Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Medicinal Chemistry
  4. Volume 31, Issue 38
  5. Article
Volume 31, Issue 38
  • ISSN: 0929-8673
  • E-ISSN: 1875-533X

Abstract

Malaria remains one of the most challenging tropical diseases. Since malaria cases are reportedly alarming in terms of infections and mortality, urgent attention is needed for addressing the issues of drug resistance in falciparum malaria. High throughput screening methods have paved way for rapid identification of anti-malarial. Furthermore, drug repurposing helps in shortening the time required for drug safety approvals. Hence, discovery of new antimalarials by drug repurposing is a promising approach for combating the disease. This article summarizes the recent computational approaches used for identifying novel antimalarials by using drug target interaction tools followed by pharmacokinetic studies.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cmc/10.2174/0929867331666230807151708
2023-09-25
2024-11-19

  • From This Site

    /content/journals/cmc/10.2174/0929867331666230807151708
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. BurchardG.D. Treatment of illnesses acquired during long-distance travel.Internist.201455911001107, 101210.1007/s00108‑014‑3546‑225070614
     [Google Scholar]
  2. WhiteN.J. Antimalarial drug resistance.J. Clin. Invest.200411381084109210.1172/JCI2168215085184
     [Google Scholar]
  3. World Health OrganizationWHO briefing on Malaria Treatment Guidelines and artemisinin monotherapies.GenevaWHO2006128
     [Google Scholar]
  4. HerlekarI. The resistance gene in malaria parasite identified.Curr. Sci.20141063345345
     [Google Scholar]
  5. BeareN.A. HardingS.P. LewallenS. MolyneuxM. TaylorT. Malarial retinopathy: A newly established diagnostic sign in severe malaria.Am. J. Trop. Med. Hyg.200675579079710.4269/ajtmh.2006.75.79017123967
     [Google Scholar]
  6. BartoloniA. ZammarchiL. Clinical aspects of uncomplicated and severe malaria.Mediterr. J. Hematol. Infect. Dis.201241e201202610.4084/mjhid.2012.02622708041
     [Google Scholar]
  7. Schlagenhauf-Lawlor P, ed. Travelers’ malaria. Hamilton, Ontario: BC Decker Inc; 2001.
  8. CastelliF. OdoliniS. AutinoB. FocaE. RussoR. Malaria prophylaxis: A comprehensive review.Pharmaceuticals.20103103212323910.3390/ph3103212
     [Google Scholar]
  9. MuellerI. ShakriA.R. ChitnisC.E. Development of vaccines for Plasmodium vivax malaria.Vaccine201533527489749510.1016/j.vaccine.2015.09.06026428453
     [Google Scholar]
  10. KokwaroG. Ongoing challenges in the management of malaria.Malar. J.20098S1S210.1186/1475‑2875‑8‑S1‑S219818169
     [Google Scholar]
  11. ManyandoC. KayentaoK. D’AlessandroU. OkaforH.U. JumaE. HamedK. A systematic review of the safety and efficacy of artemether-lumefantrine against uncomplicated Plasmodium falciparum malaria during pregnancy.Malar. J.201211114110.1186/1475‑2875‑11‑14122548983
     [Google Scholar]
  12. Waters, C.N.; Edstein, M.D. 8-Aminoquioones:Primaquine and Tafenoquine. In: Prevention of Malaria: Antimalarial Drug Chemistry, Action and Use; Staines HM, K.S., Ed., 2012.
