QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP STUDY ON THE INHIBITORY ACTIVITY OF COPPER SCHIFF BASE COMPLEXES AGAINST CANDIDA ALBICAN
DOI :
https://doi.org/10.18540/jcecvl5iss1pp0111-0124Mots-clés :
Candida albican, Copper Schiff base complex, Genetic Function Algorithm, QSARRésumé
Quantitative Structure Activity Relationship (QSAR) study was performed on Copper Schiff base complexes. Multiple Linear Regression analysis and genetic function algorithms was employed to derive QSAR model for better activity. The derived QSAR model having Squared Correlation Coefficient R2 = 0.8345, Cross Validation Squared Correlation Coefficient Q2 = 0.6681 and predicted R squared (R2pred ) = 0.5980. The predictive ability of the derived model was also confirmed by internal and external cross validation techniques. The QSAR model indicate that the descriptors (MATS4p) Moron autocorrelation of lag 4 weighed by polarizability,(RCI) Ring Complexity index, (G2m) 2nd component symmetry directional WHIM index/weighted by mass, BI0 [N-O] Presence/absence of N-O at topological distance 10 and (nF) Number of Fluorine atoms plays an important role in predicting the activities against anti-candida albican. The result obtained in this study was used in designing more potent Copper Complexes as anti-candida albican agents.
Téléchargements
Références
Atkinson, A.C.Plot, Transformation and Regression ,Clarendon Press, Oxford UK (1985).
Creaven, B.S., Devereux, M., Karcz, D., Kellett, A., McCann, M., Noble, A., Walsh, M., 2009. Copper (II) complexes of coumarin-derived Schiff bases and their anti-Candida activity. J. Inorg. Biochem. 103, 1196–1203.
Creaven, B.S., Duff, B., Egan, D.A., Kavanagh, K., Rosair, G., Thangella, V.R., Walsh, M., 2010. Anticancer and antifungal activity of copper (II) complexes of quinolin-2 (1H)-one-derived Schiff bases. Inorganica Chim. Acta 363, 4048–4058.
Kim, J., Sudbery, P., 2011. Candida albicans, a major human fungal pathogen. J. Microbiol. 49, 171.
Kovala-Demertzi, D., 2006. Recent advances on non-steroidal anti-inflammatory drugs, NSAIDs: organotin complexes of NSAIDs. J. Organomet. Chem. 691, 1767–1774.
Kumaran, J.S., Priya, S., Muthukumaran, J., Jayachandramani, N., Mahalakshmi, S., 2013. Journal of Chemical and Pharmaceutical Research, 2013, 5 (7): 56-69. J. Chem. Pharm. Res. 5, 56–69.
Motta, L., Almeida, W., 2011. Quantitative structure-activity relationships (QSAR) of a series ketone derivatives as anti candida albicans. Int. J. Drug Discov. 3, 100–117.
Raman, N., Joseph, J., Velan, A., Pothiraj, C., 2006. Antifungal activities of biorelevant complexes of copper (II) with biosensitive macrocyclic ligands. Mycobiology 34, 214–218.
Rathod, A., 2011. Antifungal and Antibacterial activities of Imidazolylpyrimidines derivatives and their QSAR Studies under Conventional and Microwave-assisted. Int J PharmTech Res 3, 1942–1951.
Tenover, F.C., 2006. Mechanisms of antimicrobial resistance in bacteria. Am. J. Infect. Control 34, S3–S10.
Tropsha, A. (2010). Best practices for QSAR model development, validation, and exploitation. Molecular Informatics, 29(6?7), 476-488.
Tropsha, A., Gramatica, P., & Gombar, V. K. (2003). The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci, 22(1), 69-77.
Veerasamy, R., Rajak, H., Jain, A., Sivadasan, S., Varghese, C.P., Agrawal, R.K., 2011. Validation of QSAR models-strategies and importance. Int. J. Drug Des. Discov. 3, 511–519.
Téléchargements
Publiée
Comment citer
Numéro
Rubrique
