Molecular Modeling Studies and Synthesis of Isocryptolepine Derivatives as Antimalarial using Docking, CoMFA, CoMSIA, and HQSAR

References

1. TalapkoJ. ŠkrlecI. AlebićT. JukićM. VčevA. Malaria: The past and the present.Microorganisms20197617910.3390/microorganisms7060179 31234443
   [Google Scholar]
2. CoxF.E.G. History of the discovery of the malaria parasites and their vectors.Parasit. Vectors201031510.1186/1756‑3305‑3‑5 20205846
   [Google Scholar]
3. MaceK.E. ArguinP.M. TanK.R. Malaria Surveillance — United States, 2015.MMWR Surveill. Summ.201867712810.15585/mmwr.ss6707a1 29723168
   [Google Scholar]
4. IslamM.R. DharP.S. RahmanM.M. Recently outbreak of malaria in current world: species, etiology, life cycle, transmission, symptoms, vaccination, diagnostic tests, treatment, and complications.Int. J. Surg.2023109217517710.1097/JS9.0000000000000165 36799842
   [Google Scholar]
5. SatoS. Plasmodium—a brief introduction to the parasites causing human malaria and their basic biology.J. Physiol. Anthropol.2021401110.1186/s40101‑020‑00251‑9 33413683
   [Google Scholar]
6. LeeW.C. CheongF.W. AmirA. Plasmodium knowlesi: the game changer for malaria eradication.Malar. J.202221114010.1186/s12936‑022‑04131‑8 35505339
   [Google Scholar]
7. PhillipsM.A. BurrowsJ.N. ManyandoC. van HuijsduijnenR.H. Van VoorhisW.C. WellsT.N.C. Malaria.Nat. Rev. Dis. Primers2017311705010.1038/nrdp.2017.50 28770814
   [Google Scholar]
8. WambaniJ. OkothP. Impact of malaria diagnostic technologies on the disease burden in the Sub-Saharan Africa.J. Trop. Med.202220221810.1155/2022/7324281 35360189
   [Google Scholar]
9. VaroR. ChaccourC. BassatQ. Update on malaria.Med. Clín. (Barc.)2020155939540210.1016/j.medcli.2020.05.010 32620355
   [Google Scholar]
10. ZekarL. SharmanT. Plasmodium falciparum Malaria.Treasure Island, FLStatPearls Publishing2024
    [Google Scholar]
11. Schantz-DunnJ. NourN.M. Malaria and pregnancy: A global health perspective.Rev. Obstet. Gynecol.200923186192 19826576
    [Google Scholar]
12. AndradeM.V. NoronhaK. DinizB.P.C. The economic burden of malaria: a systematic review.Malar. J.202221128310.1186/s12936‑022‑04303‑6 36199078
    [Google Scholar]
13. OladipoH.J. TajudeenY.A. OladunjoyeI.O. Increasing challenges of malaria control in sub-Saharan Africa: Priorities for public health research and policymakers.Ann. Med. Surg. (Lond.)20228110436610.1016/j.amsu.2022.104366 36046715
    [Google Scholar]
14. MillerL.H. SuX. Artemisinin: discovery from the Chinese herbal garden.Cell2011146685585810.1016/j.cell.2011.08.024 21907397
    [Google Scholar]
15. GrazioseR. Ann LilaM. RaskinI. Merging traditional Chinese medicine with modern drug discovery technologies to find novel drugs and functional foods.Curr. Drug Discov. Technol.20107121210.2174/157016310791162767 20156139
    [Google Scholar]
16. WangJ. XuC. WongY.K. Artemisinin, the magic drug discovered from Traditional Chinese Medicine.Engineering201951323910.1016/j.eng.2018.11.011
    [Google Scholar]
17. OmariA.A.A. GambleC.L. GarnerP. Artemether-lumefantrine (four-dose regimen) for treating uncomplicated falciparum malaria.Cochrane Libr.200620062CD00596510.1002/14651858.CD005965 16625646
    [Google Scholar]
18. PetoT.J. TripuraR. CalleryJ.J. Triple therapy with artemether–lumefantrine plus amodiaquine versus artemether–lumefantrine alone for artemisinin-resistant, uncomplicated falciparum malaria: an open-label, randomised, multicentre trial.Lancet Infect. Dis.202222686787810.1016/S1473‑3099(21)00692‑7 35276064