  13. SinhaS. MedhiB. SehgalR. Challenges of drug-resistant malaria.Parasite2014216110.1051/parasite/201405925402734
     [Google Scholar]
  14. NewmanR.D. Relegating malaria resurgences to history.Malar. J.201211112310.1186/1475‑2875‑11‑12322531295
     [Google Scholar]
  15. FlanneryE.L. ChatterjeeA.K. WinzelerE.A. Antimalarial drug discovery — approaches and progress towards new medicines.Nat. Rev. Microbiol.2013111284986210.1038/nrmicro313824217412
     [Google Scholar]
  16. MacarronR. BanksM.N. BojanicD. BurnsD.J. CirovicD.A. GaryantesT. GreenD.V.S. HertzbergR.P. JanzenW.P. PaslayJ.W. SchopferU. SittampalamG.S. Impact of high-throughput screening in biomedical research.Nat. Rev. Drug Discov.201110318819510.1038/nrd336821358738
     [Google Scholar]
  17. SharmaR. LawrensonA.S. FisherN.E. WarmanA.J. ShoneA.E. HillA. MbekeaniA. PidathalaC. AmewuR.K. LeungS. GibbonsP. HongD.W. StocksP. NixonG.L. ChadwickJ. ShearerJ. GowersI. CronkD. ParelS.P. O’NeillP.M. WardS.A. BiaginiG.A. BerryN.G. Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.J. Med. Chem.20125573144315410.1021/jm300148222380711
     [Google Scholar]
  18. WerbovetzK.A. Target-based drug discovery for malaria, leishmaniasis, and trypanosomiasis.Curr. Med. Chem.20007883586010.2174/092986700337461510828290
     [Google Scholar]
  19. Gurard-LevinZ.A. ScholleM.D. EisenbergA.H. MrksichM. High-throughput screening of small molecule libraries using SAMDI mass spectrometry.ACS Comb. Sci.201113434735010.1021/co200037321639106
     [Google Scholar]
  20. SchweitzerB.I. DickerA.P. BertinoJ.R. Dihydrofolate reductase as a therapeutic target.FASEB J.1990482441245210.1096/fasebj.4.8.21859702185970
     [Google Scholar]
  21. VermaS. PrabhakarY. Target based drug design - a reality in virtual sphere.Curr. Med. Chem.201522131603163010.2174/092986732266615020915120925666805
     [Google Scholar]
  22. TangY. DongY. VennerstromJ.L. Synthetic peroxides as antimalarials.Med. Res. Rev.200424442544810.1002/med.1006615170591
     [Google Scholar]
  23. Cechinel-FilhoV. Plant bioactives and drug discovery: principles, practice, and perspectives.John Wiley & Sons201210.1002/9781118260005
     [Google Scholar]
  24. TaleleT. KhedkarS. RigbyA. Successful applications of computer aided drug discovery: Moving drugs from concept to the clinic.Curr. Top. Med. Chem.201010112714110.2174/15680261079023225119929824
     [Google Scholar]
  25. PrachayasittikulV. WorachartcheewanA. ShoombuatongW. SongtaweeN. SimeonS. PrachayasittikulV. NantasenamatC. Computer-aided drug design of bioactive natural products.Curr. Top. Med. Chem.201515181780180010.2174/156802661566615050615110125961523
     [Google Scholar]
  26. TaleviA. BelleraC.L. Challenges and opportunities with drug repurposing: Finding strategies to find alternative uses of therapeutics.Expert Opin. Drug Discov.202015439740110.1080/17460441.2020.170472931847616
     [Google Scholar]
  27. DondorpA.M. FairhurstR.M. SlutskerL. MacarthurJ.R. BremanJ.G. GuerinP.J. WellemsT.E. RingwaldP. NewmanR.D. PloweC.V. The threat of artemisinin-resistant malaria.N. Engl. J. Med.2011365121073107510.1056/NEJMp110832221992120
     [Google Scholar]
  28. DondorpA.M. NostenF. YiP. DasD. PhyoA.P. TarningJ. LwinK.M. ArieyF. HanpithakpongW. LeeS.J. RingwaldP. SilamutK. ImwongM. ChotivanichK. LimP. HerdmanT. AnS.S. YeungS. SinghasivanonP. DayN.P.J. LindegardhN. SocheatD. WhiteN.J. Artemisinin resistance in Plasmodium falciparum malaria.N. Engl. J. Med.2009361545546710.1056/NEJMoa080885919641202
     [Google Scholar]
  29. NoedlH. SeY. SchaecherK. SmithB.L. SocheatD. FukudaM.M. Evidence of artemisinin-resistant malaria in Western Cambodia.N. Engl. J. Med.2008359242619262010.1056/NEJMc080501119064625
     [Google Scholar]
