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2000
Volume 22, Issue 6
  • ISSN: 1570-1638
  • E-ISSN: 1875-6220

Abstract

Introduction

Telomerase is a well-recognised and a promising target for cancer therapy. In this study, we selected ligand-based approaches to design telomerase inhibitors for the development of potent anticancer agents for future cancer therapy.

Methods

To investigate the chemical characteristics required for telomerase inhibitory activity, a ligand-based pharmacophore model of oxadiazole derivatives reported from the available literature was generated using the Schrodinger phase tool. This selected pharmacophore hypothesis is validated by screening a dataset of reported oxadiazole derivatives. The pharmacophore model was selected for virtual screening using ZINCPharmer against the ZINC database. The ZINC database molecules with pharmacophore features similar to the selected pharmacophore model and good fitness score were taken for molecular docking studies. With the pkCSM and SwissADME tools we predicted the pharmacokinetic and toxicity of top ten ZINC database compounds based on docking score, binding interactions and identified two potential compounds with good absorption, distribution, metabolism, and less toxicity. Then both the hit molecules were exposed to molecular dynamic simulation integrated with MM-PBSA binding free energy calculations using GROMACS tools.

Results

The generated pharmacophore model displayed five features, two hydrophobic and three aromatic rings. The MM-PBSA calculations exhibited that the free binding energy of selected protein-ligand complexes were found stable and stabilized with non-polar and van-der walls free energies.

Conclusion

Our study suggests that ZINC82107047 and ZINC8839196 can be used as hit molecules for future biological screening and for discovery of safe and potent drugs as telomerase inhibitors for cancer therapy.

© 2025 Bentham Science Publishers
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References