    [Google Scholar]
19. FaurantC. From bark to weed: The history of artemisinin.Parasite201118321521810.1051/parasite/2011183215 21894261
    [Google Scholar]
20. WellsT.N.C. Natural products as starting points for future anti-malarial therapies: going back to our roots?Malar. J.201110S110.1186/1475‑2875‑10‑S1‑S3 21411014
    [Google Scholar]
21. PerminH. NornS. KruseE. KruseP.R. On the history of Cinchona bark in the treatment of Malaria.Dan. Medicinhist. Arbog201644930 29737660
    [Google Scholar]
22. GachelinG. GarnerP. FerroniE. TröhlerU. ChalmersI. Evaluating Cinchona bark and quinine for treating and preventing malaria.J. R. Soc. Med.20171101314010.1177/0141076816681421 28106483
    [Google Scholar]
23. SáJ.M. ChongJ.L. WellemsT.E. Malaria drug resistance: new observations and developments.Essays Biochem.20115113716010.1042/bse0510137 22023447
    [Google Scholar]
24. EckerA. LehaneA.M. ClainJ. FidockD.A. PfCRT and its role in antimalarial drug resistance.Trends Parasitol.2012281150451410.1016/j.pt.2012.08.002 23020971
    [Google Scholar]
25. SinhaS. MedhiB. SehgalR. Challenges of drug-resistant malaria.Parasite2014216110.1051/parasite/2014059 25402734
    [Google Scholar]
26. PloweC.V. Malaria chemoprevention and drug resistance: a review of the literature and policy implications.Malar. J.202221110410.1186/s12936‑022‑04115‑8 35331231
    [Google Scholar]
27. HydeJ.E. Exploring the folate pathway in Plasmodium falciparum.Acta Trop.200594319120610.1016/j.actatropica.2005.04.002 15845349
    [Google Scholar]
28. WangP. LeeC.S. BayoumiR. Resistance to antifolates in Plasmodium falciparum monitored by sequence analysis of dihydropteroate synthetase and dihydrofolate reductase alleles in a large number of field samples of diverse origins.Mol. Biochem. Parasitol.199789216117710.1016/S0166‑6851(97)00114‑X 9364963
    [Google Scholar]
29. NzilaA. The past, present and future of antifolates in the treatment of Plasmodium falciparum infection.J. Antimicrob. Chemother.20065761043105410.1093/jac/dkl104 16617066
    [Google Scholar]
30. NduatiE. DiriyeA. OmmehS. Effect of folate derivatives on the activity of antifolate drugs used against malaria and cancer.Parasitol. Res.200810261227123410.1007/s00436‑008‑0897‑4 18259776
    [Google Scholar]
31. PathakM. OjhaH. TiwariA.K. SharmaD. SainiM. KakkarR. Design, synthesis and biological evaluation of antimalarial activity of new derivatives of 2,4,6-s-triazine.Chem. Cent. J.201711113210.1186/s13065‑017‑0362‑5 29256159
    [Google Scholar]
32. YuvaniyamaJ. ChitnumsubP. KamchonwongpaisanS. Insights into antifolate resistance from malarial DHFR-TS structures.Nat. Struct. Mol. Biol.200310535736510.1038/nsb921 12704428
    [Google Scholar]
33. HollingsworthS.A. DrorR.O. Molecular dynamics simulation for all.Neuron20189961129114310.1016/j.neuron.2018.08.011 30236283
    [Google Scholar]
34. TvaroškaI. KozmonS. KóňaJ. Molecular modeling insights into the structure and behavior of integrins: A review.Cells202312232410.3390/cells12020324 36672259
    [Google Scholar]
35. YuanitaE. Sudirman, Dharmayani NKT, Ulfa M, Syahri J. Quantitative structure–activity relationship (QSAR) and molecular docking of xanthone derivatives as anti-tuberculosis agents.J. Clin. Tuberc. Other Mycobact. Dis.20202110020310.1016/j.jctube.2020.100203 33294629
    [Google Scholar]
36. MattaC.F. ArabiA.A. Electron-density descriptors as predictors in quantitative structure-activity/property relationships and drug design.Future Med. Chem.20113896999410.4155/fmc.11.65 21707400