  30. MbengueA. BhattacharjeeS. PandharkarT. LiuH. EstiuG. StahelinR.V. RizkS.S. NjimohD.L. RyanY. ChotivanichK. NguonC. GhorbalM. Lopez-RubioJ.J. PfrenderM. EmrichS. MohandasN. DondorpA.M. WiestO. HaldarK. A molecular mechanism of artemisinin resistance in Plasmodium falciparum malaria.Nature2015520754968368710.1038/nature1441225874676
     [Google Scholar]
  31. ArieyF. WitkowskiB. AmaratungaC. BeghainJ. LangloisA.C. KhimN. KimS. DuruV. BouchierC. MaL. LimP. LeangR. DuongS. SrengS. SuonS. ChuorC.M. BoutD.M. MénardS. RogersW.O. GentonB. FandeurT. MiottoO. RingwaldP. Le BrasJ. BerryA. BaraleJ.C. FairhurstR.M. Benoit-VicalF. Mercereau-PuijalonO. MénardD. A molecular marker of artemisinin-resistant Plasmodium falciparum malaria.Nature20145057481505510.1038/nature1287624352242
     [Google Scholar]
  32. UwimanaA. LegrandE. StokesB.H. NdikumanaJ.L.M. WarsameM. UmulisaN. NgamijeD. MunyanezaT. MazaratiJ.B. MungutiK. CampagneP. CriscuoloA. ArieyF. MurindahabiM. RingwaldP. FidockD.A. MbituyumuremyiA. MenardD. Emergence and clonal expansion of in vitro artemisinin-resistant Plasmodium falciparum kelch13 R561H mutant parasites in Rwanda.Nat. Med.202026101602160810.1038/s41591‑020‑1005‑232747827
     [Google Scholar]
  33. ZhangD.D. LoS.C. CrossJ.V. TempletonD.J. HanninkM. Keap1 is a redox-regulated substrate adaptor protein for a Cul3-dependent ubiquitin ligase complex.Mol. Cell. Biol.20042424109411095310.1128/MCB.24.24.10941‑10953.200415572695
     [Google Scholar]
  34. CoppéeR. JeffaresD.C. SabbaghA. ClainJ. Structural evolutionary analysis predicts functional sites in the artemisinin resistance malaria protein K13.bioRxiv201834666810.1101/346668
     [Google Scholar]
  35. MalariaG.E.N. Plasmodium falciparum Community Project. Genomic epidemiology of artemisinin resistant malaria. eLife201608714
     [Google Scholar]
  36. StraimerJ. GnädigN.F. WitkowskiB. AmaratungaC. DuruV. RamadaniA.P. DacheuxM. KhimN. ZhangL. LamS. GregoryP.D. UrnovF.D. Mercereau-PuijalonO. Benoit-VicalF. FairhurstR.M. MénardD. FidockD.A. K13-propeller mutations confer artemisinin resistance in Plasmodium falciparum clinical isolates.Science2015347622042843110.1126/science.126086725502314
     [Google Scholar]
  37. DogovskiC. XieS.C. BurgioG. BridgfordJ. MokS. McCawJ.M. ChotivanichK. KennyS. GnädigN. StraimerJ. BozdechZ. FidockD.A. SimpsonJ.A. DondorpA.M. FooteS. KlonisN. TilleyL. Targeting the cell stress response of Plasmodium falciparum to overcome artemisinin resistance.PLoS Biol.2015134e100213210.1371/journal.pbio.100213225901609
     [Google Scholar]
  38. WitkowskiB. AmaratungaC. KhimN. SrengS. ChimP. KimS. LimP. MaoS. SophaC. SamB. AndersonJ.M. DuongS. ChuorC.M. TaylorW.R.J. SuonS. Mercereau-PuijalonO. FairhurstR.M. MenardD. Novel phenotypic assays for the detection of artemisinin-resistant Plasmodium falciparum malaria in Cambodia: in vitro and ex vivo drug-response studies.Lancet Infect. Dis.201313121043104910.1016/S1473‑3099(13)70252‑424035558
     [Google Scholar]
  39. KaruppasamyR. VermaK. SequeiraV.M. BasavannaL.N. VeerappapillaiS. An Integrative drug repurposing pipeline: Switching viral drugs to breast cancer.J. Cell. Biochem.201711861412142210.1002/jcb.2579927859674
     [Google Scholar]
  40. StrittmatterS.M. Overcoming drug development bottlenecks with repurposing: Old drugs learn new tricks.Nat. Med.201420659059110.1038/nm.359524901567
     [Google Scholar]
  41. AshburnT.T. ThorK.B. Drug repositioning: Identifying and developing new uses for existing drugs.Nat. Rev. Drug Discov.20043867368310.1038/nrd146815286734
     [Google Scholar]
  42. 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.2018.16830310233
     [Google Scholar]
  43. BertoliniF. SukhatmeV.P. BoucheG. Drug repurposing in oncology—patient and health systems opportunities.Nat. Rev. Clin. Oncol.2015121273274210.1038/nrclinonc.2015.16926483297
