Structural Chemistry

, Volume 30, Issue 6, pp 2301–2310 | Cite as

Relationship between electronic structures and antiplasmodial activities of xanthone derivatives: a 2D-QSAR approach

  • Gaston A. KpotinEmail author
  • Affoué Lucie Bédé
  • Alice Houngue-Kpota
  • Wilfried Anatovi
  • Urbain A. Kuevi
  • Guy S. Atohoun
  • Jean-Baptiste Mensah
  • Juan S. Gómez-Jeria
  • Michael BadawiEmail author
Original Research


Malaria is an important disease causing many death in several countries of Africa and Asia. In these continents, some plants such as Garcinia cola are used to fight against this disease because they contain xanthone derivatives which present antiplasmodial activity. The present theoretical study aims to establish a relationship between the electronic structure and the antiplasmodial activity of some xanthone derivatives, and more specifically to build a 2D-pharmacophore model in order to predict the biological activity of xanthone derivatives. The calculations are performed within the density functional theory (DFT) using the B3LYP/6-31G(d,p) level of theory. The developed approach quantitative structure-activity relationship (QSAR) follows the Klopman-Peradejordi-Gómez (KPG) methodology. We obtain a statistically significant equation relating the variation of the logarithm of half maximal inhibitory concentration (log(IC50)) with the variation of the numerical values of a set of eight local atomic reactivity descriptors (R = 0.98, R2 = 0.97, adj-R2 = 0.95, F(8.13) = 48.63, p < 0.00000, SD 0.08). The antiplasmodial activity seems to be driven by atomic orbitals and charges. Our 2D-pharmacophore model should be useful to propose new xanthone derivatives with higher antiplasmodial activity.


