tetano
Editor, Senior Moderator
Res Pharm Sci. 2011 Jan;6(1):23-33.
Application of different chemometric tools in QSAR study of azolo-adamantanes against influenza A virus.
Karbakhsh R, Sabet R.
Source
Department of Chemistry, Faculty of Advanced Sciences and Technology, Pharmaceutical Sciences Branch, Islamic Azad University, Tehran, I.R.Iran.
Abstract
Quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (FA-MLR), principle component regression analysis (PCRA), and genetic algorithm-partial least squares GA-PLS. The FA-MLR describes the effect of geometrical and quantum indices on enzyme inhibition activity of the studied molecules. The quality of PCRA equation was found to be better than those derived from FA-MLR. GA-PLS analysis indicated that the topological (IC4 and MPC06), constitutional (nf) and geometrical (G (N..S] parameters were the most significant ones on influenza A virus activity. Comparison of the different statistical methods employed revealed that GA-PLS represented superior results and it could explain and predict 85% and 77% of variances in the pIC(50) data, respectively.
PMID:
22049275
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/22049275
Application of different chemometric tools in QSAR study of azolo-adamantanes against influenza A virus.
Karbakhsh R, Sabet R.
Source
Department of Chemistry, Faculty of Advanced Sciences and Technology, Pharmaceutical Sciences Branch, Islamic Azad University, Tehran, I.R.Iran.
Abstract
Quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (FA-MLR), principle component regression analysis (PCRA), and genetic algorithm-partial least squares GA-PLS. The FA-MLR describes the effect of geometrical and quantum indices on enzyme inhibition activity of the studied molecules. The quality of PCRA equation was found to be better than those derived from FA-MLR. GA-PLS analysis indicated that the topological (IC4 and MPC06), constitutional (nf) and geometrical (G (N..S] parameters were the most significant ones on influenza A virus activity. Comparison of the different statistical methods employed revealed that GA-PLS represented superior results and it could explain and predict 85% and 77% of variances in the pIC(50) data, respectively.
PMID:
22049275
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/22049275