IDEAS home Printed from https://ideas.repec.org/h/dax/ctbtls/978-93-6163-763-6p8-21.html
   My bibliography  Save this book chapter

Computational Approach for HDAC1 Predicting Protein-Ligand Interactions for Cancer through Homology Modelling, Virtual Screening and Molecular Docking

In: Convergence of Technology & Biology ─ Transforming Life Sciences

Author

Listed:
  • M. Bhargavi
  • Sri Gayathri Bhargavi
  • Esha Sripada

Abstract

Histone Deacetylase 1 (HDAC1) is vital for controlling gene expression, chromatin remodelling, and biological functions like distinction and cellular proliferation by acetylation of histone tail residues. Its abnormal expression is of high significance in inflammatory diseases, cancers and allergic diseases. Thus, considering the structure and function of HDAC1 is very crucial because it may be used as a therapeutic target for cancer, neurologicalillnesses, and other disorders. In this study, the structure of HDAC1 was predicted using homology modelling. First, based on the known crystal structures of template proteins, a high-quality 3D model of HDAC1 was generated using the concepts of homology modelling by Modeller 10.6 software. The correctness and reliability of this model were enhanced using a GalaxyWEB refine tool and for energy minimization YASARA software was put to use.The model obtained after refinement and energy minimization was put for validation on the ProSA-WEB and SAVES server where the results of z-score, ERRAT, VERIFY-3D and Ramachandran plot were obtained and analysed. The analysed model was then employed to investigate the binding interactions with ligands that may inhibit HDAC1 activity, in molecular docking studies. The steps involved were performed using Schrodinger suites Maestro 13.5 included: protein preparation using protein preparation wizard, grid generation using GLIDE and virtual screening employing molecular docking using virtual screening workflow wizard. Therefore, through this study HDAC1's structure was predicted, validated and molecular docking studies were performed on it.

Suggested Citation

  • M. Bhargavi & Sri Gayathri Bhargavi & Esha Sripada, 2025. "Computational Approach for HDAC1 Predicting Protein-Ligand Interactions for Cancer through Homology Modelling, Virtual Screening and Molecular Docking," Convergence of Technology & Biology ─ Transforming Life Sciences, in: Malathi Varma & S.Parijatham Kanchana & G.Sony (ed.),Convergence of Technology & Biology ─ Transforming Life Sciences, chapter 2, pages 8-21, Shanlax Publications.
    • Handle: RePEc:dax:ctbtls:978-93-6163-763-6:p:8-21
    as

    Download full text from publisher

    File URL: https://www.shanlaxpublications.com/p/ctbtls/ch002.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xinsheng Nan & Huck-Hui Ng & Colin A. Johnson & Carol D. Laherty & Bryan M. Turner & Robert N. Eisenman & Adrian Bird, 1998. "Transcriptional repression by the methyl-CpG-binding protein MeCP2 involves a histone deacetylase complex," Nature, Nature, vol. 393(6683), pages 386-389, 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. Silvia Da Ros & Luca Aresu & Serena Ferraresso & Eleonora Zorzan & Eugenio Gaudio & Francesco Bertoni & Mauro Dacasto & Mery Giantin, 2018. "Validation of epigenetic mechanisms regulating gene expression in canine B-cell lymphoma: An in vitro and in vivo approach," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-19, December.
    2. Boris Kantor & Bernadette O’Donovan & Joseph Rittiner & Dellila Hodgson & Nicholas Lindner & Sophia Guerrero & Wendy Dong & Austin Zhang & Ornit Chiba-Falek, 2024. "The therapeutic implications of all-in-one AAV-delivered epigenome-editing platform in neurodegenerative disorders," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    3. Patrick A Riley, 2018. "Epigenetic Error and Large-scale Genomic Instability in Cancer," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 4(3), pages 3943-3946, May.
    4. Parker C. Wilson & Yoshiharu Muto & Haojia Wu & Anil Karihaloo & Sushrut S. Waikar & Benjamin D. Humphreys, 2022. "Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression," Nature Communications, Nature, vol. 13(1), pages 1-20, 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:dax:ctbtls:978-93-6163-763-6:p:8-21. 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: S.Lakshmanan (email available below). General contact details of provider: .

    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.