Xanthone Antiplasmodial QSAR DFT Klopman-Peradejordi-Gómez approach Malaria 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    World Health Organization and Global Malaria Programme World malaria report 2017 (2017) Accessed 29 Nov 2017
  2. 2.
    Rosenthal PJ, Rathod PK, Ndiaye D, Mharakurwa S, Cui L (2015) Antimalarial drug resistance: literature review and activities and findings of the ICEMR network. Am. J. Trop. Med. Hyg. 93:57–68PubMedPubMedCentralGoogle Scholar
  3. 3.
    Menard D, Dondorp A (2017) Antimalarial drug resistance: a threat to malaria elimination. Cold Spring Harb. Perspect. Med. 7:a025619CrossRefGoogle Scholar
  4. 4.
    Boudhar A, Ng XW, Loh CY, Chia WN, Tan ZM, Nosten F, Dymock BW, Tan KSW (2016) Overcoming chloroquine resistance in malaria: design, synthesis and structure–activity relationships of novel chemoreversal agents. Eur. J. Med. Chem. 119:231–249CrossRefGoogle Scholar
  5. 5.
    Kalaria PN, Karad SC, Raval DK (2018) A review on diverse heterocyclic compounds as the privileged scaffolds in antimalarial drug discovery. Eur. J. Med. Chem. 158:917–936CrossRefGoogle Scholar
  6. 6.
    Auranwiwat C, Laphookhieo S, Rattanajak R, Kamchonwongpaisan S, Pyne SG, Ritthiwigrom T (2016) Antimalarial polyoxygenated and prenylated xanthones from the leaves and branches of Garcinia mckeaniana. Tetrahedron 72:6837–6842CrossRefGoogle Scholar
  7. 7.
    Winter RW, Cornell KA, Johnson LL, Ignatushchenko M, Hinrichs DJ, Riscoe MK (1996) Potentiation of the antimalarial agent rufigallol. Antimicrob. Agents Chemother. 40:1408–1411CrossRefGoogle Scholar
  8. 8.
    Ignatushchenko MV, Winter RW, Bächinger HP, Hinrichs DJ, Riscoe MK (1997) Xanthones as antimalarial agents; studies of a possible mode of action. FEBS Lett. 409:67–73CrossRefGoogle Scholar
  9. 9.
    Ignatushchenko MV, Winter RW, Riscoe M (2000) Xanthones as antimalarial agents: stage specificity. Am. J. Trop. Med. Hyg. 62:77–81CrossRefGoogle Scholar
  10. 10.
    Hay A-E, Hélesbeux J-J, Duval O, Labaïed M, Grellier P, Richomme P (2004) Antimalarial xanthones from Calophyllum caledonicum and Garcinia vieillardii. Life Sci. 75:3077–3085CrossRefGoogle Scholar
  11. 11.
    Mahabusarakam W, Kuaha K, Wilairat P, Taylor W (2006) Prenylated xanthones as potential antiplasmodial substances. Planta Med. 72:912–916CrossRefGoogle Scholar
  12. 12.
    Upegui Y, Robledo SM, Gil Romero JF, Quiñones W, Archbold R, Torres F, Escobar G, Nariño B, Echeverri F (2015) In vivo antimalarial activity of α-mangostin and the new xanthone δ-mangostin: antimalarial activity of a new xanthone. Phytother. Res. 29:1195–1201CrossRefGoogle Scholar
  13. 13.
    Noguera GJ, Fabian LE, Lombardo E, Finkielsztein L (2015) QSAR study and conformational analysis of 4-arylthiazolylhydrazones derived from 1-indanones with anti-Trypanosoma cruzi activity. Eur. J. Pharm. Sci. 78:190–197CrossRefGoogle Scholar
  14. 14.
    Shayanfar A, Shayanfar S (2014) Is regression through origin useful in external validation of QSAR models? Eur. J. Pharm. Sci. 59:31–35CrossRefGoogle Scholar
  15. 15.
    Shibi IG, Aswathy L, Jisha RS, Masand VH, Divyachandran A, Gajbhiye JM (2015) Molecular docking and QSAR analyses for understanding the antimalarial activity of some 7-substituted-4-aminoquinoline derivatives. Eur. J. Pharm. Sci. 77:9–23CrossRefGoogle Scholar
  16. 16.
    Cheng Y, Luo F, Zeng Z, Wen L, Xiao Z, Bu H, Lv F, Xu Z, Lin Q (2015) DFT-based quantitative structure–activity relationship studies for antioxidant peptides. Struct. Chem. 26:739–747CrossRefGoogle Scholar
  17. 17.
    Toropov AA, Toropova AP, Benfenati E, Gini G, Fanelli R (2013) The definition of the molecular structure for potential anti-malaria agents by the Monte Carlo method. Struct. Chem. 24:1369–1381CrossRefGoogle Scholar
  18. 18.
    Martin YC (1978) Quantitative drug design: a critical introduction Print book: English. Marcel Dekker, New YorkGoogle Scholar
  19. 19.
    Gomez-Jeria JS, Orellana Í (2016) A theoretical analysis of the inhibition of the VEGFR-2 vascular endothelial growth factor and the anti-proliferative activity against the HepG2 hepatocellular carcinoma cell line by a series of 1-(4-((2- oxoindolin-3-ylidene)amino)phenyl)-3-arylureas. Pharma Chem. 8:476–487Google Scholar
  20. 20.
    Gomez-Jeria JS, Valdebenito-Gamboa J (2015) A quantum-chemical analysis of the antiproliferative activity of N-3-benzimidazolephenylbisamide derivatives against MGC803, HT29, MKN45 and SW620 cancer cell lines. Pharma Chem. 7:103–121Google Scholar
  21. 21.
