Skip to content
2000
Volume 21, Issue 1
  • ISSN: 1573-4064
  • E-ISSN: 1875-6638

Abstract

Background

Chagas disease has an ineffective drug treatment despite efforts made over the last four decades. The carbonic anhydrase of (α-CA) has emerged as an interesting target for the design of new antiparasitic compounds due to its crucial role in parasite processes.

Objective

The aim in this study was identify potential α-CA inhibitors with trypanocidal activity.

Methods

A maximum common substructure (MCS) and molecular docking were used to carried out a ligand- and structure-based virtual screening of ZINC20 and MolPort databases. The compounds selected were evaluated in an model against the NINOA strain of and cytotoxicity was determined in a murine model of macrophage cells J774.2.

Results

Five sulfonamide derivatives (, , , , and ) had the highest docking scores (-6.94 to -8.31 kcal/mol). They showed key residue interactions on the active site of the α-CA and good biopharmaceutical and pharmacokinetic properties. , , and had half-maximal inhibitory concentration (IC) values of 26, 61.6, and 49 μM, respectively, against NINOA strain epimastigotes of .

Conclusion

Compounds , and showed trypanocidal activity; therefore, these results encourage the development of new trypanocidal agents based in their scaffold.

Loading

Article metrics loading...

/content/journals/mc/10.2174/0115734064310458240719071823
2024-07-30
2024-12-28
Loading full text...

Full text loading...

