey & Chrysafis Vogiatzis, 2022. "The Star Degree Centrality Problem: A Decomposition Approach," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 93-112, January.
    14. Ramesh Ummanni & Frederike Mundt & Heike Pospisil & Simone Venz & Christian Scharf & Christine Barett & Maria Fälth & Jens Köllermann & Reinhard Walther & Thorsten Schlomm & Guido Sauter & Carsten Bok, 2011. "Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-14, February.
    15. repec:plo:pcbi00:0030118 is not listed on IDEAS
    16. Peter Langfelder & Paul S Mischel & Steve Horvath, 2013. "When Is Hub Gene Selection Better than Standard Meta-Analysis?," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-16, April.
    17. Kim, Jongkwang & Wilhelm, Thomas, 2008. "What is a complex graph?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2637-2652.
    18. Erica W. Carter & Orlene Guerra Peraza & Nian Wang, 2023. "The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    19. Takeshi Hase & Yoshihito Niimura & Tsuguchika Kaminuma & Hiroshi Tanaka, 2008. "Non-Uniform Survival Rate of Heterodimerization Links in the Evolution of the Yeast Protein-Protein Interaction Network," PLOS ONE, Public Library of Science, vol. 3(2), pages 1-7, February.
    20. Dong, Chen & Xu, Guiqiong & Meng, Lei & Yang, Pingle, 2022. "CPR-TOPSIS: A novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    21. Jiawei Luo & Yi Qi, 2015. "Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-27, June.
    22. Xia Cao & Chuanyun Li & Wei Chen & Jinqiu Li & Chaoran Lin, 2020. "Research on the invulnerability and optimization of the technical cooperation innovation network based on the patent perspective—A case study of new energy vehicles," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-19, September.

    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:pone00:0283364. 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.