    [Google Scholar]
37. WangF. YangW. ZhouB. Studies on the antibacterial activities and molecular mechanism of GyrB inhibitors by 3D-QSAR, molecular docking and molecular dynamics simulation.Arab. J. Chem.202215610387210.1016/j.arabjc.2022.103872
    [Google Scholar]
38. AbdizadehR. HadizadehF. AbdizadehT. QSAR analysis of coumarin-based benzamides as histone deacetylase inhibitors using CoMFA, CoMSIA and HQSAR methods.J. Mol. Struct.2020119912696110.1016/j.molstruc.2019.126961
    [Google Scholar]
39. VeríssimoG.C. Menezes DutraE.F. Teotonio DiasA.L. HQSAR and random forest-based QSAR models for anti-T. vaginalis activities of nitroimidazoles derivatives.J. Mol. Graph. Model.20199018019110.1016/j.jmgm.2019.04.007 31100677
    [Google Scholar]
40. BastikarV. BastikarA. GuptaP. Quantitative structure–activity relationship-based computational approaches.Infection2022202219120510.1016/B978‑0‑323‑91172‑6.00001‑7
    [Google Scholar]
41. KimJ.H. JeongJ.H. Structure-activity relationship studies based on 3D-QSAR CoMFA/CoMSIA for thieno-pyrimidine derivatives as triple negative breast cancer inhibitors.Molecules20222722797410.3390/molecules27227974 36432075
    [Google Scholar]
42. MurumkarP.R. GuptaS.D. ZambreV.P. GiridharR. YadavM.R. Development of predictive 3D-QSAR CoMFA and CoMSIA models for β-aminohydroxamic acid-derived tumor necrosis factor-α converting enzyme inhibitors.Chem. Biol. Drug Des.20097319710710.1111/j.1747‑0285.2008.00737.x 19152638
    [Google Scholar]
43. YangX.L. ZhouY. LiuX.L. Fragment-based hologram QSAR studies on a series of 2,4-dioxopyrimidine-1-carboxamides as highly potent inhibitors of acid ceramidase.Iran. J. Pharm. Res.201615139148 28058055
    [Google Scholar]
44. SouzaA. MagalhaesU. AlbuquerqueM. Hologram quantitative structure–activity relationship and comparative molecular field analysis studies within a series of tricyclic phthalimide HIV-1 integrase inhibitors.Drug Des. Devel. Ther.2013795396110.2147/DDDT.S47057 24039405
    [Google Scholar]
45. WangJ. ZhangC.J. ChiaW.N. Haem-activated promiscuous targeting of artemisinin in Plasmodium falciparum.Nat. Commun.2015611011110.1038/ncomms10111 26694030
    [Google Scholar]
46. ZhaoY.Q. LiX. GuoH.Y. ShenQ.K. QuanZ.S. LuanT. Application of quinoline ring in structural modification of natural products.Molecules20232818647810.3390/molecules28186478 37764254
    [Google Scholar]
47. HerraizT. GuillénH. González-PeñaD. AránV.J. Antimalarial quinoline drugs inhibit β-hematin and increase free hemin catalyzing peroxidative reactions and inhibition of cysteine proteases.Sci. Rep.2019911539810.1038/s41598‑019‑51604‑z 31659177
    [Google Scholar]
48. ParvatkarP.T. DiagneK. ZhaoY. ManetschR. Indoloquinoline alkaloids as antimalarials: Advances, challenges, and opportunities.ChemMedChem20241918e20240025410.1002/cmdc.202400254 38840271
    [Google Scholar]
49. WangN. WichtK.J. ImaiK. Synthesis, β-haematin inhibition, and in vitro antimalarial testing of isocryptolepine analogues: SAR study of indolo[3, 2-c]quinolines with various substituents at C2, C6, and N11.Bioorg. Med. Chem.20142292629264210.1016/j.bmc.2014.03.030 24721829
    [Google Scholar]
50. HonarparvarB. GovenderT. MaguireG.E.M. SolimanM.E.S. KrugerH.G. Integrated approach to structure-based enzymatic drug design: molecular modeling, spectroscopy, and experimental bioactivity.Chem. Rev.2014114149353710.1021/cr300314q 24024775
    [Google Scholar]
51. CramerR.D. PattersonD.E. BunceJ.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.J. Am. Chem. Soc.1988110185959596710.1021/ja00226a005 22148765