References

  1. RodriguesG.C. FeijóD.F. BozzaM.T. PanP. VulloD. ParkkilaS. SupuranC.T. CapassoC. AguiarA.P. VermelhoA.B. Design, synthesis, and evaluation of hydroxamic acid derivatives as promising agents for the management of Chagas disease.J. Med. Chem.201457229830810.1021/jm400902y24299463
    [Google Scholar]
  2. EchavarríaN.G. EcheverríaL.E. StewartM. GallegoC. SaldarriagaC. Chagas disease: Chronic chagas cardiomyopathy.Curr. Probl. Cardiol.202146310050710.1016/j.cpcardiol.2019.10050731983471
    [Google Scholar]
  3. NTD. World Health Organization. Available from: https://www.who.int/ (accessed Feb 23, 2022).
  4. Güzel-AkdemirÖ. AkdemirA. PanP. VermelhoA.B. ParkkilaS. ScozzafavaA. CapassoC. SupuranC.T. A class of sulfonamides with strong inhibitory action against the α-carbonic anhydrase from Trypanosoma cruzi.J. Med. Chem.201356145773578110.1021/jm400418p23815159
    [Google Scholar]
  5. CamposM.C.O. LeonL.L. TaylorM.C. KellyJ.M. Benznidazole-resistance in Trypanosoma cruzi: Evidence that distinct mechanisms can act in concert.Mol. Biochem. Parasitol.20141931171910.1016/j.molbiopara.2014.01.00224462750
    [Google Scholar]
  6. WilkinsonS.R. TaylorM.C. HornD. KellyJ.M. CheesemanI. A mechanism for cross-resistance to nifurtimox and benznidazole in trypanosomes.Proc. Natl. Acad. Sci. USA2008105135022502710.1073/pnas.071101410518367671
    [Google Scholar]
  7. MejiaA.M. HallB.S. TaylorM.C. Gómez-PalacioA. WilkinsonS.R. Triana-ChávezO. KellyJ.M. Benznidazole-resistance in Trypanosoma cruzi is a readily acquired trait that can arise independently in a single population.J. Infect. Dis.2012206222022810.1093/infdis/jis33122551809
    [Google Scholar]
  8. RibeiroV. DiasN. PaivaT. Hagström-BexL. NitzN. PratesiR. HechtM. Current trends in the pharmacological management of Chagas disease.Int. J. Parasitol. Drugs Drug Resist.20201271710.1016/j.ijpddr.2019.11.00431862616
    [Google Scholar]
  9. Vázquez-JiménezL.K. Paz-GonzálezA.D. Juárez-SaldivarA. UhrigM.L. AgustiR. Reyes-ArellanoA. Nogueda-TorresB. RiveraG. Structure-based virtual screening of new benzoic acid derivatives as trypanosoma cruzi trans-sialidase inhibitors.Med. Chem.202117772473110.2174/157340641666620050608461132370720
    [Google Scholar]
  10. Lara-RamirezE.E. López-CedilloJ.C. Nogueda-TorresB. KashifM. Garcia-PerezC. Bocanegra-GarciaV. AgustiR. UhrigM.L. RiveraG. An in vitro and in vivo evaluation of new potential trans -sialidase inhibitors of Trypanosoma cruzi predicted by a computational drug repositioning method.Eur. J. Med. Chem.201713224926110.1016/j.ejmech.2017.03.06328364659
    [Google Scholar]
  11. VázquezK. PaulinoM. SalasC.O. Zarate-RamosJ.J. VeraB. RiveraG. Trypanothione reductase: A target for the development of anti- trypanosoma cruzi drugs.Mini Rev. Med. Chem.2017171193994628302040
    [Google Scholar]
  12. Espinosa-BustosC. Ortiz PérezM. Gonzalez-GonzalezA. ZarateA.M. RiveraG. Belmont-DíazJ.A. SaavedraE. CuellarM.A. VázquezK. SalasC.O. New amino naphthoquinone derivatives as anti-Trypanosoma cruzi agents targeting trypanothione reductase.Pharmaceutics2022146112110.3390/pharmaceutics1406112135745694
    [Google Scholar]
  13. Vázquez-JiménezL.K. Juárez-SaldivarA. Gómez-EscobedoR. Delgado-MaldonadoT. Méndez-ÁlvarezD. PalosI. BandyopadhyayD. Gaona-LopezC. Ortiz-PérezE. Nogueda-TorresB. Ramírez-MorenoE. RiveraG. Ligand-based virtual screening and molecular docking of benzimidazoles as potential inhibitors of triosephosphate isomerase identified new trypanocidal agents.Int. J. Mol. Sci.202223171004710.3390/ijms23171004736077439