     [Google Scholar]
  44. VermaK. LahariyaA.K. DubeyS. VermaA.K. DasA. SchneiderK.A. BhartiP.K. An integrated virtual screening and drug repurposing strategy for the discovery of new antimalarial drugs against Plasmodium falciparum phosphatidylinositol 3-kinase.J. Cell. Biochem.2021122101326133610.1002/jcb.2995433998049
     [Google Scholar]
  45. WishartD.S. FeunangY.D. GuoA.C. LoE.J. MarcuA. GrantJ.R. SajedT. JohnsonD. LiC. SayeedaZ. AssempourN. IynkkaranI. LiuY. MaciejewskiA. GaleN. WilsonA. ChinL. CummingsR. LeD. PonA. KnoxC. WilsonM. DrugBank 5.0: A major update to the DrugBank database for 2018.Nucleic Acids Res.201846D1D1074D108210.1093/nar/gkx103729126136
     [Google Scholar]
  46. YangJ. AnishchenkoI. ParkH. PengZ. OvchinnikovS. BakerD. Improved protein structure prediction using predicted interresidue orientations.Proc. Natl. Acad. Sci.202011731496150310.1073/pnas.191467711731896580
     [Google Scholar]
  47. LaskowskiR.A. HutchinsonE.G. MichieA.D. WallaceA.C. JonesM.L. ThorntonJ.M. PDBsum: A web-based database of summaries and analyses of all PDB structures.Trends Biochem. Sci.1997221248849010.1016/S0968‑0004(97)01140‑79433130
     [Google Scholar]
  48. BwireG.M. NgasalaB. MikomangwaW.P. KilonziM. KamuhabwaA.A.R. Detection of mutations associated with artemisinin resistance at k13-propeller gene and a near complete return of chloroquine susceptible falciparum malaria in Southeast of Tanzania.Sci. Rep.2020101350010.1038/s41598‑020‑60549‑732103124
     [Google Scholar]
  49. ShoichetB.K. Virtual screening of chemical libraries.Nature2004432701986286510.1038/nature0319715602552
     [Google Scholar]
  50. VermaK. KannanK. vS. RS. vK. KR. Exploring β-tubulin inhibitors from plant origin using computational approach.Phytochem. Anal.201728323024110.1002/pca.266528008675
     [Google Scholar]
  51. WangJ. HuangL. LiJ. FanQ. LongY. LiY. ZhouB. Artemisinin directly targets malarial mitochondria through its specific mitochondrial activation.PLoS One201053e958210.1371/journal.pone.000958220221395
     [Google Scholar]
  52. RamanathanK. VermaK. GuptaN. ShanthiV. Discovery of therapeutic lead molecule against β-tubulin using computational approach.Interdiscip. Sci.201810473474710.1007/s12539‑017‑0233‑828488218
     [Google Scholar]
  53. HuQ. FengM. LaiL. PeiJ. Prediction of drug-likeness using deep autoencoder neural networks.Front. Genet.2018958510.3389/fgene.2018.0058530538725
     [Google Scholar]
  54. TondiD. SlomczynskaU. CostiM.P. WattersonD.M. GhelliS. ShoichetB.K. Structure-based discovery and in-parallel optimization of novelcompetitive inhibitors of thymidylate synthase.Chem. Biol.19996531933110.1016/S1074‑5521(99)80077‑510322126
     [Google Scholar]
  55. SanderT. FreyssJ. von KorffM. RufenerC. DataWarrior: An open-source program for chemistry aware data visualization and analysis.J. Chem. Inf. Model.201555246047310.1021/ci500588j25558886
     [Google Scholar]
  56. von KorffM. SanderT. Toxicity-indicating structural patterns.J. Chem. Inf. Model.200646253654410.1021/ci050358k16562981
     [Google Scholar]
  57. PuL. NaderiM. LiuT. WuH.C. MukhopadhyayS. BrylinskiM. eToxPred: A machine learning-based approach to estimate the toxicity of drug candidates.BMC Pharmacol. Toxicol.2019201210.1186/s40360‑018‑0282‑630621790
     [Google Scholar]
  58. EnmozhiS.K. RajaK. SebastineI. JosephJ. Andrographolide as a potential inhibitor of SARS-CoV-2 main protease: An in silico approach.J. Biomol. Struct. Dyn.20213993092309832329419
     [Google Scholar]
  59. Pratap SinghH. SharmaC.S. MishraS.S. PandiyaH. KumarN. In silico ADME, bioactivity and toxicity prediction of some selected anti-Parkinson agents.Int J Pharm Phytopharmacol Res.201763646710.24896/eijppr.2016631
     [Google Scholar]