    [Google Scholar]
52. KlebeG. AbrahamU. MietznerT. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity.J. Med. Chem.199437244130414610.1021/jm00050a010 7990113
    [Google Scholar]
53. ChoS.J. KimJ.H. Hologram QSAR: three-dimensional quantitative structure-activity relationships with molecule hologram.J. Chem. Inf. Comput. Sci.199939589990610.1021/ci9903239
    [Google Scholar]
54. ] SYBYL X 2.0, Molecular Modeling Software. Tripos International, St. Louis, MO, USA. SYBYL X 2.0 Accessed from Tripos, L.P. (now part of Certara).1999
    [Google Scholar]
55. VilarS. CostanziS. Predicting the biological activities through QSAR analysis and docking-based scoring.Methods Mol. Biol.201291427128410.1007/978‑1‑62703‑023‑6_16 22976034
    [Google Scholar]
56. ShiriF. PirhadiS. GhasemiJ.B. Alignment independent 3D-QSAR, quantum calculations and molecular docking of Mer specific tyrosine kinase inhibitors as anticancer drugs.Saudi Pharm. J.201624219721210.1016/j.jsps.2015.03.012 27013913
    [Google Scholar]
57. SharmaR. DhingraN. PatilS. CoMFA, CoMSIA, HQSAR and molecular docking analysis of ionone-based chalcone derivatives as antiprostate cancer activity.Indian J. Pharm. Sci.2016781546410.4103/0250‑474X.180251 27168682
    [Google Scholar]
58. AshrafN. AsariA. YousafN. Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors.Front Chem.202210100381610.3389/fchem.2022.1003816
    [Google Scholar]
59. BabuS. SohnH. MadhavanT. Computational Analysis of CRTh2 receptor antagonist: A Ligand-based CoMFA and CoMSIA approach.Comput. Biol. Chem.20155610912110.1016/j.compbiolchem.2015.04.007 25935115
    [Google Scholar]
60. RasulevB. Recent developments in 3D QSAR and molecular docking studies of organic and nanostructures. Handbook of Computational Chemistry201710.1007/978‑3‑319‑27282‑5_54
    [Google Scholar]
61. QinJ. XiL. DuJ. LiuH. YaoX. QSAR studies on aminothiazole derivatives as aurora a kinase inhibitors.Chem. Biol. Drug Des.201076652753710.1111/j.1747‑0285.2010.01030.x 21040493
    [Google Scholar]
62. ZhaoX. ChenM. HuangB. JiH. YuanM. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies on α(1A)-adrenergic receptor antagonists based on pharmacophore molecular alignment.Int. J. Mol. Sci.201112107022703710.3390/ijms12107022 22072933
    [Google Scholar]
63. GajjarK.A. GajjarA.K. CoMFA, CoMSIA and HQSAR analysis of 3-aryl-3-ethoxypropanoic acid derivatives as GPR40 modulators.Curr. Drug Discov. Technol.202017110011810.2174/1570163815666180829144431 30160214
    [Google Scholar]
64. AshekA. San JuanA.A. ChoS.J. HQSAR study of β-ketoacyl‐acyl carrier protein synthase III (FabH) inhibitors.J. Enzyme Inhib. Med. Chem.200722171410.1080/14756360600920149 17373541
    [Google Scholar]
65. SalumL.B. AndricopuloA.D. Fragment-based QSAR: perspectives in drug design.Mol. Divers.200913327728510.1007/s11030‑009‑9112‑5 19184499
    [Google Scholar]
66. KumarR. LångströmB. Darreh-ShoriT. Novel ligands of Choline Acetyltransferase designed by in silico molecular docking, hologram QSAR and lead optimization.Sci. Rep.2016613124710.1038/srep31247 27507101
    [Google Scholar]
67. ChhatbarD.M. ChaubeU.J. VyasV.K. BhattH.G. CoMFA, CoMSIA, Topomer CoMFA, HQSAR, molecular docking and molecular dynamics simulations study of triazine morpholino derivatives as mTOR inhibitors for the treatment of breast cancer.Comput. Biol. Chem.20198035136310.1016/j.compbiolchem.2019.04.017 31085426
    [Google Scholar]