    [Google Scholar]
  14. Vázquez-JiménezL.K. Moreno-HerreraA. Juárez-SaldivarA. González-GonzálezA. Ortiz-PérezE. Paz-GonzálezA.D. Palos-PizarroI. Ramírez-MorenoE. RiveraG. Recent advances in the development of triose phosphate isomerase inhibitors as antiprotozoal agents.Curr. Med. Chem.202113827610.2174/092986732866621091309092834517794
    [Google Scholar]
  15. PalosI. Lara-RamirezE.E. Lopez-CedilloJ.C. Garcia-PerezC. KashifM. Bocanegra-GarciaV. Nogueda-TorresB. RiveraG. Repositioning FDA drugs as potential cruzain inhibitors from trypanosoma cruzi: virtual screening, in vitro and in vivo studies.Molecules2017226101510.3390/molecules2206101528629155
    [Google Scholar]
  16. Herrera-MayorgaV. Lara-RamírezE. Chacón-VargasK. Aguirre-AlvaradoC. Rodríguez-PáezL. Alcántara-FarfánV. Cordero-MartínezJ. Nogueda-TorresB. Reyes-EspinosaF. Bocanegra-GarcíaV. RiveraG. Structure-based virtual screening and in vitro evaluation of new Trypanosoma cruzi cruzain inhibitors.Int. J. Mol. Sci.2019207174210.3390/ijms2007174230970549
    [Google Scholar]
  17. PanP. VermelhoA.B. Capaci RodriguesG. ScozzafavaA. TolvanenM.E.E. ParkkilaS. CapassoC. SupuranC.T. Cloning, characterization, and sulfonamide and thiol inhibition studies of an α-carbonic anhydrase from Trypanosoma cruzi, the causative agent of Chagas disease.J. Med. Chem.20135641761177110.1021/jm400061623391336
    [Google Scholar]
  18. Beatriz VermelhoA. RodriguesG.C. NocentiniA. MansoldoF.R.P. SupuranC.T. Discovery of novel drugs for chagas disease: Is carbonic anhydrase a target for antiprotozoal drugs?Expert Opin. Drug Discov.202217101147115810.1080/17460441.2022.211729536039500
    [Google Scholar]
  19. SupuranC.T. Carbonic anhydrase inhibitors.Bioorg. Med. Chem. Lett.201020123467347410.1016/j.bmcl.2010.05.00920529676
    [Google Scholar]
  20. SupuranC.T. Carbonic anhydrases: Novel therapeutic applications for inhibitors and activators.Nat. Rev. Drug Discov.20087216818110.1038/nrd246718167490
    [Google Scholar]
  21. VermelhoA.B. CapaciG.R. RodriguesI.A. CardosoV.S. MazottoA.M. SupuranC.T. Carbonic anhydrases from Trypanosoma and Leishmania as anti-protozoan drug targets.Bioorg. Med. Chem.20172551543155510.1016/j.bmc.2017.01.03428161253
    [Google Scholar]
  22. NocentiniA. VulloD. BartolucciG. SupuranC.T. N-Nitrosulfonamides: A new chemotype for carbonic anhydrase inhibition.Bioorg. Med. Chem.201624163612361710.1016/j.bmc.2016.05.07227290692
    [Google Scholar]
  23. LlanosM.A. SbaragliniM.L. VillalbaM.L. RuizM.D. CarrilloC. Alba SotoC. TaleviA. AngeliA. ParkkilaS. SupuranC.T. GavernetL. A structure-based approach towards the identification of novel antichagasic compounds: Trypanosoma cruzi carbonic anhydrase inhibitors.J. Enzyme Inhib. Med. Chem.2020351213010.1080/14756366.2019.167763831619095
    [Google Scholar]
  24. VirtanenP. GommersR. OliphantT.E. HaberlandM. ReddyT. CournapeauD. BurovskiE. PetersonP. WeckesserW. BrightJ. van der WaltS.J. BrettM. WilsonJ. MillmanK.J. MayorovN. NelsonA.R.J. JonesE. KernR. LarsonE. CareyC.J. Polatİ. FengY. MooreE.W. VanderPlasJ. LaxaldeD. PerktoldJ. CimrmanR. HenriksenI. QuinteroE.A. HarrisC.R. ArchibaldA.M. RibeiroA.H. PedregosaF. van MulbregtP. VijaykumarA. BardelliA.P. RothbergA. HilbollA. KloecknerA. ScopatzA. LeeA. RokemA. WoodsC.N. FultonC. MassonC. HäggströmC. FitzgeraldC. NicholsonD.A. HagenD.R. PasechnikD.V. OlivettiE. MartinE. WieserE. SilvaF. LendersF. WilhelmF. YoungG. PriceG.A. In-goldG-L. AllenG.E. LeeG.R. AudrenH. ProbstI. DietrichJ.P. SilterraJ. WebberJ.T. SlavičJ. NothmanJ. BuchnerJ. KulickJ. SchönbergerJ.L.; de