MOLECULAR DOCKING, ADMET, AND MOLECULAR DYNAMICS SIMULATION STUDIES FOR MOLECULES WITH EXPECTED HDAC INHIBITION ACTIVITY
Abstract
Background: Histone deacetylases (HDACs) are promising epigenetic target for the treatment of a variety of diseases including cancer, inflammations, and neurological disorders. A number of. HDAC inhibitors have been approved for the treatment of cancer. Most of the HDAC inhibitors have poor pharmacokinetic properties such as short half-life, fast metabolism, and clearance. To overcome this limitation, several attempts are ongoing to develop new molecules with unique zinc binding groups. The objective is to design and evaluate new compounds featuring heterocyclic ring-based zinc binding groups (ZBGs) targeting histone deacetylases (HDACs) for potential therapeutic use in various diseases, including cancer, inflammations, and neurological disorders. The expected zinc chelation activity for ZBG in addition the construction of the linker and the cap group were evaluated using molecular modeling studies.
Materials & Methods: A series of new compounds with promising HDAC inhibition activities were designed based on a molecular modeling to improve the HDACs inhibitory potency, improving pharmacokinetic properties, and conferring cancer cell targeting. Twenty new compounds (K1-K20) were designed via special modification of common structural activity relationship (SAR) of HDAC inhibitors using heterocyclic rings as a zinc binding group (ZBG), diverse group in cap group, and hydrophobic linker. These compounds were analyzed by docking study, ADMET, and molecular dynamics (MD) simulations against HDAC isoforms using vorinostat as a reference.
Results: The docking study revealed that the proposed compounds haves higher docking score than vorinostat. All molecules were showed promising virtual HDACs binding affinity. The ADMET analysis of the designed compound showed acceptable pharmacokinetics results. In comparison to vorinostat, the MD simulation analysis revealed that compound K1 had significantly perfect alignment to HDAC8.
Conclusions: The precise virtual binding affinity for K1 might be attributed to the unique chelation capacity of the amino group of imidazole ZBG of K1 with zinc metal cofactor of HDACs enzymes, other interaction of linker with surrounding amino acid residues, and the presence of fused aromatic ring in cap group.
Keywords
Full Text:
PDFReferences
Tronick E, Hunter RG. Waddington, Dynamic Systems, and Epigenetics. Front Behav Neurosci. 2016;10:107. https://doi.org/10.3389/fnbeh.2016.00107
Saeed AM, Al-Hamashi AA. Molecular Docking, ADMET Study, Synthesis, Characterization and Preliminary Antiproliferative Activity of Potential Histone Deacetylase Inhibitors with Isoxazole as New Zinc Binding Group. Iraqi Journal of Pharmaceutical Sciences. 2023 Nov 3;32(Suppl.):188-203. https://doi.org/10.31351/vol32issSuppl.pp188-203
Abdulameer AMS, Al-Hamashi AAA. Docking, ADMET study, Synthesis and Biological evaluation of Isoxazole Derivatives as potential Histone Deacetylase Inhibitors. History of Medicine. 2023;9(1):2501-508. https://doi.org/10.17720/2409-5834.v9.1.2023324
Mosa HM, Al-Hamashi AA. Design, Synthesis, and Cytotoxicity Evaluation of Sulfonamide Derivatives as Potential HDAC Inhibitors. Azerbaijan Pharmaceutical and Pharmacotherapy Journal. 2023;22(2):214-7. https://doi.org/10.61336/appj/22-2-44
Jones P, Issa JP, Baylin S. Targeting the cancer epigenome for therapy. Nat Rev Genet. 2016;17:630-41. https://doi.org/10.1038/nrg.2016.93
Al-Hamashi A, Abdulhadi S, Ali R. Evaluation of Zinc Chelation Ability for Non-Hydroxamic Organic Moieties. Egyptian Journal of Chemistry. 2023;66(5):215-21. https://doi.org/10.21608/ejchem.2022.147377.6415
Al-Hamashi AA, Koranne R, Dlamini S, Alqahtani A, Karaj E, Rashid MS, et al. A new class of cytotoxic agents targets tubulin and disrupts microtubule dynamics. Bioorg Chem. 2021;116:105297. https://doi.org/10.1016/j.bioorg.2021.105297
