Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry - Anti-Cancer Agents)
  4. Volume 25, Issue 3
  5. Article
Volume 25, Issue 3
  • ISSN: 1871-5206
  • E-ISSN: 1875-5992

Abstract

Introduction

Programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) are critical immune checkpoints in cancer biology. Multiple small-molecule drugs have been developed as inhibitors of the PD-1/PD-L1 axis. Those drugs promote the formation of PD-L1 homodimers, causing their stabilization, internalization, and subsequent degradation. Drug repurposing is a strategy that expedites the clinical translation by identifying new effects of drugs with clinical use. Herein, we aimed to repurpose drugs as inductors of PD-L1 homodimerization and, therefore, as potential inhibitors of PD-L1.

Methods

We generated a hybrid pharmacophore model by analyzing the structures of reported ligands that induce PD-L1 homodimerization and their target-binding mode. Pharmacophore-matching compounds were selected from a chemical library of Food and Drug Administration (FDA)-approved drugs. Their binding modes to PD-L1 homodimers were assessed by molecular docking and the stability of the complexes and the corresponding binding energies were evaluated by molecular dynamics (MD) simulations. Finally, the activity of one drug as promoter of PD-L1 homodimerization was assessed in protein crosslinking assays.

Results

We identified 12 pharmacophore-matching compounds, but only 4 reproduced the binding mode of the reference inhibitors. Further characterization by MD showed that pranlukast, an antagonist of leukotriene receptors that is used to treat asthma, generated stable and energy-favorable interactions with PD-L1 homodimers and induced homodimerization of recombinant PD-L1.

Conclusion

Our results suggest that pranlukast inhibits the PD-1/PD-L1 axis, meriting its repurposing as an antitumor drug.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/acamc/10.2174/0118715206303675241009104647
2024-10-14
2025-01-18

  • From This Site

    /content/journals/acamc/10.2174/0118715206303675241009104647
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Labani-MotlaghA. Ashja-MahdaviM. LoskogA. The tumor microenvironment: A milieu hindering and obstructing antitumor immune responses.Front. Immunol.20201194010.3389/fimmu.2020.00940 32499786
     [Google Scholar]
  2. SunX. WuB. ChiangH.C. DengH. ZhangX. XiongW. LiuJ. RozeboomA.M. HarrisB.T. BlommaertE. GomezA. GarciaR.E. ZhouY. MitraP. PrevostM. ZhangD. BanikD. IsaacsC. BerryD. LaiC. ChaldekasK. LathamP.S. BrantnerC.A. PopratiloffA. JinV.X. ZhangN. HuY. PujanaM.A. CurielT.J. AnZ. LiR. Tumour DDR1 promotes collagen fibre alignment to instigate immune exclusion.Nature2021599788667367810.1038/s41586‑021‑04057‑2 34732895
     [Google Scholar]
  3. ChaJ.H. ChanL.C. LiC.W. HsuJ.L. HungM.C. Mechanisms controlling PD-L1 expression in cancer.Mol. Cell201976335937010.1016/j.molcel.2019.09.030 31668929
     [Google Scholar]
  4. Córdova-BahenaL. Velasco-VelázquezM.A. Anti-PD-1 and Anti-PD-L1 antibodies as immunotherapy against cancer: A structural perspective.Rev. Invest. Clin.202173100801610.24875/RIC.20000341 33079077
