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Volume 21, Issue 18
  • ISSN: 1570-1808
  • E-ISSN: 1875-628X

Abstract

Background

Enzymes belonging to the kinase family have been extensively implicated in cancer. Aurora A (AURKA) is crucial in regulating the cell cycle. AURKA's significant role in the formation of abnormal mitotic spindles and the failure of cytokinesis positions it as a promising target for anticancer treatments. Notably, AURKA is observed to be overexpressed in various cancer types, making its inhibition a compelling strategy for the development of anticancer agents.

Objective

In this study, we set out to investigate a novel de novo design strategy aimed at developing and optimizing potent inhibitors for Aurora Kinase A. Given Aurora Kinase A's critical role in cell cycle regulation and its overexpression in various cancers, it presents a promising target for therapeutic intervention. Our goal was to create a new library of compounds, building on existing inhibitors known for their selectivity and potency against Aurora Kinase A. By making strategic modifications to these lead molecules, we aimed to improve their binding affinity and inhibitory effectiveness. This research was focused on identifying and refining compounds with enhanced drug-like properties and robust inhibitory potential, contributing to the advancement of effective anticancer therapies.

Methods

A compound library based on known inhibitors having Aurora Kinase A selectivity and IC value in the nanomolar range was designed by modification in the lead molecules identified by analyzing the binding mode of the molecules in the catalytic site of the enzyme. A molecular docking study was performed in GOLD 2020. Drug-likeness ADME parameters (molecular weight, H-bond acceptors, H-bond donors, LogP, and the number of rotatable bonds) of designed molecules were calculated using SwissADME, pkCSM, and ProToxII web servers.

Results

The docking study, utilizing GOLD 2020 software on Aurora Kinase A (PDB: 3W2C), successfully identified inhibitors that hindered the enzyme's activity by occupying its catalytic site. This inhibition mechanism, consistent across all cases, involves crucial interactions with residues such as Ala213, Asp274, and Phe144. A detailed analysis of the compounds guided the design of new analogs, aiming to enhance the lead compound's affinity for the receptor. Subsequent derivatization of M1 and M15 resulted in molecules (M1_46, M1_49, M1_50, M15_21, M15_14, and M15_43) showing a notable 10-15% increase in the Chemscore fitness scoring function compared to their parent molecules. This improvement correlated with a rise in the number of hydrogen bond interactions in the complexes, guiding further development.

Conclusion

This computational assessment lays a foundation for further in-vitro and in-vivo studies in drug development, suggesting these derivatives as promising candidates for cancer treatment.

© 2024 Bentham Science Publishers
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2024-12-26
2025-05-08