  60. MazzatortaP. EstevezM.D. CouletM. SchilterB. Modeling oral rat chronic toxicity.J. Chem. Inf. Model.200848101949195410.1021/ci800197418803370
     [Google Scholar]
  61. SarkarP. AlheetyM.A. SrivastavaV. Molecular docking and ADMET study of spice-derived potential phytochemicals against human DNA topoisomerase III alpha.Macromol. Symp.20234071220010810.1002/masy.202200108
     [Google Scholar]
  62. 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]
  63. StowersA.W. CioceV. ShimpR.L. LawsonM. HuiG. MuratovaO. KaslowD.C. RobinsonR. LongC.A. MillerL.H. Efficacy of two alternate vaccines based on Plasmodium falciparum merozoite surface protein 1 in an Aotus challenge trial.Infect. Immun.20016931536154610.1128/IAI.69.3.1536‑1546.200111179324
     [Google Scholar]
  64. MogireR.M. AkalaH.M. MachariaR.W. JumaD.W. CheruiyotA.C. AndagaluB. BrownM.L. El-ShemyH.A. NyanjomS.G. Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets.PLoS One20171210e018636410.1371/journal.pone.018636429088219
     [Google Scholar]
  65. MalhotraH. KumarA. AfaqY. Molecular docking analysis of FDA approved drugs with the glycoprotein from Junin and Machupo viruses.Bioinformation202218211912610.6026/9732063001811936420432
     [Google Scholar]
  66. HsuK.C. ChenY.F. LinS.R. YangJ.M. iGEMDOCK: A graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis.BMC Bioinformatics201112S1S3310.1186/1471‑2105‑12‑S1‑S3321342564
     [Google Scholar]
  67. GuedesI.A. CostaL.S.C. dos SantosK.B. KarlA.L.M. RochaG.K. TeixeiraI.M. GalheigoM.M. MedeirosV. KrempserE. CustódioF.L. BarbosaH.J.C. NicolásM.F. DardenneL.E. Drug design and repurposing with DockThor-VS web server focusing on SARS-CoV-2 therapeutic targets and their non-synonym variants.Sci. Rep.2021111554310.1038/s41598‑021‑84700‑033692377
     [Google Scholar]
  68. DainaA. MichielinO. ZoeteV. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.Sci. Rep.2017714271710.1038/srep4271728256516
     [Google Scholar]
  69. WagenerM. van GeeresteinV.J. Potential drugs and nondrugs: Prediction and identification of important structural features.J. Chem. Inf. Comput. Sci.200040228029210.1021/ci990266t10761129
     [Google Scholar]
  70. ByvatovE. FechnerU. SadowskiJ. SchneiderG. Comparison of support vector machine and artificial neural network systems for drug/nondrug classification.J. Chem. Inf. Comput. Sci.20034361882188910.1021/ci034116114632437
     [Google Scholar]
  71. SolimanM.E. AdewumiA.T. AkawaO.B. SubairT.I. OkunlolaF.O. AkinsukuO.E. KhanS. Simulation models for prediction of bioavailability of medicinal drugs—the interface between experiment and computation.AAPS PharmSciTech20222338610.1208/s12249‑022‑02229‑535292867
     [Google Scholar]
  72. WalumE. Acute oral toxicity.Environ. Health Perspect.1998106S249750310.1289/ehp.981064979599698
     [Google Scholar]
  73. ErhirhieE.O. IhekweremeC.P. IlodigweE.E. Advances in acute toxicity testing: Strengths, weaknesses and regulatory acceptance.Interdiscip. Toxicol.201811151210.2478/intox‑2018‑000130181707
     [Google Scholar]
  74. XuY. PeiJ. LaiL. Deep learning based regression and multiclass models for acute oral toxicity prediction with automatic chemical feature extraction.J. Chem. Inf. Model.201757112672268510.1021/acs.jcim.7b0024429019671
     [Google Scholar]
  75. YangH. LouC. SunL. LiJ. CaiY. WangZ. LiW. LiuG. TangY. admetSAR 2.0: Web-service for prediction and optimization of chemical ADMET properties.Bioinformatics.20193561067106910.1093/bioinformatics/bty70730165565
     [Google Scholar]
  76. NationsU. Globally harmonized system of classification and labelling of chemicals (GHS).New York, NY, USAUnited Nations201110.18356/4255cc90‑en
     [Google Scholar]