     [Google Scholar]
  5. TwomeyJ.D. ZhangB. Cancer immunotherapy update: FDA-approved checkpoint inhibitors and companion diagnostics.AAPS J.20212323910.1208/s12248‑021‑00574‑0 33677681
     [Google Scholar]
  6. BadieeP. MaritzM.F. DmochowskaN. CheahE. ThierryB. Intratumoral Anti-PD-1 nanoformulation improves its biodistribution.ACS Appl. Mater. Interfaces20221414158811589310.1021/acsami.1c22479 35357803
     [Google Scholar]
  7. BaxiS. YangA. GennarelliR.L. KhanN. WangZ. BoyceL. KorensteinD. Immune-related adverse events for anti-PD-1 and anti-PD-L1 drugs: systematic review and meta-analysis.BMJ2018360k79310.1136/bmj.k793 29540345
     [Google Scholar]
  8. Datta-MannanA. EstwickS. ZhouC. ChoiH. DouglassN.E. WitcherD.R. LuJ. BeidlerC. MillicanR. Influence of physiochemical properties on the subcutaneous absorption and bioavailability of monoclonal antibodies.MAbs2020121177002810.1080/19420862.2020.1770028 32486889
     [Google Scholar]
  9. NaidooJ. PageD.B. LiB.T. ConnellL.C. SchindlerK. LacoutureM.E. PostowM.A. WolchokJ.D. Toxicities of the anti-PD-1 and anti-PD-L1 immune checkpoint antibodies.Ann. Oncol.201526122375239110.1093/annonc/mdv383 26371282
     [Google Scholar]
  10. RibasA. WolchokJ.D. Cancer immunotherapy using checkpoint blockade.Science201835963821350135510.1126/science.aar4060 29567705
     [Google Scholar]
  11. AiL. ChenJ. YanH. HeQ. LuoP. XuZ. YangX. Research status and outlook of PD-1/PD-L1 inhibitors for cancer therapy.Drug Des. Devel. Ther.2020143625364910.2147/DDDT.S267433 32982171
     [Google Scholar]
  12. GuzikK. TomalaM. MuszakD. KoniecznyM. HecA. BłaszkiewiczU. PustułaM. ButeraR. DömlingA. HolakT.A. Development of the inhibitors that target the PD-1/PD-L1 interaction—A brief look at progress on small molecules, peptides and macrocycles.Molecules20192411207110.3390/molecules24112071 31151293
     [Google Scholar]
  13. LiuC. ZhouF. YanZ. ShenL. ZhangX. HeF. WangH. LuX. YuK. ZhaoY. ZhuD. Discovery of a novel, potent and selective small‐molecule inhibitor of PD‐1/PD‐L1 interaction with robust in vivo anti‐tumour efficacy.Br. J. Pharmacol.2021178132651267010.1111/bph.15457 33768523
     [Google Scholar]
  14. KoblishH.K. WuL. WangL.C.S. LiuP.C.C. WynnR. Rios-DoriaJ. SpitzS. LiuH. VolginaA. ZolotarjovaN. KapilashramiK. BehshadE. CovingtonM. YangY. LiJ. DiamondS. SolovievM. O’HayerK. RubinS. KanellopoulouC. YangG. RuparM. DiMatteoD. LinL. StevensC. ZhangY. ThekkatP. GeschwindtR. MarandoC. YeleswaramS. JacksonJ. ScherleP. HuberR. YaoW. HollisG. Characterization of INCB086550: A potent and novel small-molecule PD-L1 inhibitor.Cancer Discov.20221261482149910.1158/2159‑8290.CD‑21‑1156 35254416
     [Google Scholar]
  15. WangT. CaiS. ChengY. ZhangW. WangM. SunH. GuoB. LiZ. XiaoY. JiangS. Discovery of small-molecule inhibitors of the PD-1/PD-L1 axis that promote PD-L1 internalization and degradation.J. Med. Chem.20226553879389310.1021/acs.jmedchem.1c01682 35188766
     [Google Scholar]
  16. LiuL. ZhangH. HouJ. ZhangY. WangL. WangS. YaoZ. XieT. WenX. XuQ. DaiL. FengZ. ZhangP. WuY. SunH. LiuJ. YuanH. Discovery of novel PD-L1 small-molecular inhibitors with potent in vivo anti-tumor immune activity.J. Med. Chem.20246764977499710.1021/acs.jmedchem.4c00102 38465588