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References

  1. HeX. JiangZ. AkakuruO.U. LiJ. WuA. Nanoscale covalent organic frameworks: from controlled synthesis to cancer therapy.Chem. Commun. (Camb.)20215793124171243510.1039/D1CC04846E34734601
     [Google Scholar]
  2. AshrafizadehM. DaiJ. TorabianP. NabaviN. ArefA.R. AljabaliA.A.A. TambuwalaM. ZhuM. Circular RNAs in EMT-driven metastasis regulation: modulation of cancer cell plasticity, tumorigenesis and therapy resistance.Cell. Mol. Life Sci.202481121410.1007/s00018‑024‑05236‑w38733529
     [Google Scholar]
  3. YuY. WangL. NiS. LiD. LiuJ. ChuH.Y. ZhangN. SunM. LiN. RenQ. ZhuoZ. ZhongC. XieD. LiY. ZhangZ.K. ZhangH. LiM. ZhangZ. ChenL. PanX. XiaW. ZhangS. LuA. ZhangB.T. ZhangG. Targeting loop3 of sclerostin preserves its cardiovascular protective action and promotes bone formation.Nat. Commun.2022131424110.1038/s41467‑022‑31997‑835869074
     [Google Scholar]
  4. YangB. YangH. LiangJ. ChenJ. WangC. WangY. WangJ. LuoW. DengT. GuoJ. A review on the screening methods for the discovery of natural antimicrobial peptides.J. Pharm. Anal.2024202410104610.1016/j.jpha.2024.101046
     [Google Scholar]
  5. ZhuJ. JiangX. LuoX. ZhaoR. LiJ. CaiH. YeX.Y. BaiR. XieT. Combination of chemotherapy and gaseous signaling molecular therapy: Novel β ‐elemene nitric oxide donor derivatives against leukemia.Drug Dev. Res.202384471873510.1002/ddr.2205136988106
     [Google Scholar]
  6. TangL. ZhangW. ChenL. Brain radiotherapy combined with targeted therapy for HER2-positive breast cancer patients with brain metastases.Breast Cancer20241637939210.2147/BCTT.S460856
     [Google Scholar]
  7. HuangY. WangC. ZhouT. XieF. LiuZ. XuH. LiuM. WangS. LiL. ChiQ. ShiJ. DongN. XuK. Lumican promotes calcific aortic valve disease through H3 histone lactylation.Eur. Heart J.20242024ehae40710.1093/eurheartj/ehae40738976370
     [Google Scholar]
  8. ZhuJ. PanS. ChaiH. ZhaoP. FengY. ChengZ. ZhangS. WangW. Microfluidic Impedance Cytometry Enabled One‐Step Sample Preparation for Efficient Single‐Cell Mass Spectrometry.Small20242026231070010.1002/smll.20231070038483007
     [Google Scholar]
  9. WangY. LiD. LvZ. FengB. LiT. WengX. Efficacy and safety of Gutong Patch compared with NSAIDs for knee osteoarthritis: A real-world multicenter, prospective cohort study in China.Pharmacol. Res.202319710695410.1016/j.phrs.2023.10695437832860
     [Google Scholar]
  10. StefaniA. PiroG. SchietromaF. StrusiA. VitaE. FioraniS. BaroneD. MonacaF. SparagnaI. ValenteG. FerraraM.G. D’ArgentoE. Di SalvatoreM. CarboneC. TortoraG. BriaE. Unweaving the mitotic spindle: A focus on Aurora kinase inhibitors in lung cancer.Front. Oncol.202212102602010.3389/fonc.2022.102602036387232
     [Google Scholar]
  11. AliA. StukenbergP.T. Aurora kinases: Generators of spatial control during mitosis.Front. Cell Dev. Biol.202311113936710.3389/fcell.2023.113936736994100
     [Google Scholar]
  12. de SouzaV.B. KawanoD.F. Structural basis for the design of allosteric inhibitors of the Aurora kinase A enzyme in the cancer chemotherapy.Biochim. Biophys. Acta, Gen. Subj.20201864112944810.1016/j.bbagen.2019.12944831676293
     [Google Scholar]
  13. YevaleD.B. TeraiyaN. LalwaniT.D. AmetaR.K. SanganiC.B. A novel class of pyrazole analogues as aurora kinase A inhibitor: design, synthesis, and anticancer evaluation.Bioorg. Chem.202314110690110.1016/j.bioorg.2023.10690137797455
     [Google Scholar]
  14. BoY.X. XiangR. XuY. HaoS.Y. WangX.R. ChenS.W. Synthesis, biological evaluation and molecular modeling study of 2-amino-3,5-disubstituted-pyrazines as Aurora kinases inhibitors.Bioorg. Med. Chem.202028511535110.1016/j.bmc.2020.11535132035750
     [Google Scholar]
  15. Gomes-FilhoS.M. dos SantosE.O. BertoldiE.R.M. ScalabriniL.C. HeidrichV. DazzaniB. LevantiniE. ReisE.M. BassèresD.S. Aurora A kinase and its activator TPX2 are potential therapeutic targets in KRAS-induced pancreatic cancer.Cell Oncol. (Dordr.)202043344546010.1007/s13402‑020‑00498‑532193808
     [Google Scholar]
  16. NasoF.D. BoiD. AscanelliC. PamfilG. LindonC. PaiardiniA. GuarguagliniG. Nuclear localisation of Aurora-A: its regulation and significance for Aurora-A functions in cancer.Oncogene202140233917392810.1038/s41388‑021‑01766‑w33981003
     [Google Scholar]
  17. Al-SaneaM.M. ElkamhawyA. PaikS. LeeK. El KerdawyA.M. Syed Nasir AbbasB. Joo RohE. EldehnaW.M. ElshemyH.A.H. BakrR.B. Ali FarahatI. AlzareaA.I. AlzareaS.I. AlharbiK.S. AbdelgawadM.A. Sulfonamide-based 4-anilinoquinoline derivatives as novel dual Aurora kinase (AURKA/B) inhibitors: Synthesis, biological evaluation and in silico insights.Bioorg. Med. Chem.2020281311552510.1016/j.bmc.2020.11552532371117
     [Google Scholar]
  18. DuR. HuangC. LiuK. LiX. DongZ. Targeting AURKA in Cancer: molecular mechanisms and opportunities for Cancer therapy.Mol. Cancer20212011510.1186/s12943‑020‑01305‑333451333
     [Google Scholar]