68. GadheC. BalupuriA. BalasubramanianP. ChoS. Modeling study of phenylsulfonylfuroxan derivatives as P-gp inhibitors: a combined approach of CoMFA, CoMSIA and HQSAR.Anticancer. Agents Med. Chem.20131471019103010.2174/18715206113136660335 24066798
    [Google Scholar]
69. LuoD. TongJ.B. ZhangX. XiaoX.C. BianS. Computational strategies towards developing novel SARS-CoV-2 Mpro inhibitors against COVID-19.J. Mol. Struct.2022124713137810.1016/j.molstruc.2021.131378 34483363
    [Google Scholar]
70. QianH. ChenJ. PanY. ChenJ. Molecular modeling studies of 11β-hydroxysteroid dehydrogenase type 1 inhibitors through receptor-based 3D-QSAR and molecular dynamics simulations.Molecules2016219122210.3390/molecules21091222 27657020
    [Google Scholar]
71. BuabeidM.A. ArafaE.S.A. HassanW. MurtazaG. In silico prediction of the mode of action of Viola odorata in diabetes.BioMed Res. Int.2020202011310.1155/2020/2768403 33490239
    [Google Scholar]
72. RenY. LongS. CaoS. Molecular docking and virtual screening of an influenza virus inhibitor that disrupts protein–protein interactions.Viruses20211311222910.3390/v13112229 34835035
    [Google Scholar]
73. LiX. ChuZ. DuX. QiuY. LiY. Combined molecular docking, homology modelling and density functional theory studies to modify dioxygenase to efficiently degrade aromatic hydrocarbons.RSC Advances2019920114651147510.1039/C8RA10663K 35520246
    [Google Scholar]
74. BermanH.M. WestbrookJ. FengZ. The protein data bank.Nucleic Acids Res.200028123524210.1093/nar/28.1.235 10592235
    [Google Scholar]
75. ReadR.J. AdamsP.D. ArendallW.B.III A new generation of crystallographic validation tools for the protein data bank.Structure201119101395141210.1016/j.str.2011.08.006 22000512
    [Google Scholar]
76. SinghR. LemireJ. MaillouxR.J. AppannaV.D. A novel strategy involved in [corrected] anti-oxidative defense: the conversion of NADH into NADPH by a metabolic network.PLoS One200837e268210.1371/journal.pone.0002682 18628998
    [Google Scholar]
77. MengX.Y. ZhangH.X. MezeiM. CuiM. Molecular docking: a powerful approach for structure-based drug discovery.Curr. Computeraided Drug Des.20117214615710.2174/157340911795677602 21534921
    [Google Scholar]
78. LiH. RobertsonA.D. JensenJ.H. Very fast empirical prediction and rationalization of protein pKa values.Proteins200561470472110.1002/prot.20660 16231289
    [Google Scholar]
79. OlssonM.H.M. SøndergaardC.R. RostkowskiM. JensenJ.H. PROPKA3: Consistent treatment of internal and surface residues in empirical p Ka predictions.J. Chem. Theory Comput.20117252553710.1021/ct100578z 26596171
    [Google Scholar]
80. GaoX. HanL. RenY. In silico exploration of 1,7-diazacarbazole analogs as checkpoint kinase 1 inhibitors by using 3D QSAR, molecular docking study, and molecular dynamics simulations.Molecules201621559110.3390/molecules21050591 27164065
    [Google Scholar]
81. BaammiS. DaoudR. El AllaliA. In silico protein engineering shows that novel mutations affecting NAD+ binding sites may improve phosphite dehydrogenase stability and activity.Sci. Rep.2023131187810.1038/s41598‑023‑28246‑3 36725973
    [Google Scholar]
82. XueQ. LiuX. RussellP. Evaluation of the binding performance of flavonoids to estrogen receptor alpha by Autodock, Autodock Vina and Surflex-Dock.Ecotoxicol. Environ. Saf.202223311332310.1016/j.ecoenv.2022.113323 35183811
    [Google Scholar]
83. MorrisG.M. HueyR. LindstromW. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.J. Comput. Chem.200930162785279110.1002/jcc.21256 19399780
    [Google Scholar]