     [Google Scholar]
  17. ParkJ.J. ThiE.P. CarpioV.H. BiY. ColeA.G. DorseyB.D. FanK. HarasymT. IottC.L. KadhimS. KimJ.H. LeeA.C.H. NguyenD. ParatalaB.S. QiuR. WhiteA. LakshminarasimhanD. LeoC. SutoR.K. RijnbrandR. TangS. SofiaM.J. MooreC.B. Checkpoint inhibition through small molecule-induced internalization of programmed death-ligand 1.Nat. Commun.2021121122210.1038/s41467‑021‑21410‑1 33619272
     [Google Scholar]
  18. LaiF. JiM. HuangL. WangY. XueN. DuT. DongK. YaoX. JinJ. FengZ. ChenX. YPD-30, a prodrug of YPD-29B, is an oral small-molecule inhibitor targeting PD-L1 for the treatment of human cancer.Acta Pharm. Sin. B20221262845285810.1016/j.apsb.2022.02.031 35755282
     [Google Scholar]
  19. WangK. ZhangX. ChengY. QiZ. YeK. ZhangK. JiangS. LiuY. XiaoY. WangT. Discovery of novel PD-L1 inhibitors that induce the dimerization, internalization, and degradation of PD-L1 based on the fragment coupling strategy.J. Med. Chem.20236624168071682710.1021/acs.jmedchem.3c01534 38109261
     [Google Scholar]
  20. BaillyC. VergotenG. Protein homodimer sequestration with small molecules: Focus on PD-L1.Biochem. Pharmacol.202017411382110.1016/j.bcp.2020.113821 31972166
     [Google Scholar]
  21. VerduraS. CuyàsE. CortadaE. BrunetJ. Lopez-BonetE. Martin-CastilloB. Bosch-BarreraJ. EncinarJ.A. MenendezJ.A. Resveratrol targets PD-L1 glycosylation and dimerization to enhance antitumor T-cell immunity.Aging (Albany NY)202012183410.18632/aging.102646 31901900
     [Google Scholar]
  22. ChenT. LiQ. LiuZ. ChenY. FengF. SunH. Peptide-based and small synthetic molecule inhibitors on PD-1/PD-L1 pathway: A new choice for immunotherapy?Eur. J. Med. Chem.201916137839810.1016/j.ejmech.2018.10.044 30384043
     [Google Scholar]
  23. ZakK.M. GrudnikP. GuzikK. ZiebaB.J. MusielakB. DömlingA. DubinG. HolakT.A. Structural basis for small molecule targeting of the programmed death ligand 1 (PD-L1).Oncotarget2016721303233033510.18632/oncotarget.8730 27083005
     [Google Scholar]
  24. YamaguchiH. HsuJ.M. YangW.H. HungM.C. Mechanisms regulating PD-L1 expression in cancers and associated opportunities for novel small-molecule therapeutics.Nat. Rev. Clin. Oncol.202219528730510.1038/s41571‑022‑00601‑9 35132224
     [Google Scholar]
  25. YangJ. HuL. Immunomodulators targeting the PD‐1/PD‐L1 protein‐protein interaction: From antibodies to small molecules.Med. Res. Rev.201939126530110.1002/med.21530 30215856
     [Google Scholar]
  26. PushpakomS. IorioF. EyersP.A. EscottK.J. HopperS. WellsA. DoigA. GuilliamsT. LatimerJ. McNameeC. NorrisA. SanseauP. CavallaD. PirmohamedM. Drug repurposing: progress, challenges and recommendations.Nat. Rev. Drug Discov.2019181415810.1038/nrd.2018.168 30310233
     [Google Scholar]
  27. JaradaT.N. RokneJ.G. AlhajjR. A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions.J. Cheminform.20201214610.1186/s13321‑020‑00450‑7 33431024
     [Google Scholar]
  28. GuzikK. ZakK.M. GrudnikP. MagieraK. MusielakB. TörnerR. SkalniakL. DömlingA. DubinG. HolakT.A. Small-molecule inhibitors of the programmed cell death-1/programmed death-ligand 1 (PD-1/PD-L1) interaction via transiently induced protein states and dimerization of PD-L1.J. Med. Chem.201760135857586710.1021/acs.jmedchem.7b00293 28613862