  1. O’SullivanR.J. KarlsederJ. Telomeres: Protecting chromosomes against genome instability.Nat. Rev. Mol. Cell Biol.201011317118110.1038/nrm284820125188
     [Google Scholar]
  2. HayflickL. MoorheadP.S. The serial cultivation of human diploid cell strains.Exp. Cell Res.196125358562110.1016/0014‑4827(61)90192‑613905658
     [Google Scholar]
  3. NaultJ.C. MalletM. PilatiC. High frequency of telomerase reverse-transcriptase promoter somatic mutations in hepatocellular carcinoma and preneoplastic lesions.Nat. Commun.201341221810.1038/ncomms321823887712
     [Google Scholar]
  4. DilleyR.L. GreenbergR.A. Alternative telomere maintenance and cancer.Trends Cancer20151214515610.1016/j.trecan.2015.07.00726645051
     [Google Scholar]
  5. DeyA. ChakrabartiK. Current perspectives of telomerase structure and function in eukaryotes with emerging views on telomerase in human parasites.Int. J. Mol. Sci.201819233310.3390/ijms1902033329364142
     [Google Scholar]
  6. KimN.W. PiatyszekM.A. ProwseK.R. Specific association of human telomerase activity with immortal cells and cancer.Science199426651932011201510.1126/science.76054287605428
     [Google Scholar]
  7. OzturkM. LiY. TergaonkarV. Current insights to regulation and role of telomerase in human diseases.Antioxidants2017611710.3390/antiox601001728264499
     [Google Scholar]
  8. FelsherD.W. AvvanitisC. BendapudiP. BachiredyP. Oncogenes and the initiation and maintenance of tumorigenesis.Molecular Basis of Human Cancer. 2nd ed ColemanW.B. TsongalisG.J. New York, NYSpringer201714314510.1007/978‑1‑59745‑458‑2_8
     [Google Scholar]
  9. KoesD.R. CamachoC.J. ZINCPharmer: Pharmacophore search of the ZINC database.Nucleic Acids Res.201240W1W409-1410.1093/nar/gks37822553363
     [Google Scholar]
  10. PiresD.E.V. BlundellT.L. AscherD.B. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures.J. Med. Chem.20155894066407210.1021/acs.jmedchem.5b0010425860834
     [Google Scholar]
  11. Schrödinger Release2018-3: Maestro.New York, NYSchrödinger, LLC2018
     [Google Scholar]
  12. ZhangF. WangX.L. ShiJ. Synthesis, molecular modeling and biological evaluation of N-benzylidene-2-((5-(pyridin-4-yl)-1,3,4-oxadiazol-2-yl)thio)acetohydrazide derivatives as potential anticancer agents.Bioorg. Med. Chem.201422146847710.1016/j.bmc.2013.11.00424286761
     [Google Scholar]
  13. ZhangX.M. QiuM. SunJ. Synthesis, biological evaluation, and molecular docking studies of 1,3,4-oxadiazole derivatives possessing 1,4-benzodioxan moiety as potential anticancer agents.Bioorg. Med. Chem.201119216518652410.1016/j.bmc.2011.08.01321962523
     [Google Scholar]
  14. ZhangY.B. WangX.L. LiuW. YangY.S. TangJ.F. ZhuH.L. Design, synthesis and biological evaluation of heterocyclic azoles derivatives containing pyrazine moiety as potential telomerase inhibitors.Bioorg. Med. Chem.201220216356636510.1016/j.bmc.2012.08.05923018096
     [Google Scholar]
  15. ReleaseS Schrödinger Release 2018-3: LigPrepSchrödinger, LLCNew York, NYAvailable from: https://www.schrodinger.com/platform/products/ligprep/ 2018
     [Google Scholar]
  16. ZhengQ.Z. ZhangX.M. XuY. ChengK. JiaoQ.C. ZhuH.L. Synthesis, biological evaluation, and molecular docking studies of 2-chloropyridine derivatives possessing 1,3,4-oxadiazole moiety as potential antitumor agents.Bioorg. Med. Chem.201018227836784110.1016/j.bmc.2010.09.05120947362
     [Google Scholar]
  17. SunJ. ZhuH. YangZ.M. ZhuH.L. Synthesis, molecular modeling and biological evaluation of 2-aminomethyl-5-(quinolin-2-yl)-1,3,4-oxadiazole-2(3H)-thione quinolone derivatives as novel anticancer agent.Eur. J. Med. Chem.201360232810.1016/j.ejmech.2012.11.03923279864
     [Google Scholar]
  18. DixonS.L. SmondyrevA.M. KnollE.H. RaoS.N. ShawD.E. FriesnerR.A. PHASE: A new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results.J. Comput. Aided Mol. Des.20062010-1164767110.1007/s10822‑006‑9087‑617124629
     [Google Scholar]