  77. CourniaZ. AllenB. ShermanW. Relative binding free energy calculations in drug discovery: Recent advances and practical considerations.J. Chem. Inf. Model.201757122911293710.1021/acs.jcim.7b0056429243483
     [Google Scholar]
  78. WangE. SunH. WangJ. WangZ. LiuH. ZhangJ.Z.H. HouT. End-point binding free energy calculation with MM/PBSA and MM/GBSA: strategies and applications in drug design.Chem. Rev.2019119169478950810.1021/acs.chemrev.9b0005531244000
     [Google Scholar]
  79. BioviaD.S. Discovery Studio Modeling Environment, Release, 4.Dassault SystèmesSan Diego2017
     [Google Scholar]
  80. BalmforthG.V. SamuelR.K. Controlled trial of oxethazaine as an analgesic in duodenal ulcer.BMJ19641537935535610.1136/bmj.1.5379.35514079039
     [Google Scholar]
  81. MoghadasianM.H. Clinical pharmacology of 3-hydroxy-3-methylglutaryl coenzyme a reductase inhibitors.Life Sci.199965131329133710.1016/S0024‑3205(99)00199‑X10503952
     [Google Scholar]
  82. Massi-BenedettiM. DamsboP. Pharmacology and clinical experience with repaglinide.Expert Opin. Investig. Drugs20009488589810.1517/13543784.9.4.88511060717
     [Google Scholar]
  83. CazzolaM. RoglianiP. MateraM.G. Aclidinium bromide/formoterol fumarate fixed-dose combination for the treatment of chronic obstructive pulmonary disease.Expert Opin. Pharmacother.201314677578110.1517/14656566.2013.77653923472632
     [Google Scholar]
  84. ConnollyS.J. KatesR.E. LebsackC.S. HarrisonD.C. WinkleR.A. Clinical pharmacology of propafenone.Circulation198368358959610.1161/01.CIR.68.3.5896872170
     [Google Scholar]
  85. BorutaT. BizukojcM. Production of lovastatin and itaconic acid by Aspergillus terreus: A comparative perspective.World J. Microbiol. Biotechnol.20173323410.1007/s11274‑017‑2206‑928102516
     [Google Scholar]
  86. WongR.P.M. DavisT.M.E. Statins as potential antimalarial drugs: Low relative potency and lack of synergy with conventional antimalarial drugs.Antimicrob. Agents Chemother.20095352212221410.1128/AAC.01469‑0819258270
     [Google Scholar]
  87. GrellierP. ValentinA. MilleriouxV. SchrevelJ. RigomierD. 3-Hydroxy-3-methylglutaryl coenzyme A reductase inhibitors lovastatin and simvastatin inhibit in vitro development of Plasmodium falciparum and Babesia divergens in human erythrocytes.Antimicrob. Agents Chemother.19943851144114810.1128/AAC.38.5.11448067753
     [Google Scholar]
  88. DialloB.N. SwartT. HoppeH.C. Tastan BishopÖ. LobbK. Potential repurposing of four FDA approved compounds with antiplasmodial activity identified through proteome scale computational drug discovery and in vitro assay.Sci. Rep.2021111141310.1038/s41598‑020‑80722‑233446838
     [Google Scholar]
  89. PainterH.J. MorriseyJ.M. VaidyaA.B. Mitochondrial electron transport inhibition and viability of intraerythrocytic Plasmodium falciparum.Antimicrob. Agents Chemother.201054125281528710.1128/AAC.00937‑1020855748
     [Google Scholar]
  90. Gomez-LorenzoM.G. Rodríguez-AlejandreA. Martínez-HoyosM. Bahamontes-RosaN. Gonzalez Del RioR. CarolinaR. de la FuenteJ. JoseL.L. García-BustosJ.F. Mendoza-LosanaA. Functional screening of selective mitochondrial inhibitors of Plasmodium.Int J Parasitol Drugs Drug Resist.20188229530310.1016/j.ijpddr.2018.04.007
     [Google Scholar]
/content/journals/cmc/10.2174/0929867331666230807151708
Loading
Drug Repurposing against Novel Therapeutic Targets in Plasmodium falciparum for Malaria: The Computational Perspective
Curr. Med. Chem. 31, 6272 (2024); https://doi.org/10.2174/0929867331666230807151708
/content/journals/cmc/10.2174/0929867331666230807151708
/content/journals/cmc/10.2174/0929867331666230807151708
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): antimalarial; computational biology; computational perspective; drug repurposing; Falciparum; tropical diseases

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