     [Google Scholar]
  29. PerryE. MillsJ.J. ZhaoB. WangF. SunQ. ChristovP.P. TarrJ.C. RietzT.A. OlejniczakE.T. LeeT. FesikS. Fragment-based screening of programmed death ligand 1 (PD-L1).Bioorg. Med. Chem. Lett.201929678679010.1016/j.bmcl.2019.01.028 30728114
     [Google Scholar]
  30. ChupakL.S. ZhengX. Compounds useful as immunomodulators.WO2015034820A12015
  31. FengZ. ChenX. ZhangL. YangY. LaiF. JiM. ZhouC. ZhangL. WangK. Preparation method therefor, and pharmaceutical composition and uses thereof.U.S. Patent No. 10,941,1292021
  32. WhiteK.A. Grillo-HillB.K. BarberD.L. Cancer cell behaviors mediated by dysregulated pH dynamics at a glance.J. Cell Sci.2017130466366910.1242/jcs.195297 28202602
     [Google Scholar]
  33. ThomsenR. ChristensenM.H. MolDock: a new technique for high-accuracy molecular docking.J. Med. Chem.200649113315332110.1021/jm051197e 16722650
     [Google Scholar]
  34. AbrahamM.J. MurtolaT. SchulzR. PállS. SmithJ.C. HessB. LindahlE. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers.SoftwareX20151-2192510.1016/j.softx.2015.06.001
     [Google Scholar]
  35. HuangJ. RauscherS. NawrockiG. RanT. FeigM. De GrootB.L. GrubmüllerH. MacKerellA.D.Jr CHARMM36m: an improved force field for folded and intrinsically disordered proteins.Nat. Methods2017141717310.1038/nmeth.4067 27819658
     [Google Scholar]
  36. SalentinS. SchreiberS. HauptV.J. AdasmeM.F. SchroederM. PLIP: fully automated protein–ligand interaction profiler.Nucleic Acids Res.201543W1W443W44710.1093/nar/gkv315 25873628
     [Google Scholar]
  37. HumphreyW. DalkeA. SchultenK. VMD: Visual molecular dynamics.J. Mol. Graph.199614133-38, 27-28.10.1016/0263‑7855(96)00018‑5 8744570
     [Google Scholar]
  38. SunseriJ. KoesD.R. Pharmit: interactive exploration of chemical space.Nucleic Acids Res.201644W1W442W44810.1093/nar/gkw287 27095195
     [Google Scholar]
  39. KumariR. KumarR. LynnA. g_mmpbsa--a GROMACS tool for high-throughput MM-PBSA calculations.J. Chem. Inf. Model.20145471951196210.1021/ci500020m 24850022
     [Google Scholar]
  40. LungJ. HungM.S. LinY.C. HungC.H. ChenC.C. LeeK.D. TsaiY. Virtual screening and in vitro evaluation of PD-L1 dimer stabilizers for uncoupling PD-1/PD-L1 interaction from natural products.Molecules20202522529310.3390/molecules25225293 33202823
     [Google Scholar]
  41. StaelS. MillerL.P. Fernández-FernándezÁ.D. Van BreusegemF. Detection of damage-activated metacaspase activity activities by western blot in plants. Plant Proteases and Plant Cell Death: Methods and Protocols; Klemenčič, M.; Stael, S. HuesgenP.F. New York, NYSpringer US202212713710.1007/978‑1‑0716‑2079‑3_11
     [Google Scholar]
  42. FengZ. ChenX. YangY. ZhengY. LaiF. JiM. ZhouC. ZhangL. WangK. Nicotinyl alcohol ether derivative, preparation method therefor, and pharmaceutical composition and uses thereof.U.S. Patent No. 10,975,0492021
  43. BasuS. YangJ. XuB. Magiera-MularzK. SkalniakL. MusielakB. KholodovychV. HolakT.A. HuL. Design, synthesis, evaluation, and structural studies of C2-symmetric small molecule inhibitors of programmed cell death-1/programmed death-ligand 1 protein–protein interaction.J. Med. Chem.201962157250726310.1021/acs.jmedchem.9b00795 31298541
