Article ID Journal Published Year Pages File Type
1222504 Journal of Pharmaceutical and Biomedical Analysis 2012 8 Pages PDF
Abstract

Quantitative structure–retention relationships (QSRR) were proposed for Separon SGX C18 and Separon SGX Phenyl columns using physico-chemical molecular descriptors for the compounds, which are potential local anaesthetic drugs. Chemometrical methods were used for the QSRR studies of the HPLC retention factor k of 59 esters of alkoxyphenylcarbamic acid, which exhibit surface and/or infiltration anaesthetic activity. Four separation systems were used: phenyl column and acetonitrile/water mobile phase, phenyl column and methanol/water mobile phase, C18 column and acetonitrile/water mobile phase, and C18 column and methanol/water mobile phase. The values of log P and log S and 13C and 1H NMR chemical shifts were simulated and utilized in calculating the corresponding QSRR models and predicting the retention factors by artificial neural networks (ANN). In addition, principal component analysis and cluster analysis were used for a closer characterization of alkoxyphenylcarbamic acid esters. The proposed ANN models, based on optimally selected species descriptors, showed a high degree of correlation between k predicted and k measured. The intercepts and the slopes of the obtained dependences were close to the theoretically expected values of 0 and 1, respectively.

► A joint use of several chemometrical techniques and their joint interpretation. ► Comparison of the results of sensitivity analysis and correlation analysis. ► Evaluation of relationships between the selected retention factors and lipophilicity (defining the potential drug distribution between n-octanol and water), which allows its substitution by the retention factor found for the optimal separation systems. ► A very accurate prediction of retention factors by the ANN methodology.

Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
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