Computational Analysis of Selected Phytochemicals for their PARP Inhibitory Potential in Cancer
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Abstract
Poly (ADP-ribose) polymerase (PARP) inhibitors have emerged as promising agents in cancer prevention due to their ability to target DNA repair machinery of cancerous cells. PARP enzymes repair single-strand DNA breaks through the base excision repair pathway. In cancer cells, particularly those with deficiencies in homologous recombination, PARP aids in DNA repair pathways and promote cancer cell survival. PARP inhibitors suppress the enzyme function and thus induce apoptosis in cancerous cells. Phytochemicals, bioactive compounds derived from plants, have gained increasing attention for their potential role in cancer prevention and treatment. We have investigated selected phytochemicals such as cinnamaldehyde, baicalein, curcumin, galangin, ellagic acid, resveratrol, pinocembrin, genistein, quercetin, and apigenin against PARP. The assessment of selected phytochemicals, including baicalein, galangin, ellagic acid, genistein, and apigenin, reveals promising attributes through various computational analyses. Specifically, these compounds exhibit favorable docking scores, indicating strong binding affinity to their target molecules. Molecular dynamic simulation for 10 nanosecond was performed to validate the findings. Moreover, their potential as PARP inhibitors suggests a plausible role in inhibiting DNA repair mechanisms, an essential aspect of cancer therapy. These compounds were found to exert PARP inhibition through direct interference with enzymatic activity or modulation of PARP expression. This targeted investigation underscores the potential of these phytochemicals as PARP inhibitors contributing to the advancement of precision cancer therapeutics.
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33. Balasundaram A, Doss GPC. A computational examination of the therapeutic advantages of fourth-generation ALK inhibitors TPX-0131 and repotrectinib over third-generation lorlatinib for NSCLC with ALK F1174C/L/V mutations. Frontiers in Molecular Biosciences. 2024;10.
34. Saah SA, Sakyi PO, Adu-Poku D, Boadi NO, Djan G, Amponsah D, et al. Docking and Molecular Dynamics Identify Leads against 5 Alpha Reductase 2 for Benign Prostate Hyperplasia Treatment. Journal of Chemistry. 2023;2023:8880213.
2. Pérez-Herrero E, Fernández-Medarde A. Advanced targeted therapies in cancer: Drug nanocarriers, the future of chemotherapy. Eur J Pharm Biopharm. 2015;93:52-79.
3. Joo WD, Visintin I, Mor G. Targeted cancer therapy–are the days of systemic chemotherapy numbered? Maturitas. 2013;76(4):308-314.
4. Herrstedt J, Dombernowsky P. Anti‐emetic therapy in cancer chemotherapy: current status. Basic Clin Pharmacol Toxicol. 2007;101(3):143-150.
5. Schmitt CA, Wang B, Demaria M. Senescence and cancer—role and therapeutic opportunities. Nat Rev Clin Oncol. 2022;19(10):619-636.
6. Jubin T, Kadam A, Jariwala M, Bhatt S, Sutariya S, Gani AR, et al. The PARP family: insights into functional aspects of poly (ADP‐ribose) polymerase‐1 in cell growth and survival. Cell Prolif. 2016;49(4):421-437.
7. Hassa PO, Haenni SS, Elser M, Hottiger MO. Nuclear ADP-ribosylation reactions in mammalian cells: where are we today and where are we going? Microbiol Mol Biol Rev. 2006;70(3):789-829.
8. Thomas C, Tulin AV. Poly-ADP-ribose polymerase: machinery for nuclear processes. Mol Aspects Med. 2013;34(6):1124-1137.
9. De Vos M, Schreiber V, Dantzer F. The diverse roles and clinical relevance of PARPs in DNA damage repair: current state of the art. Biochem Pharmacol. 2012;84(2):137-146.
10. Javle M, Curtin NJ. The potential for poly (ADP-ribose) polymerase inhibitors in cancer therapy. Ther Adv Med Oncol. 2011;3(6):257-267.
11. Aberle L, Krüger A, Reber JM, Lippmann M, Hufnagel M, Schmalz M, et al. PARP1 catalytic variants reveal branching and chain length-specific functions of poly (ADP-ribose) in cellular physiology and stress response. Nucleic Acids Res. 2020;48(18):10015-10033.
12. Yi M, Dong B, Qin S, Chu Q, Wu K, Luo S. Advances and perspectives of PARP inhibitors. Exp Hematol Oncol. 2019;8:1-12.