     [Google Scholar]
  44. ButeraR. WażyńskaM. Magiera-MularzK. PlewkaJ. MusielakB. SurmiakE. SalaD. KitelR. de BruynM. NijmanH.W. ElsingaP.H. HolakT.A. DömlingA. Design, synthesis, and biological evaluation of imidazopyridines as PD-1/PD-L1 antagonists.ACS Med. Chem. Lett.202112576877310.1021/acsmedchemlett.1c00033 34055224
     [Google Scholar]
  45. MuszakD. SurmiakE. PlewkaJ. Magiera-MularzK. Kocik-KrolJ. MusielakB. SalaD. KitelR. StecM. WeglarczykK. SiedlarM. DömlingA. SkalniakL. HolakT.A. Terphenyl-based small-molecule inhibitors of programmed cell death-1/programmed death-ligand 1 protein–protein interaction.J. Med. Chem.20216415116141163610.1021/acs.jmedchem.1c00957 34313116
     [Google Scholar]
  46. SkalniakL. ZakK.M. GuzikK. MagieraK. MusielakB. PachotaM. SzelazekB. KocikJ. GrudnikP. TomalaM. KrzanikS. PyrcK. DömlingA. DubinG. HolakT.A. Small-molecule inhibitors of PD-1/PD-L1 immune checkpoint alleviate the PD-L1-induced exhaustion of T-cells.Oncotarget2017842721677218110.18632/oncotarget.20050 29069777
     [Google Scholar]
  47. ShaabaniS. HuizingaH.P.S. ButeraR. KouchiA. GuzikK. Magiera-MularzK. HolakT.A. DömlingA. A patent review on PD-1/PD-L1 antagonists: small molecules, peptides, and macrocycles (2015-2018).Expert Opin. Ther. Pat.201828966567810.1080/13543776.2018.1512706 30107136
     [Google Scholar]
  48. FanJ. FuA. ZhangL. Progress in molecular docking.Quant. Biol.201972838910.1007/s40484‑019‑0172‑y
     [Google Scholar]
  49. Van der SpoelD. ZhangJ. ZhangH. Quantitative predictions from molecular simulations using explicit or implicit interactions.Wiley Interdiscip. Rev. Comput. Mol. Sci.2022121e156010.1002/wcms.1560
     [Google Scholar]
  50. StanzioneF. GiangrecoI. ColeJ.C. Chapter four - use of molecular docking computational tools in drug discovery.Progress in Medicinal Chemistry. WittyD.R. CoxB. Elsevier2021Vol. 60273343
     [Google Scholar]
  51. BenderB.J. GahbauerS. LuttensA. LyuJ. WebbC.M. SteinR.M. FinkE.A. BaliusT.E. CarlssonJ. IrwinJ.J. ShoichetB.K. A practical guide to large-scale docking.Nat. Protoc.202116104799483210.1038/s41596‑021‑00597‑z 34561691
     [Google Scholar]
  52. MittalL. TonkR.K. AwasthiA. AsthanaS. Targeting cryptic-orthosteric site of PD-L1 for inhibitor identification using structure-guided approach.Arch. Biochem. Biophys.202171310905910.1016/j.abb.2021.109059 34673001
     [Google Scholar]
  53. HollingsworthS.A. DrorR.O. Molecular dynamics simulation for all.Neuron20189961129114310.1016/j.neuron.2018.08.011 30236283
     [Google Scholar]
  54. SinghS. Bani BakerQ. SinghD.B. Molecular docking and molecular dynamics simulation. Bioinformatics; Singh, D.B. PathakR.K. Academic Press202229130410.1016/B978‑0‑323‑89775‑4.00014‑6
     [Google Scholar]
  55. LazimR. SuhD. ChoiS. Advances in molecular dynamics simulations and enhanced sampling methods for the study of protein systems.Int. J. Mol. Sci.20202117633910.3390/ijms21176339 32882859
     [Google Scholar]