Miranda Cardoso, J.V.; Reimer, J.; Harrington, J.; Rodríguez, J.L.C.; Nunez-Iglesias, J.; Kuczynski, J.; Tritz, K.; Thoma, M.; Newville, M.; Kümmerer, M.; Bolingbroke, M.; Tartre, M.; Pak, M.; Smith, N.J.; Nowaczyk, N.; Shebanov, N.; Pavlyk, O.; Brodtkorb, P.A.; Lee, P.; McGibbon, R.T.; Feldbauer, R.; Lewis, S.; Tygier, S.; Sievert, S.; Vigna, S.; Peterson, S.; More, S.; Pudlik, T.; Oshima, T.; Pingel, T.J.; Robitaille, T.P.; Spura, T.; Jones, T.R.; Cera, T.; Leslie, T.; Zito, T.; Krauss, T.; Upadhyay, U.; Halchenko, Y.O.; Vázquez-Baeza, Y. SciPy 1.0: Fundamental algorithms for scientific computing in Python.Nat. Methods202017326127210.1038/s41592‑019‑0686‑232015543
    [Google Scholar]
  25. WaskomM. Seaborn: Statistical data visualization.J. Open Source Softw.2021660302110.21105/joss.03021
    [Google Scholar]
  26. IrwinJ.J. TangK.G. YoungJ. DandarchuluunC. WongB.R. KhurelbaatarM. MorozY.S. MayfieldJ. SayleR.A. ZINC20—A free ultralarge-scale chemical database for ligand discovery.J. Chem. Inf. Model.202060126065607310.1021/acs.jcim.0c0067533118813
    [Google Scholar]
  27. MolPort. Available from: https://www.molport.com/shop/index(accessed Aug 16, 2021).
  28. O’BoyleN.M. BanckM. JamesC.A. MorleyC. VandermeerschT. HutchisonG.R. Open Babel: An open chemical toolbox.J. Cheminform.2011313310.1186/1758‑2946‑3‑3321982300
    [Google Scholar]
  29. WaterhouseA. BertoniM. BienertS. StuderG. TaurielloG. GumiennyR. HeerF.T. de BeerT.A.P. RempferC. BordoliL. LeporeR. SchwedeT. SWISS-MODEL: Homology modelling of protein structures and complexes.Nucleic Acids Res.201846W1W296W30310.1093/nar/gky42729788355
    [Google Scholar]
  30. KimD.E. ChivianD. BakerD. Protein structure prediction and analysis using the Robetta server.Nucleic Acids Res.200432Web Server)(Suppl. 2W526W53110.1093/nar/gkh46815215442
    [Google Scholar]
  31. WebbB. SaliA. Comparative protein structure modeling using MODELLER.Curr. Protoc. Bioinformatics20165416.13710.1002/cpbi.327322406
    [Google Scholar]
  32. EswarN. EramianD. WebbB. ShenM-Y. SaliA. Protein structure modeling with MODELLER.Structural Proteomics. Methods in Molecular Biology™Humana Press2008426145159
    [Google Scholar]
  33. KällbergM. MargaryanG. WangS. MaJ. XuJ. RaptorX server: A resource for template-based protein structure modeling.Protein Structure PredictionHumana Press: New York, NY201411371727
    [Google Scholar]
  34. VaradiM. AnyangoS. DeshpandeM. NairS. NatassiaC. YordanovaG. YuanD. StroeO. WoodG. LaydonA. ŽídekA. GreenT. TunyasuvunakoolK. PetersenS. JumperJ. ClancyE. GreenR. VoraA. LutfiM. FigurnovM. CowieA. HobbsN. KohliP. KleywegtG. BirneyE. HassabisD. VelankarS. Alphafold protein structure database: Massively expanding the structural coverage of protein-sequence space with high-accuracy models.Nucleic Acids Res.202250D1D439D44410.1093/nar/gkab106134791371
    [Google Scholar]
  35. JumperJ. EvansR. PritzelA. GreenT. FigurnovM. RonnebergerO. TunyasuvunakoolK. BatesR. ŽídekA. PotapenkoA. BridglandA. MeyerC. KohlS.A.A. BallardA.J. CowieA. Romera-ParedesB. NikolovS. JainR. AdlerJ. BackT. PetersenS. ReimanD. ClancyE. ZielinskiM. SteineggerM. PacholskaM. BerghammerT. BodensteinS. SilverD. VinyalsO. SeniorA.W. KavukcuogluK. KohliP. HassabisD. Highly accurate protein structure prediction with AlphaFold.Nature2021596787358358910.1038/s41586‑021‑03819‑234265844
    [Google Scholar]