  19. WangW. FengX. LiuH.X. ChenS.W. HuiL. Synthesis and biological evaluation of 2,4-disubstituted phthalazinones as Aurora kinase inhibitors.Bioorg. Med. Chem.201826123217322610.1016/j.bmc.2018.04.04829705376
     [Google Scholar]
  20. AlmogaddamM.A. ShoaibT.H. MohamedS.G.A. MohamedG.A. IbrahimS.R.M. HusseinH.G.A. SindiI.A. AlzainA.A. Computational screening identifies depsidones as promising Aurora A kinase inhibitors: extra precision docking and molecular dynamics studies.Netw. Model. Anal. Health Inform. Bioinform.20241311710.1007/s13721‑024‑00451‑8
     [Google Scholar]
  21. MouP.K. YangE.J. ShiC. RenG. TaoS. ShimJ.S. Aurora kinase A, a synthetic lethal target for precision cancer medicine.Exp. Mol. Med.202153583584710.1038/s12276‑021‑00635‑634050264
     [Google Scholar]
  22. LinS.Y. ChangC.F. CoumarM.S. ChenP.Y. KuoF.M. ChenC.H. LiM.C. LinW.H. KuoP.C. WangS.Y. LiA.S. LinC.Y. YangC.M. YehT.K. SongJ.S. HsuJ.T.A. HsiehH.P. Drug-like property optimization: Discovery of orally bioavailable quinazoline-based multi-targeted kinase inhibitors.Bioorg. Chem.20209810368910.1016/j.bioorg.2020.10368932171993
     [Google Scholar]
  23. HijjawiM.S. AbutayehR.F. TahaM.O. Structure-based discovery and bioactivity evaluation of novel aurora-A kinase inhibitors as anticancer agents via docking-based comparative intermolecular contacts analysis (dbCICA).Molecules20202524600310.3390/molecules2524600333353031
     [Google Scholar]
  24. RasoolN. AkhtarA. HussainW. Insights into the inhibitory potential of selective phytochemicals against Mpro of 2019-nCoV: a computer-aided study.Struct. Chem.20203151777178310.1007/s11224‑020‑01536‑632362735
     [Google Scholar]
  25. ArjmandB. HamidpourS.K. Alavi-MoghadamS. YavariH. ShahbazbadrA. TaviraniM.R. GilanyK. LarijaniB. Molecular docking as a therapeutic approach for targeting cancer stem cell metabolic processes.Front. Pharmacol.20221376855610.3389/fphar.2022.76855635264950
     [Google Scholar]
  26. CheungC.H.A. SarvagallaS. LeeJ.Y.C. HuangY.C. CoumarM.S. Aurora kinase inhibitor patents and agents in clinical testing: an update (2011 – 2013).Expert Opin. Ther. Pat.20142491021103810.1517/13543776.2014.93137424965505
     [Google Scholar]
  27. JingX.L. ChenS.W. Aurora kinase inhibitors: a patent review (2014-2020).Expert Opin. Ther. Pat.202131762564310.1080/13543776.2021.189002733573401
     [Google Scholar]
  28. LiebeschuetzJ.W. ColeJ.C. KorbO. Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test.J. Comput. Aided Mol. Des.201226673774810.1007/s10822‑012‑9551‑422371207
     [Google Scholar]
  29. WarrenG.L. DoT.D. KelleyB.P. NichollsA. WarrenS.D. Essential considerations for using protein–ligand structures in drug discovery.Drug Discov. Today20121723-241270128110.1016/j.drudis.2012.06.01122728777
     [Google Scholar]
  30. MayaC. Using PyMOL to understand why COVID-19 vaccines save lives.J. Chem. Educ.202310031351135610.1021/acs.jchemed.2c0077936920160
     [Google Scholar]
  31. RamírezD. CaballeroJ. Is it reliable to take the molecular docking top scoring position as the best solution without considering available structural data?Molecules2018235103810.3390/molecules2305103829710787
     [Google Scholar]
  32. AlaviA. SharmaV. Role of Docking in Anticancer Drug Discovery.Lett. Drug Des. Discov.202320101490151110.2174/1570180820666221111151104
     [Google Scholar]
  33. SardarH. Drug-like potential of Daidzein using SwissADME prediction: In silico Approaches.Phytonutrients20231628
     [Google Scholar]
  34. 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]
  35. BanerjeeP. EckertA.O. SchreyA.K. PreissnerR. ProTox-II: a webserver for the prediction of toxicity of chemicals.Nucleic Acids Res.201846W1W257W26310.1093/nar/gky31829718510
     [Google Scholar]
  36. SinghM. KumarB. K SinghA.; Shekhar Azad, C.; K Yadav, M.; Kumar, A.; Kumar, R.; Kumar, A.; Chaudhary, P. Pharmacokinetic screening to Estimate the drug likeliness characteristics of selected Herbal Anticancer Drugs.Research Journal of Pharmacy and Technology20231673422342610.52711/0974‑360X.2023.00566
     [Google Scholar]
  37. AzzamK.A. SwissADME and pkCSM webservers predictors: An integrated online platform for accurate and comprehensive predictions for in silico ADME/T properties of artemisinin and its derivatives.Kompleksnoe Ispolzovanie Mineralnogo Syra Complex use of mineral resources.202332521421
     [Google Scholar]
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Unlocking Therapeutic Potential: Molecular Docking Insights into Aurora Kinase A Inhibitors Patented and Published from 2011-2020 for Innovative Anticancer Drug Design
Letters in Drug Design & Discovery 21, 4293 (2024); https://doi.org/10.2174/0115701808310599241003080546
/content/journals/lddd/10.2174/0115701808310599241003080546
/content/journals/lddd/10.2174/0115701808310599241003080546
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  • Article Type:     Research Article
Keyword(s): ADMET; anticancer agents; aurora kinase A; drug likeliness; Molecular docking; physicochemical parameters

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