13. Ranjan A, Ramachandran S, Gupta N, Kaushik I, Wright S, Srivastava S, Das H, Srivastava S, Prasad S, Srivastava SK. Role of Phytochemicals in Cancer Prevention. Int J Mol Sci. 2019;20(20):4981.
14. Pagliaro B, Santolamazza C, Simonelli F, Rubattu S. Phytochemical Compounds and Protection from Cardiovascular Diseases: A State of the Art. Biomed Res Int. 2015;2015:918069.
15. Ajiboye BO, Iwaloye O, Owolabi OV, Ejeje JN, Okerewa A, Johnson OO, et al. Screening of potential antidiabetic phytochemicals from Gongronema latifolium leaf against therapeutic targets of type 2 diabetes mellitus: multi-targets drug design. SN Applied Sciences. 2021;4(1):14.
16. Abbas K, Alam M, Ali V, Ajaz M. Virtual screening, molecular docking and ADME/T properties analysis of neuroprotective property present in root extract of chinese skullcap against β-site amyloid precursor protein cleaving enzyme 1 (BACE1) in case of alzheimer’s disease. J Pharmacogn Phytochem. 2023;12(1):146-53.
17. Mangal M, Sagar P, Singh H, Raghava GP, Agarwal SM. NPACT: Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database. Nucleic Acids Res. 2013 J(Database issue):D1124-9.
18. Schrödinger L, DeLano W. PyMOL. 2020. Available from: http://www.pymol.org/pymol.
19. O'Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR. Open Babel: An open chemical toolbox. J Cheminform. 2011;3(1):1-4.
20. Dallakyan S, Olson AJ. Small-molecule library screening by docking with PyRx. Chem Biol Methods Protoc. 2015:243-50.
21. Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-61.
22. Discovery Studio Modeling Environment, Release 4.5. 2021. BIOVIA, Dassault Systèmes, San Diego.
23. Oostenbrink C, Villa A, Mark AE, van Gunsteren WF. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J Comput Chem. 2004(13):1656-76
24. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1-2:19-25.
25. Bjelkmar P, Larsson P, Cuendet MA, Hess B, Lindahl E. Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models. J Chem Theory Comput. 2010;6(2):459-66.
26. Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:42717.
27. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original particle: S0169-409X(96)00423-1. Adv Drug Deliv Rev. 2001;46(1-3):3-26.
28. Cheng F, Li W, Zhou Y, et al. AdMetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties. J Chem Inf Model. 2012;52(11):3099-3105.
29. Banerjee P, Eckert A, Schrey AK, Preißner R. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 2018;46(W1):W257-W263.
30. Filimonov DA, Lagunin AA, Gloriozova TA, Rudik AV, Druzhilovskii DS, Pogodin PV, Poroikov VV. Prediction of the biological activity spectra of organic compounds using the PASS online web resource. Chem Heterocycl Compd. 2014;50:444-57.
31. Lindorff-Larsen K, Piana S, Palmo K, Maragakis P, Klepeis JL, Dror RO, Shaw DE. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins. 2010;78(8):1950-8.
32. Meena P, Manral A, Nemaysh V, Saini V, Siraj F, Luthra P, et al. Novel Insights into Multitargeted Potential of N'-(4-benzylpiperidin-1-yl)alkylamine derivatives in the Management of Alzheimer's Disease Associated Pathogenesis. RSC Adv. 2016;6.
33. Balasundaram A, Doss GPC. A computational examination of the therapeutic advantages of fourth-generation ALK inhibitors TPX-0131 and repotrectinib over third-generation lorlatinib for NSCLC with ALK F1174C/L/V mutations. Frontiers in Molecular Biosciences. 2024;10.
34. Saah SA, Sakyi PO, Adu-Poku D, Boadi NO, Djan G, Amponsah D, et al. Docking and Molecular Dynamics Identify Leads against 5 Alpha Reductase 2 for Benign Prostate Hyperplasia Treatment. Journal of Chemistry. 2023;2023:8880213.
| Files | ||
| Issue | Vol 2 No 1 (2024) | |
| Section | Original Articles | |
| DOI | https://doi.org/10.18502/abi.v2i1.16243 | |
| Keywords | ||
| PARP DNA repair phytochemicals cancer molecular docking MD simulation | ||
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How to Cite
1.
Alam M, Abbas K, Chaudhary B, Asif S, Balti AA. Computational Analysis of Selected Phytochemicals for their PARP Inhibitory Potential in Cancer. ABI. 2024;2(1):11-21.