Alwash AH, Naser NH. Synthesis, characterization, and vitro evaluation of new materials in vorinostat analogs containing biomolecules. Materials Today: Proceedings. 2022;60:1424-39. https://doi.org/10.1016/j.matpr.2021.11.016
Nadendla RR. Molecular modeling: A powerful tool for drug design and molecular docking. Reson. 2004;9:51-60. https://doi.org/10.1007/BF02834015
Ferreira LG, Dos Santos RN, Oliva G, Andricopulo AD. Molecular Docking and Structure-Based Drug Design Strategies. Molecules. 2015;20:13384-421. https://doi.org/10.3390/molecules200713384
Zhu K, Borrelli KW, Greenwood JR, Day T, Abel R, Farid RS, et al. Docking Covalent Inhibitors: A Parameter Free Approach To Pose Prediction and Scoring. J Chem Inf Model. 2014;54(7):1932-40. https://doi.org/10.1021/ci500118s
Halgren TA, Murphy RB, Friesner RA, Beard HS, Frye LL, Pollard WT, et al. Glide: A new approach for rapid, accurate docking and scoring. J Med Chem. 2004;47:1750-59. https://doi.org/10.1021/jm030644s
Hai Y, Christianson D. Histone deacetylase 6 structure and molecular basis of catalysis and inhibition. Nat Chem Biol. 2016;12:741-47. https://doi.org/10.1038/nchembio.2134
Lauffer BE, Mintzer R, Fong R, Kaminker JS, Heise CE, Steiner P, et al. Histone deacetylase (HDAC) inhibitor kinetic rate constants correlate with cellular histone acetylation but not transcription and cell viability. J Biol Chem. 2013;288(37):26926-43. https://doi.org/10.1074/jbc.M113.490706
Somoza JR, Skene RJ, Katz BA, Swanson RV, McRee DE, Tari LW, et al. Structural snapshots of human HDAC8 provide insights into the class I histone deacetylases. Structure. 2004 Jul;12(7):1325-34. https://doi.org/10.1016/j.str.2004.04.012
Mali S, Chaudhari H. Computational Studies on Imidazo[1,2-a] Pyridine-3-Carboxamide Analogues as Antimycobacterial Agents: Common Pharmacophore Generation, Atom-based 3D-QSAR, Molecular dynamics Simulation, QikProp, Molecular Docking and Prime MMGBSA Approaches. Open Pharmaceutical Sciences Journal. 2018;5:13. https://doi.org/10.2174/1874844901805010012
Lu C, Wu C, Ghoreishi D, Chen W, Wang L, Damm W, et al. OPLS4: Improving force field accuracy on challenging regimes of chemical space. J Chem Theory Comput. 2021;17(7):4291-300. https://doi.org/10.1021/acs.jctc.1c00302
Friesner RA, Murphy RB, Repasky MP, Frye LL, Greenwood JR, Halgren TA, et al. Extra precision Glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J Med Chem. 2006;49:6177-96. https://doi.org/10.1021/jm051256o
QikProp, Schrödinger, LLC, New York, NY. 2021.
Bowers KJ, Chow E, Xu H, et al. Scalable algorithms for molecular dynamics simulations on commodity clusters. Proceedings of the ACM/IEEE Conference on Supercomputing (SC06), Tampa, Florida, November 11-17, 2006. https://doi.org/10.1145/1188455.544
Hasan Y, Al-Hamashi A. Identification of Selisistat Derivatives as SIRT1-3 Inhibitors by in Silico Virtual Screening. Turkish Computational and Theoretical Chemistry. 2024;8(2):1-11. https://doi.org/10.33435/tcandtc.1224592
Repasky MP, Murphy RB, Banks JL, Greenwood JR, Tubert-Brohman I, Bhat S, et al. Docking performance of the glide program as evaluated on the Astex and DUD datasets: a complete set of glide SP results and selected results for a new scoring function integrating WaterMap and glide. J Comput Aided Mol Des. 2012;26:787-99. https://doi.org/10.1007/s10822-012-9575-9
Ntie-Kang F. An in-silico evaluation of the ADMET profile of the Streptome DB database. Springerplus. 2013 Jul 30;2:353. https://doi.org/10.1186/2193-1801-2-353
Hollingsworth S, Dror R. Molecular Dynamics Simulation for All. Neuron. 2018;99:1129-43. https://doi.org/10.1016/j.neuron.2018.08.011
DOI: https://doi.org/10.46903/gjms/22.02.1640
Refbacks
- There are currently no refbacks.
Copyright (c) 2024. Zaid Mahmood Mohammed, Ayad Abed Ali Al-Hamashi

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Gomal Medical College, Daraban Road, Dera Ismail Khan, Pakistan
ISSN: 1819-7973, e-ISSN: 1997-2067
Website: https://www.gmcdikhan.edu.pk
Phone: +92-966-747373