  56. BaillyC. VergotenG. N-glycosylation and ubiquitinylation of PD-L1 do not restrict interaction with BMS-202: A molecular modeling study.Comput. Biol. Chem.20208810736210.1016/j.compbiolchem.2020.107362 32871472
     [Google Scholar]
  57. SasmalP. BabasahibS. KumarB.R. RaghavendraN. Biphenyl-based small molecule inhibitors: Novel cancer immunotherapeutic agents targeting PD-1/PD-L1 interaction.Bioorg. Med. Chem.20227311700110.1016/j.bmc.2022.117001 36126447
     [Google Scholar]
  58. XiaW. HeL. BaoJ. QiY. ZhangJ.Z.H. Insights into small molecule inhibitor bindings to PD-L1 with residue-specific binding free energy calculation.J. Biomol. Struct. Dyn.20224022122771228510.1080/07391102.2021.1971558 34486939
     [Google Scholar]
  59. ZakK.M. KitelR. PrzetockaS. GolikP. GuzikK. MusielakB. DömlingA. DubinG. HolakT.A. Structure of the complex of human programmed death 1, PD-1, and its ligand PD-L1.Structure201523122341234810.1016/j.str.2015.09.010 26602187
     [Google Scholar]
  60. TyagiR. SinghA. ChaudharyK.K. YadavM.K. Pharmacophore modeling and its applications.Bioinformatics. SinghD.B. PathakR.K. Academic Press202226928910.1016/B978‑0‑323‑89775‑4.00009‑2
     [Google Scholar]
  61. GiordanoD. BiancanielloC. ArgenioM.A. FacchianoA. Drug design by pharmacophore and virtual screening approach.Pharm. (Basel)202215564610.3390/ph15050646 35631472
     [Google Scholar]
  62. LuoL. ZhongA. WangQ. ZhengT. Structure-based pharmacophore modeling, virtual screening, molecular docking, ADMET, and molecular dynamics (MD) simulation of potential inhibitors of PD-L1 from the library of marine natural products.Mar. Drugs20212012910.3390/md20010029 35049884
     [Google Scholar]
  63. MejíasC. GuirolaO. Pharmacophore model of immunocheckpoint protein PD-L1 by cosolvent molecular dynamics simulations.J. Mol. Graph. Model.20199110511110.1016/j.jmgm.2019.06.001 31202914
     [Google Scholar]
  64. ZhongY. LiX. YaoH. LinK. The characteristics of PD-L1 inhibitors, from peptides to small molecules.Molecules20192410194010.3390/molecules24101940 31137573
     [Google Scholar]
  65. AntoszczakM. MarkowskaA. MarkowskaJ. HuczyńskiA. Old wine in new bottles: Drug repurposing in oncology.Eur. J. Pharmacol.202086617278410.1016/j.ejphar.2019.172784 31730760
     [Google Scholar]
  66. ParvathaneniV. KulkarniN.S. MuthA. GuptaV. Drug repurposing: a promising tool to accelerate the drug discovery process.Drug Discov. Today201924102076208510.1016/j.drudis.2019.06.014 31238113
     [Google Scholar]
  67. AlhusbanA. Al-AzayzihA. GocA. GaoF. FaganS.C. SomanathP.R. Clinically relevant doses of candesartan inhibit growth of prostate tumor xenografts in vivo through modulation of tumor angiogenesis.J. Pharmacol. Exp. Ther.2014350363564510.1124/jpet.114.216382 24990940
     [Google Scholar]
  68. BellamkondaK. SatapathyS.R. DouglasD. ChandrashekarN. SelvanesanB.C. LiuM. SavariS. JonssonG. SjölanderA. Montelukast, a CysLT1 receptor antagonist, reduces colon cancer stemness and tumor burden in a mouse xenograft model of human colon cancer.Cancer Lett.2018437132410.1016/j.canlet.2018.08.019 30144515
     [Google Scholar]
  69. FanF. TianC. TaoL. WuH. LiuZ. ShenC. JiangG. LuY. Candesartan attenuates angiogenesis in hepatocellular carcinoma via downregulating AT1R/VEGF pathway.Biomed. Pharmacother.20168370471110.1016/j.biopha.2016.07.039 27470571