  36. BisongE. BisongE. Building machine learning and deep learning models on google cloud platform: A comprehensive guide for beginners.1st edSpringerLink20195964
    [Google Scholar]
  37. DeLanoW.L. Pymol: An open-source molecular graphics tool. CCP4 Newsl.Protein Crystallogr20024018292
    [Google Scholar]
  38. YuanS. ChanH.C.S. HuZ. Using PYMOL as a platform for computational drug design.Wiley Interdiscip. Rev. Comput. Mol. Sci.201772e129810.1002/wcms.1298
    [Google Scholar]
  39. McNuttA.T. FrancoeurP. AggarwalR. MasudaT. MeliR. RagozaM. SunseriJ. KoesD.R. GNINA 1.0: Molecular docking with deep learning.J. Cheminform.20211314310.1186/s13321‑021‑00522‑234108002
    [Google Scholar]
  40. AdasmeM.F. LinnemannK.L. BolzS.N. KaiserF. SalentinS. HauptV.J. SchroederM. PLIP 2021: Expanding the scope of the protein–ligand interaction profiler to DNA and RNA.Nucleic Acids Res.202149W1W530W53410.1093/nar/gkab29433950214
    [Google Scholar]
  41. SupuranC.T. Inhibition of carbonic anhydrase from Trypanosoma cruzi for the management of Chagas disease: An underexplored therapeutic opportunity.Future Med. Chem.20168331132410.4155/fmc.15.18526898220
    [Google Scholar]
  42. DainaA. MichielinO. ZoeteV. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.Sci. Rep.20162017711310.1038/srep4271728256516
    [Google Scholar]
  43. XiongG. WuZ. YiJ. FuL. YangZ. HsiehC. YinM. ZengX. WuC. LuA. ChenX. HouT. CaoD. ADMETlab 2.0: An integrated online platform for accurate and comprehensive predictions of ADMET properties.Nucleic Acids Res.202149W1W5W1410.1093/nar/gkab25533893803
    [Google Scholar]
  44. Domínguez-DíazL.R. Eugenia OchoaM. Soto-CastroD. FarfánN. Morales-ChamorroM. Yépez-MuliaL. Pérez-CamposE. SantillanR. Moreno-RodríguezA. In vitro, ex vivo and in vivo short-term screening of DHEA nitrate derivatives activity over Trypanosoma cruzi Ninoa and TH strains from Oaxaca State, México.Bioorg. Med. Chem.20214811641710.1016/j.bmc.2021.11641734571489
    [Google Scholar]
  45. LipinskiC.A. LombardoF. DominyB.W. FeeneyP.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.Adv. Drug Deliv. Rev.20126441710.1016/j.addr.2012.09.01911259830
    [Google Scholar]
  46. KrissinelE. HenrickK. Multiple alignment of protein structures in three dimensions. International Symposium on Computational Life ScienceSpringerBerlin, Heidelberg, September 2005677810.1007/11560500_7
    [Google Scholar]
  47. GouyM. GuindonS. GascuelO. SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building.Mol. Biol. Evol.201027222122410.1093/molbev/msp25919854763
    [Google Scholar]
  48. CoimbraJ.R.M. BaptistaS.J. DinisT.C.P. SilvaM.M.C. MoreiraP.I. SantosA.E. SalvadorJ.A.R. Combining virtual screening protocol and in vitro evaluation towards the discovery of BACE1 inhibitors.Biomolecules202010453510.3390/biom1004053532244832
    [Google Scholar]
  49. StuderG. RempferC. WaterhouseA.M. GumiennyR. HaasJ. SchwedeT. QMEANDisCo—distance constraints applied on model quality estimation.Bioinformatics20203661765177110.1093/bioinformatics/btz82831697312
    [Google Scholar]
  50. PanP. VermelhoA.B. ScozzafavaA. ParkkilaS. CapassoC. SupuranC.T. Anion inhibition studies of the α-carbonic anhydrase from the protozoan pathogen Trypanosoma cruzi, the causative agent of Chagas disease.Bioorg. Med. Chem.201321154472447610.1016/j.bmc.2013.05.05823790722
    [Google Scholar]
  51. De Fuentes-VicenteJ.A. Vidal-LópezD.G. Flores-VillegasA.L. Moreno-RodríguezA. De Alba-AlvaradoM.C. Salazar-Schettino, P.M.; Rodríguez-López, M.H.; Gutiérrez-Cabrera, A.E. Trypanosoma cruzi: A review of biological and methodological factors in Mexican strains.Acta Trop.2019195April515710.1016/j.actatropica.2019.04.02431022383