  19. KleinjungJ. FraternaliF. Design and application of implicit solvent models in biomolecular simulations.Curr. Opin. Struct. Biol.20142510012613410.1016/j.sbi.2014.04.00324841242
     [Google Scholar]
  20. FriesnerR.A. BanksJ.L. MurphyR.B. Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.J. Med. Chem.20044771739174910.1021/jm030643015027865
     [Google Scholar]
  21. SallamA.A. HoussenW.E. GissendannerC.R. OrabiK.Y. FoudahA.I. El SayedK.A. Bioguided discovery and pharmacophore modeling of the mycotoxic indole diterpene alkaloids penitrems as breast cancer proliferation, migration, and invasion inhibitors.MedChemComm20134101360136910.1039/c3md00198a24273638
     [Google Scholar]
  22. HallM.D. SalamN.K. HellawellJ.L. Synthesis, activity, and pharmacophore development for isatin-beta-thiosemicarbazones with selective activity toward multidrug-resistant cells.J. Med. Chem.200952103191320410.1021/jm800861c19397322
     [Google Scholar]
  23. MurahariM. PrakashK.V. PetersG.J. MayurY.C. Acridone-pyrimidine hybrids- design, synthesis, cytotoxicity studies in resistant and sensitive cancer cells and molecular docking studies.Eur. J. Med. Chem.201713996198110.1016/j.ejmech.2017.08.02328886509
     [Google Scholar]
  24. Schrodinger Release 2018-3: Glide, Schrodinger, LLC, New York, NY, 2018
  25. BryanC. RiceC. HoffmanH. HarkisheimerM. SweeneyM. SkordalakesE. Structural basis of telomerase inhibition by the highly specific BIBR1532.Structure201523101934194210.1016/j.str.2015.08.00626365799
     [Google Scholar]
  26. Glide ver 59Schrödinger LLCNew York, NY (USA)2010
     [Google Scholar]
  27. FriesnerR.A. MurphyR.B. RepaskyM.P. Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes.J. Med. Chem.200649216177619610.1021/jm051256o17034125
     [Google Scholar]
  28. CutinhoP.F. RoyJ. AnandA. ShankarR. MurahariM. VenkataramanaC.H.S. Design of metronidazole derivatives and flavonoids as potential non-nucleoside reverse transcriptase inhibitors using combined ligand- and structure-based approaches.J. Biomol. Struct. Dyn.20203861626164810.1080/07391102.2019.1614094
     [Google Scholar]
  29. DainaA. MichielinO. ZoeteV. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.Sci. Rep.201774271710.1038/srep4271728256516
     [Google Scholar]
  30. LindahlE. AbrahamM.J. BerkH. Van Der SpoelD. GROMACS 2019.4 Source Code.2019Available from: [https://www.scirp.org/reference/referencespapers?referenceid=2886944
  31. GangadharappaB.S. SharathR. RevanasiddappaP.D. ChandramohanV. BalasubramaniamM. VardhineniT.P. Structural insights of metallo-beta-lactamase revealed an effective way of inhibition of enzyme by natural inhibitors.J. Biomol. Struct. Dyn.202038133757377110.1080/07391102.2019.166726531514687
     [Google Scholar]
  32. KumarB. ParasuramanP. MurthyT.P.K. MurahariM. ChandramohanV. In silico screening of therapeutic potentials from Strychnosnux-vomica against the dimeric main protease (Mpro) structure of SARS-CoV-2.J. Biomol. Struct. Dyn.20214017119
     [Google Scholar]
  33. KrishnaS. KumarS.B. MurthyT.P.K. MurahariM. Structure-based design approach of potential BCL-2 inhibitors for cancer chemotherapy.Comput. Biol. Med.202113410445510.1016/j.compbiomed.2021.104455
     [Google Scholar]
  34. SchüttelkopfA.W. van AaltenD.M.F. PRODRG: A tool for high-throughput crystallography of protein–ligand complexes.Acta Crystallogr. D Biol. Crystallogr.20046081355136310.1107/S090744490401167915272157
     [Google Scholar]
  35. MohankumarT. ChandramohanV. LalithambaH.S. Design and molecular dynamic investigations of 7,8-dihydroxyflavone derivatives as potential neuroprotective agents against alpha-synuclein.Sci. Rep.202010159910.1038/s41598‑020‑57417‑9
     [Google Scholar]
  36. KumariR. KumarR. LynnA. g_mmpbsa--A GROMACS tool for high-throughput MM-PBSA calculations.J. Chem. Inf. Model.20145471951196210.1021/ci500020m24850022
     [Google Scholar]