     [Google Scholar]
  70. GonçalvesJ.M. SilvaC.A.B. RiveroE.R.C. CordeiroM.M.R. Inhibition of cancer stem cells promoted by Pimozide.Clin. Exp. Pharmacol. Physiol.201946211612510.1111/1440‑1681.13049 30383889
     [Google Scholar]
  71. KachiK. KatoH. Naiki-ItoA. KomuraM. Nagano-MatsuoA. NaitohI. HayashiK. KataokaH. InagumaS. TakahashiS. Anti-allergic drug suppressed pancreatic carcinogenesis via down-regulation of cellular proliferation.Int. J. Mol. Sci.20212214744410.3390/ijms22147444 34299067
     [Google Scholar]
  72. KobaraH. FujiharaS. IwamaH. MatsuiT. FujimoriA. ChiyoT. TingtingS. KobayashiN. NishiyamaN. YachidaT. TadokoroT. OuraK. TaniJ. FujitaK. NomuraT. YoneyamaH. MorishitaA. OkanoK. SuzukiY. MoriH. MasakiT. Antihypertensive drug telmisartan inhibits cell proliferation of gastrointestinal stromal tumor cells in vitro.Mol. Med. Rep.20202221063107110.3892/mmr.2020.11144 32626983
     [Google Scholar]
  73. NozakiM. YoshikawaM. IshitaniK. KobayashiH. HoukinK. ImaiK. ItoY. MurakiT. Cysteinyl leukotriene receptor antagonists inhibit tumor metastasis by inhibiting capillary permeability.Keio J. Med.2010591101810.2302/kjm.59.10 20375653
     [Google Scholar]
  74. SuknunthaK. YubolphanR. KrueaprasertkulK. SrihirunS. SibmoohN. VivithanapornP. Leukotriene receptor antagonists inhibit mitogenic activity in triple negative breast cancer cells.Asian Pac. J. Cancer Prev.201819383383710.22034/APJCP.2018.19.3.833 29582642
     [Google Scholar]
  75. TabatabaiE. KhazaeiM. AsgharzadehF. NazariS.E. ShakourN. FiujiH. ZiaeemehrA. MostafapourA. ParizadehM.R. NouriM. HassanianS.M. HadizadehF. FernsG.A. RahmatiM. RahmaniF. AvanA. Inhibition of angiotensin II type 1 receptor by candesartan reduces tumor growth and ameliorates fibrosis in colorectal cancer.EXCLI J.20212086387810.17179/excli2021‑3421 34121975
     [Google Scholar]
  76. TangC. LeiH. ZhangJ. LiuM. JinJ. LuoH. XuH. WuY. Montelukast inhibits hypoxia inducible factor-1α translation in prostate cancer cells.Cancer Biol. Ther.201819871572110.1080/15384047.2018.1451279 29708817
     [Google Scholar]
  77. TsaiM.J. ChangW.A. TsaiP.H. WuC.Y. HoY.W. YenM.C. LinY.S. KuoP.L. HsuY.L. Montelukast induces apoptosis-inducing factor-mediated cell death of lung cancer cells.Int. J. Mol. Sci.2017187135310.3390/ijms18071353 28672809
     [Google Scholar]
  78. Velázquez-QuesadaI. Ruiz-MorenoA.J. Casique-AguirreD. Aguirre-AlvaradoC. Cortés-MendozaF. De la Fuente-GranadaM. García-PérezC. Pérez-TapiaS.M. González-ArenasA. Segura-CabreraA. Velasco-VelázquezM.A. Pranlukast antagonizes CD49f and reduces stemness in triple-negative breast cancer cells.Drug Des. Devel. Ther.2020141799181110.2147/DDDT.S247730 32494122
     [Google Scholar]
  79. ZovkoA. Yektaei-KarinE. SalamonD. NilssonA. WallvikJ. StenkeL. Montelukast, a cysteinyl leukotriene receptor antagonist, inhibits the growth of chronic myeloid leukemia cells through apoptosis.Oncol. Rep.201840290290810.3892/or.2018.6465 29845257
     [Google Scholar]
  80. KeamS.J. Lyseng-WilliamsonK.A. GoaK.L. Pranlukast.Drugs20036310991101910.2165/00003495‑200363100‑00005 12699401