84. LimaM.N.N. Melo-FilhoC.C. CassianoG.C. QSAR-driven design and discovery of novel compounds with antiplasmodial and transmission blocking activities.Front. Pharmacol.2018914610.3389/fphar.2018.00146 29559909
    [Google Scholar]
85. SainyJ. SharmaR. QSAR analysis of thiolactone derivatives using HQSAR, CoMFA and CoMSIA.SAR QSAR Environ. Res.2015261087389210.1080/1062936X.2015.1095238 26524489
    [Google Scholar]
86. BergmanJ. EngqvistR. StålhandskeC. WallbergH. Studies of the reactions between indole-2,3-diones (isatins) and 2-aminobenzylamine.Tetrahedron20035971033104810.1016/S0040‑4020(02)01647‑2
    [Google Scholar]
87. MajiA. Drug susceptibility testing methods of antimalarial agents.Trop. Parasitol.201882707610.4103/2229‑5070.248695 30693210
    [Google Scholar]
88. TouganT. EdulaJ.R. MoritaM. The malaria parasite Plasmodium falciparum in red blood cells selectively takes up serum proteins that affect host pathogenicity.Malar. J.202019115510.1186/s12936‑020‑03229‑1 32295584
    [Google Scholar]
89. SchusterF.L. Cultivation of Plasmodium spp.Clin. Microbiol. Rev.200215335536410.1128/CMR.15.3.355‑364.2002 12097244
    [Google Scholar]
90. BascoL.K. Cultivation of Asexual Intraerythrocytic Stages of Plasmodium falciparum.Pathogens202312790010.3390/pathogens12070900 37513747
    [Google Scholar]
91. AlshawshM.A. MothanaR.A. Al-shamahyH.A. AlsllamiS.F. LindequistU. Assessment of antimalarial activity against Plasmodium falciparum and phytochemical screening of some Yemeni medicinal plants.Evid. Based Complement. Alternat. Med.20096445345610.1093/ecam/nem148 18955251
    [Google Scholar]
92. DiasB.K.M. NakabashiM. AlvesM.R.R. The Plasmodium falciparum eIK1 kinase (PfeIK1) is central for melatonin synchronization in the human malaria parasite. Melatotosil blocks melatonin action on parasite cell cycle.J. Pineal Res.2020693e1268510.1111/jpi.12685 32702775
    [Google Scholar]
93. TomarV. BhattacharjeeG. Kamaluddin, Rajakumar S, Srivastava K, Puri SK. Synthesis of new chalcone derivatives containing acridinyl moiety with potential antimalarial activity.Eur. J. Med. Chem.201045274575110.1016/j.ejmech.2009.11.022 20022412
    [Google Scholar]
94. DentA.E. ChelimoK. SumbaP.O. Temporal stability of naturally acquired immunity to Merozoite Surface Protein-1 in Kenyan Adults.Malar. J.20098116210.1186/1475‑2875‑8‑162 19607717
    [Google Scholar]
95. NqoroX. TobekaN. AderibigbeB. Quinoline-based hybrid compounds with antimalarial activity.Molecules20172212226810.3390/molecules22122268 29257067
    [Google Scholar]
96. CortopassiW.A. GundersonE. AnnunciatoY. Fighting Plasmodium chloroquine resistance with acetylenic chloroquine analogues.Int. J. Parasitol. Drugs Drug Resist.20222012112810.1016/j.ijpddr.2022.10.003 36375339
    [Google Scholar]
97. FaizanM. KumarR. MazumderA. The medicinal chemistry of piperazines: A review.Chem. Biol. Drug Des.20241036e1453710.1111/cbdd.14537 38888058
    [Google Scholar]
98. CalicP.P.S. MansouriM. ScammellsP.J. McGowanS. Driving antimalarial design through understanding of target mechanism.Biochem. Soc. Trans.20204852067207810.1042/BST20200224 32869828
    [Google Scholar]
99. UpadhyayC. ChaudharyM. De OliveiraR.N. Fluorinated scaffolds for antimalarial drug discovery.Expert Opin. Drug Discov.202015670571810.1080/17460441.2020.1740203 32202162
    [Google Scholar]
100. Al-HarthyT. ZoghaibW. Abdel-JalilR. Importance of fluorine in benzazole compounds.Molecules20202520467710.3390/molecules25204677 33066333
     [Google Scholar]