    Robles-Navarro A, Gómez Jeria J (2016) A quantum-chemical analysis of the relationships between electronic structure and cytotoxicity, GyrB inhibition, DNA supercoiling inhibition and antitubercular activity of a series of quinoline–aminopiperidine hybrid analogues. Pharma Chem. 8:417–440Google Scholar
  22. 22.
    Gomez-Jeria JS, Cassels BK, Saavedra-Aguilar JC (1987) A quantum-chemical and experimental study of the hallucinogen (±)-1-(2,5-dimethoxy-4-nitrophenyl)-2-aminopropane (DON). Eur. J. Med. Chem. 22:433–437CrossRefGoogle Scholar
  23. 23.
    GóMez-Jeria JS, Soto-Morales F, Rivas J, Sotomayor A (2008) A theoretical structure-affinity relationship study of some cannabinoid DERIVATIVES. J. Chil. Chem. Soc. 53Google Scholar
  24. 24.
    Gómez Jeria JS (2013) A new set of local reactivity indices within the Hartree-Fock-Roothaan and density functional theory frameworks. Can. Chem. Trans. 1:25–55CrossRefGoogle Scholar
  25. 25.
    Gómez Jeria JS (2013) Elements of molecular electronic pharmacology1st edn. Ediciones Sokar, Santiago de ChileGoogle Scholar
  26. 26.
    Gómez Jeria JS (1982) Calculation of the nucleophilic superdelocalizability by the CNDO/2 method. J. Pharm. Sci. 71:1423–1424CrossRefGoogle Scholar
  27. 27.
    Gómez Jeria JS (1982) La Pharmacologie Quantique. Boll. Chim. Farm. 121:619–625PubMedGoogle Scholar
  28. 28.
    Gomez-Jeria JS (1983) On some problems in quantum pharmacology I. The partition functions. Int. J. Quantum Chem. 23:1969–1972CrossRefGoogle Scholar
  29. 29.
    Gómez Jeria JS, Flores-Catalán M (2013) Quantum-chemical modeling of the relationships between molecular structure and in vitro multi-step, multimechanistic drug effects. HIV-1 replication inhibition and inhibition of cell proliferation as examples. Can. Chem. Trans. 1:215–237CrossRefGoogle Scholar
  30. 30.
    Gómez-Jeria JS (1989) Modeling the drug-receptor interaction in quantum pharmacology. In: Maruani J (ed) Molecules in physics, chemistry, and biology. Springer Netherlands, Dordrecht, pp 215–231CrossRefGoogle Scholar
  31. 31.
    Gomez-Jeria JS, Sotomayor P (1988) Quantum chemical study of electronic structure and receptor binding in opiates. J. Mol. Struct. THEOCHEM 166:493–498CrossRefGoogle Scholar
  32. 32.
    Kpotin G, Atohoun SYG, Kuevi AU, Kpota-Hounguè A, Mensah J-B, Gómez Jeria JS (2016) A quantum-chemical study of the relationships between electronic structure and trypanocidal activity against Trypanosoma brucei brucei of a series of thiosemicarbazone derivatives. Pharm. Lett. 8:215–222Google Scholar
  33. 33.
    Gómez-Jeria JS, Cornejo-Martínez P (2016) A DFT study of the inhibition of human phosphodiesterases PDE3A and PDE3B by a group of 2-(4-(1H-tetrazol-5-yl)-1H-pyrazol-1-yl)- 4-(4-phenyl)thiazole derivatives. Pharma Chem. 8:329–337Google Scholar
  34. 34.
    Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Montgomery JA Jr, Vreven T, Kudin KN, Burant JC, Millam JM, Iyengar SS, Tomasi J, Barone V, Mennucci B, Cossi M, Scalmani G, Rega N, Petersson GA, Nakatsuji H, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Klene M, Li X, Knox JE, Hratchian HP, Cross JB, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Ayala PY, Morokuma K, Voth GA, Salvador P, Dannenberg JJ, Zakrzewski VG, Dapprich S, Daniels AD, Strain MC, Farkas O, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Ortiz JV, Cui Q, Baboul AG, Clifford S, Cioslowski J, Stefanov BB, Liu G, Liashenko A, Piskorz P, Komaromi I, Martin RL, Fox DJ, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Challacombe M, Gill PMW, Johnson B, Chen W, Wong MW, Gonzalez C, Pople JA (2003) Gaussian 03, Revision B.04. Gaussian, Inc., PittsburghGoogle Scholar
  35. 35.
    Gómez-Jeria JS (2014) D-Cent-QSAR, a program to generate local atomic reactivity indices from Gaussian 03 log files. V.1.0, Santiago de ChileGoogle Scholar
  36. 36.
    Gómez-Jeria JS (2009) An empirical way to correct some drawbacks of Mulliken population analysis (Erratum in: J. Chil. Chem. Soc., 55, 4, IX, 2010). J. Chil. Chem. Soc. 54:482–485CrossRefGoogle Scholar
  37. 37.
    StatSoft, Inc. (2011) STATISTICA (data analysis software system), version 10.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Laboratory of Theoretical Chemistry and Molecular Spectroscopy, Faculty of Sciences and TechniquesUniversity of Abomey - CalaviCotonouBenin
  2. 2.Laboratoire de Chimie Organique StructuraleUniversité Félix Houphouët-BoignyAbidjanCôte d’Ivoire
  3. 3.Quantum Pharmacology Unit, Department of Chemistry, Faculty of SciencesUniversity of ChileSantiagoChile
  4. 4.Laboratoire de Physique et Chimie ThéoriquesUniversité de Lorraine - CNRSNancyFrance

Personalised recommendations