    [Google Scholar]
  52. AmbudkarS.V. Kimchi-SarfatyC. SaunaZ.E. GottesmanM.M. P-glycoprotein: From genomics to mechanism.Oncogene200322477468748510.1038/sj.onc.120694814576852
    [Google Scholar]
  53. OrrS.T.M. RippS.L. BallardT.E. HendersonJ.L. ScottD.O. ObachR.S. SunH. KalgutkarA.S. Mechanism-based inactivation (MBI) of cytochrome P450 enzymes: Structure-activity relationships and discovery strategies to mitigate drug-drug interaction risks.J. Med. Chem.201255114896493310.1021/jm300065h22409598
    [Google Scholar]
  54. CollierD.J. WolffC.B. HedgesA.M. NathanJ. FlowerR.J. MilledgeJ.S. SwensonE.R. Benzolamide improves oxygenation and reduces acute mountain sickness during a high‐altitude trek and has fewer side effects than acetazolamide at sea level.Pharmacol. Res. Perspect.201643e0020310.1002/prp2.20327433337
    [Google Scholar]
  55. VulloD. Del PreteS. FisherG.M. AndrewsK.T. PoulsenS.A. CapassoC. SupuranC.T. Sulfonamide inhibition studies of the η-class carbonic anhydrase from the malaria pathogen Plasmodium falciparum.Bioorg. Med. Chem.201523352653110.1016/j.bmc.2014.12.00925533402
    [Google Scholar]
  56. AngeliA. CartaF. NocentiniA. WinumJ.Y. ZalubovskisR. AkdemirA. OnnisV. EldehnaW.M. CapassoC. SimoneG.D. MontiS.M. CarradoriS. DonaldW.A. DedharS. SupuranC.T. Carbonic anhydrase inhibitors targeting metabolism and tumor microenvironment.Metabolites2020101041210.3390/metabo1010041233066524
    [Google Scholar]
  57. NishimoriI. VulloD. InnocentiA. ScozzafavaA. MastrolorenzoA. SupuranC.T. Carbonic anhydrase inhibitors: Inhibition of the transmembrane isozyme XIV with sulfonamides.Bioorg. Med. Chem. Lett.200515173828383310.1016/j.bmcl.2005.06.05516039848
    [Google Scholar]
  58. PreteS.D. VulloD. OsmanS.M. ScozzafavaA. AlO-thmanZ. CapassoC. SupuranC.T. Sulfonamide inhibition study of the carbonic anhydrases from the bacterial pathogen Porphyromonas gingivalis: The β-class (PgiCAb) versus the γ-class (PgiCA) enzymes.Bioorg. Med. Chem.201422174537454310.1016/j.bmc.2014.07.04825129169
    [Google Scholar]
  59. SyrjänenL. KuuslahtiM. TolvanenM. VulloD. ParkkilaS. SupuranC.T. The β-carbonic anhydrase from the malaria mosquito Anopheles gambiae is highly inhibited by sulfonamides.Bioorg. Med. Chem.201523102303230910.1016/j.bmc.2015.03.08125882523
    [Google Scholar]
  60. VulloD. BhattA. MahonB.P. McKennaR. SupuranC.T. Sulfonamide inhibition studies of the α-carbonic anhydrase from the gammaproteobacterium Thiomicrospira crunogena XCL-2, TcruCA.Bioorg. Med. Chem. Lett.201626240140510.1016/j.bmcl.2015.11.10426691758
    [Google Scholar]
  61. VelaA. Coral-AlmeidaM. SerenoD. CostalesJ.A. BarnabéC. BrenièreS.F. In vitro susceptibility of Trypanosoma cruzi discrete typing units (DTUs) to benznidazole: A systematic review and meta-analysis.PLoS Negl. Trop. Dis.2021153e000926910.1371/journal.pntd.000926933750958
    [Google Scholar]
  62. TahghighiA. BabaloueiF. Thiadiazoles: The appropriate pharmacological scaffolds with leishmanicidal and antimalarial activities: A review.Iran. J. Basic Med. Sci.201720661362228868117
    [Google Scholar]
/content/journals/mc/10.2174/0115734064310458240719071823
Loading
/content/journals/mc/10.2174/0115734064310458240719071823
Loading

Data & Media loading...

Supplements

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

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