  37. PrasanthD.S.N.B.K. MurahariM. ChandramohanV. PandaS.P. AtmakuriL.R. GuntupalliC. In silico identification of potential inhibitors from Cinnamon against main protease and spike glycoprotein of SARS CoV-2.J. Biomol. Struct. Dyn.2020202011510.1080/07391102.2020.177912932567989
     [Google Scholar]
  38. AliebrahimiS. Montasser KouhsariS. OstadS.N. ArabS.S. KaramiL. Identification of phytochemicals targeting c-met kinase domain using consensus docking and molecular dynamics simulation studies.Cell Biochem. Biophys.2018761-213514510.1007/s12013‑017‑0821‑628852971
     [Google Scholar]
  39. GhoshR. ChakrabortyA. BiswasA. ChowdhuriS. Evaluation of green tea polyphenols as novel corona virus (SARS CoV-2) main protease (Mpro) inhibitors–an in silico docking and molecular dynamics simulation study.J. Biomol. Struct. Dyn.202039124362437410.1080/07391102.2020.177981832568613
     [Google Scholar]
  40. ReedJ.C. ZhaH. Aime-SempeC. TakayamaS. WangH.G. Structure-function analysis of Bcl-2 family proteins. Regulators of programmed cell death.Adv. Exp. Med. Biol.19964069911210.1007/978‑1‑4899‑0274‑0_108910675
     [Google Scholar]
  41. GargS. AnandA. LambaY. RoyA. Molecular docking analysis of selected phytochemicals against SARS-CoV-2 Mpro receptor.Vegetos202033476678110.1007/s42535‑020‑00162‑133100613
     [Google Scholar]
  42. Udhaya KumarS. Thirumal KumarD. MandalP.D. Comprehensive in silico screening and molecular dynamics studies of missense mutations in Sjogren-Larsson syndrome associated with the ALDH3A2 gene.Adv. Protein Chem. Struct. Biol.202012034937710.1016/bs.apcsb.2019.11.00432085885
     [Google Scholar]
  43. GenhedenS. RydeU. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities.Expert Opin. Drug Discov.201510544946110.1517/17460441.2015.103293625835573
     [Google Scholar]
  44. MukherjeeS. DasguptaS. AdhikaryT. AdhikariU. PanjaS.S. Structural insight to hydroxychloroquine-3C-like proteinase complexation from SARS-CoV-2: Inhibitor modelling study through molecular docking and MD-simulation study.J. Biomol. Struct. Dyn.2020391811310.1080/07391102.2020.180445832772895
     [Google Scholar]
  45. BajajS. KumarM.S. PetersG.J. MayurY.C. Targeting telomerase for its advent in cancer therapeutics.Med. Res. Rev.20204051871191910.1002/med.2167432391613
     [Google Scholar]
  46. ZhangY YangX ZhouH YaoG ZhouL QianC. BIBR1532 inhibits proliferation and enhances apoptosis in multiple myeloma cells by reducing telomerase activity.PeerJ 202311e1640410.7717/peerj.1640437953768
     [Google Scholar]
  47. YangH. ZhangH. ZhongY. Concomitant underexpression of TGFBR2 and overexpression of hTERT are associated with poor prognosis in cervical cancer.Sci. Rep.2017714167010.1038/srep4167028195144
     [Google Scholar]
  48. MazloumiZ. RafatA. Dizaji AslK. Nozad CharoudehH. A combination of telomerase inhibition and NK cell therapy increased breast cancer cell line apoptosis.Biochem. Biophys. Res. Commun.2023640505510.1016/j.bbrc.2022.11.09036502631
     [Google Scholar]
  49. El-DalyH. KullM. ZimmermannS. PanticM. WallerC.F. MartensU.M. Selective cytotoxicity and telomere damage in leukemia cells using the telomerase inhibitor BIBR1532.Blood200510541742174910.1182/blood‑2003‑12‑432215507522
     [Google Scholar]
/content/journals/cddt/10.2174/0115701638352883250414054348
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Design of Potent Telomerase Inhibitors using Ligand-based Approaches and Molecular Dynamics Simulations Studies
Current Drug Discovery Technologies 22, E15701638352883 (2025); https://doi.org/10.2174/0115701638352883250414054348
/content/journals/cddt/10.2174/0115701638352883250414054348
/content/journals/cddt/10.2174/0115701638352883250414054348
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  • Article Type:     Research Article
Keyword(s): cancer therapy; docking score; gene expression; MD simulation; pharmacophore; Telomerase; virtual screening

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