3. FOOD ChEMISTRy & bIOTEChNOLOGy 3.1. Lectures
3. FOOD ChEMISTRy & bIOTEChNOLOGy 3.1. Lectures
3. FOOD ChEMISTRy & bIOTEChNOLOGy 3.1. Lectures
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Chem. Listy, 102, s265–s1311 (2008) Food Chemistry & Biotechnology<br />
pharmacological activity. This evidence was clearly described<br />
in lipid theory advanced by Meyer and Overton. According<br />
to this theory, log P is a measure of hydrophobicity which is<br />
important for the penetration and distribution of the drug, but<br />
also for the interaction of drug with receptors. Therefore, it<br />
can be suggested that lipophilic properties have to be checked<br />
for designing of potent antifungal agents as they are deciding<br />
factors for its activity.<br />
Fig. 2. Plot of residual values against the experimentally observed<br />
log 1/c MIC values<br />
Conclusions<br />
QSAR analysis was performed to estimate the quantitative<br />
effects of the lipophilicity parameter, logP, of the different<br />
substituted 2-amino and 2-methylbenzimidazole derivatives<br />
on their antifungal activity against Saccharomyces<br />
cerevisiae. log P values were calculated for each molecule,<br />
and high-quality mathematical model relating the inhibitory<br />
activity, log 1/c MIC , and log P was defined . . For the estimation<br />
of the predictive ability of this model, the cross-validation<br />
statistical technique was applied. Comparison of the linear,<br />
quadratic and cubic relationships showed that the cubic equation<br />
was the most appropriate for prediction of antifungal<br />
activity of the investigated class of molecules. It is concluded<br />
that strong influence of the partition coefficient, log P, is<br />
important for the inhibitory activity and this parameter is usually<br />
related to pharmacological activity. The obtained mathematical<br />
model was used to predict antifungal activity of the<br />
benzimidazoles investigated and close agreement between<br />
experimental and predicted values was obtained. It indicates<br />
that this model can be successfully applied to predict the antifungal<br />
activity of these class of molecules.<br />
This work has been supported by Ministry of Science<br />
and Environment Protection of the Republic of Serbia as are<br />
the part of the project No. 142028<br />
REFEREnCES<br />
1. Goker H., Alp M., Yildiz S.: Molecules 10, 1377 (2000).<br />
2. nguyen P. T. M., Baldeck J. D., Olsson J., Marquis R. E.:<br />
Oral Microbiol. Immunol. 20, 93 (2005).<br />
s756<br />
<strong>3.</strong> Podunavac-Kuzmanović S. O., Leovac V. M., Perišić-Janjić<br />
n. U., Rogan J., Balaž J.: J. Serb. Chem. Soc. 64, 381<br />
(1999).<br />
4. Podunavac-Kuzmanović S. O., Cvetković D.: J. Serb.<br />
Chem. Soc. 75, 381 (2007).<br />
5. Ayhan-Kilcigil G., Altanlar n.: Turk. J. Chem. 30, 223<br />
(2006).<br />
6. Boiani M., Gonzalez M.: J. Med. Chem. 5, 409 (2005).<br />
7. Garuti L., Roberti M., Cermelli C.: Bioorg. Medicinal<br />
Chem. Letter 9, 2525 (1999).<br />
8. Kazimierczuk Z., Upcroft J. A., Upcroft P., Gorska A., Starosciak<br />
B., Laudy A.: Acta Biochim. Polon. 49, 185 (2002).<br />
9. Akbay A., Oren I., Temiz-Arpaci O., Aki-Sener E., Yalcin I.:<br />
Arzneim.-Forcsh./Drug Res. 53, 266 (2003).<br />
10. Bevan D.: QSAR and Drug Design. network Science,<br />
http://www.netsci.org/Science/Compchem/feature12.html.<br />
11. QSAR, The Australian Computational Chemistry via the<br />
InternetProject,www.chem.swin.edu.au/modukes/mod4/<br />
index.html.<br />
12. Hansch C.: J. Med. Chem. 19, 1 (1976).<br />
1<strong>3.</strong> Vasanthanathan P., Lakshmi M., Babu M. A., Gupta A. K.,<br />
Kaskhedikar S. G.: Chem. Pharm. Bull. 54, 583 (2006).<br />
14. Melagraki G., Afantitis A., Sarimveis H., Igglessi-Markopoulou<br />
O., Supuran C. T.: Bioorg. Med. Chem. 14, 1108<br />
(2006).<br />
15. Podunavac-Kuzmanović S. O., Markov S. L., Barna D. J.:<br />
J. Theor. Comp. Chem. 6, 687 (2007).<br />
16. Podunavac-Kuzmanović, S. O., Barna, D. J., Cvetković<br />
D. M.: Acta Periodica Technol. 38, 139 (2007).<br />
17. Leo A., Hansch C., Elkins D.: Chem. Rev. 71, 525 (1971).<br />
18. nasal A., Siluk D., Kaliszan R.: Curr. Med. Chem. 10, 381<br />
(2003).<br />
19. Tiperciuc B, Sarbu C.: J. Liq. Chrom. Rel. Technol. 29,<br />
2257 (2006).<br />
20. Perišić-Janjić n. U., Podunavac-Kuzmanović S. O.: J.<br />
Planar Chromatogr. 21, 135 (2008).<br />
21. Perišić-Janjić n. U., Podunavac-Kuzmanović S. O., Balaž,<br />
J. S., Vlaović Dj.: J. Planar Chromatogr. 13, 123 (2000).<br />
22. Slawik T., Paw B.: J.Liq. Chromatogr. 27, 1043 (2004).<br />
2<strong>3.</strong> Vlaović Đ., Čanadanović-Brunet J., Balaž J., Juranić I., Đoković<br />
D., Mackenzie K.: Biosci. Biotech. Biochem. 56, 199<br />
(1992).<br />
24. national Committee for Clinical Laboratory Standards,<br />
nCCLS Approval Standard Document M2-A7. Vilanova,<br />
Pa, U.S.A. 2000.<br />
25. national Committee for Clinical Laboratory Standards,<br />
NCCLS Approval Standard Document M7-A5. Vilanova,<br />
Pa, U.S.A. 2000.<br />
26. CS. Chem. Office, Version 7.0, Cambridge Soft Corporation,<br />
100 Cambridge Park Drive, Cambridge, MA 02140-<br />
2317, U.S.A. 2001.<br />
27. www.ncss.com.<br />
28. Lien E.J.: Side Effects and Drug Design. Marcel Dekker,<br />
new York 1987.<br />
29. Jalali-Heravi M., Kyani A.: J. Chem. Inf. Comput. Sci. 44,<br />
1328 (2004).