     [Google Scholar]
  81. FigueroaE.E. KramerM. StrangeK. DentonJ.S. CysLT1 receptor antagonists pranlukast and zafirlukast inhibit LRRC8-mediated volume regulated anion channels independently of the receptor.Am. J. Physiol. Cell Physiol.20193174C857C86610.1152/ajpcell.00281.2019 31390227
     [Google Scholar]
  82. Montes-GrajalesD. Puerta-GuardoH. EspinosaD.A. HarrisE. Caicedo-TorresW. Olivero-VerbelJ. Martínez-RomeroE. In silico drug repurposing for the identification of potential candidate molecules against arboviruses infection.Antiviral Res.202017310466810.1016/j.antiviral.2019.104668 31786251
     [Google Scholar]
  83. MittendorfE.A. PhilipsA.V. Meric-BernstamF. QiaoN. WuY. HarringtonS. SuX. WangY. Gonzalez-AnguloA.M. AkcakanatA. ChawlaA. CurranM. HwuP. SharmaP. LittonJ.K. MolldremJ.J. AlatrashG. PD-L1 expression in triple-negative breast cancer.Cancer Immunol. Res.20142436137010.1158/2326‑6066.CIR‑13‑0127 24764583
     [Google Scholar]
  84. EhrtC. BrinkjostT. KochO. Impact of binding site comparisons on medicinal chemistry and rational molecular design.J. Med. Chem.20165994121415110.1021/acs.jmedchem.6b00078 27046190
     [Google Scholar]
  85. EhrtC. BrinkjostT. KochO. Binding site characterization – similarity, promiscuity, and druggability.MedChemComm20191071145115910.1039/C9MD00102F 31391887
     [Google Scholar]
  86. HauptV.J. DaminelliS. SchroederM. Drug promiscuity in PDB: Protein binding site similarity is key.PLoS One201386e6589410.1371/journal.pone.0065894 23805191
     [Google Scholar]
  87. LugininaA. GusachA. MarinE. MishinA. BrouilletteR. PopovP. ShiriaevaA. Besserer-OffroyÉ. LongpréJ.M. LyapinaE. IshchenkoA. PatelN. PolovinkinV. SafronovaN. BogorodskiyA. EdelweissE. HuH. WeierstallU. LiuW. BatyukA. GordeliyV. HanG.W. SarretP. KatritchV. BorshchevskiyV. CherezovV. Structure-based mechanism of cysteinyl leukotriene receptor inhibition by antiasthmatic drugs.Sci. Adv.2019510eaax251810.1126/sciadv.aax2518 31633023
     [Google Scholar]
  88. HofferL. MullerC. RocheP. MorelliX. Chemistry‐driven Hit‐to‐lead optimization guided by structure‐based approaches.Mol. Inform.2018379-10180005910.1002/minf.201800059 30051601
     [Google Scholar]
  89. MignaniS. RodriguesJ. TomasH. JalalR. SinghP.P. MajoralJ.P. VishwakarmaR.A. Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?Drug Discov. Today201823360561510.1016/j.drudis.2018.01.010 29330127
     [Google Scholar]
/content/journals/acamc/10.2174/0118715206303675241009104647
Loading
In silico-driven identification of Pranlukast as a Stabilizer of PD-L1 Homodimers
Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry - Anti-Cancer Agents) 25, 179 (2025); https://doi.org/10.2174/0118715206303675241009104647
/content/journals/acamc/10.2174/0118715206303675241009104647
/content/journals/acamc/10.2174/0118715206303675241009104647
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher's website along with the published article.

file format download Download

  • Article Type:     Research Article
Keyword(s): drug repurposing; Immune checkpoint; molecular dynamics; pharmacophore modeling; pranlukast; virtual screening

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test