VolSurf analysis of pharmacokinetic properties for several antifungal sesquiterpene lactones isolated from Greek Centaurea sp.
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Sesquiterpene lactones are terpenoid compounds characteristic of the Asteraceae (Compositae) possessing a variety of biological activities, such as cytotoxic, antitumor, antibacterial, and antifungal. The prediction of the pharmacokinetic profile of several antifungal sesquiterpene lactones, isolated from Greek taxa of Centaurea sp., was undertaken in this study using the VolSurf procedure. The molecules were projected on the following pre-calculated ADME models: Caco-2 cell permeability, plasma protein affinity, blood–brain barrier permeation and thermodynamic solubility. The in silico projection revealed a non optimal pharmacokinetic profile for the studied compounds. ADME in silico screening of a semi-synthetic derivatives virtual library has been performed in order to optimize the pharmacokinetic properties. A number of derivatives were proposed as it was predicted to have higher Caco-2 cell permeability, while the pharmacokinetic behaviour regarding BBB penetration, protein binding and solubility was mainly preserved.
KeywordsADME, sesquiterpene lactones, virtual screening, VolSurf
absorption, distribution, metabolism, excretion
blood brain barrier
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We are grateful to Prof. Gabriele Cruciani (Laboratory for Chemometrics, School of Chemistry, University of Perugia, Italy) for providing us the VolSurf program (version 4, Linux, www.moldiscovery.com), and also to Dr. Emanuele Carosati and Dr. Giovanni Cianchetta (same laboratory) for helpful advises. This research was financially supported by the Italian Ministry of Education.
- 12.Cruciani, G., Crivori, P., Carrupt, P.-A. and Testa B., J.␣Mol. Str.: Theochem, 503 (2000) 17Google Scholar
- 14.Cruciani, G., Meniconi, M., Carosati, E., Zamora, I. and Mannhold, R., In Waterbeemd, H., Lennernäs, H. and Artursson, P. (Eds.), VOLSURF: A Tool for Drug ADME-properties Prediction, WILEY-VCH, Weinheim, Germany, 2003, pp. 406–419Google Scholar
- 16.Skaltsa H., Lazari D., Garcia B., Pedro J.R., Sokovic M., Constantinidis T., (2000) Z. Naturforsch. C 55c: 534Google Scholar
- 18.Karioti A., Skaltsa H., Lazari D., Sokovic M., Garcia B., Harvala C., (2002) Z. Naturforsch. C 57c: 75Google Scholar
- 19.Sybyl Molecular Modeling System, version 6. 8. 1; Tripos Assoc.: St. Louis, MOGoogle Scholar
- 22.Fischer, N.H., Olivier, E.J. and Fischer, H.D., In Hertz, W., Grisebach, H., Kirby, G.W. (Eds.), Progress in the Chemistry of Organic Natural Products. Springer-Verlag, Wien, New York, 1979, pp. 47–390Google Scholar
- 23.Seaman F.C., (1982) Bot. Rev. 48: 121Google Scholar
- 25.Robles M., Aregullin M., West J., Rodriguez E., (1995) Planta Med. 61: 199Google Scholar
- 26.Wedge, D.E., Galindo, J.C.G. and Macías, F.A., Phytochemistry, 53 (2000) 747Google Scholar
- 31.Smith C.H., Larner J., Thomas A.M., Kupchan S.M., (1972) Biochim. Biophys. Acta 276: 94Google Scholar
- 34.Oprea T., (2002) Molecules 7: 51Google Scholar
- 36.Koukoulitsa, E., Skaltsa, H., Demetzos, C. and Cruciani, G., 11th Panhellenic Pharmaceutical Congress, Athens, Greece Special Issue of Eur. J. Drug Metabol. Pharmacokinet., 28 (2003) 7Google Scholar
- 37.Koukoulitsa, C., Skaltsa, H. and Cruciani, G., 15th European Symposium on Quantitative Structure-Activity Relationships & Molecular Modelling, Istanbul, Turkey, September 05–10, 2004, proceedings in pressGoogle Scholar