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Prediction of immobilized artificial membrane‐liquid chromatography retention of some drugs from their molecular structure descriptors and LFER parameters
Author(s) -
Fatemi Mohammad Hossein,
Shamseddin Hoda
Publication year - 2009
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/jssc.200900367
Subject(s) - taft equation , chemistry , molecular descriptor , linear regression , chromatography , biological system , quantitative structure–activity relationship , statistics , mathematics , stereochemistry , substituent , biology
In this work multiple linear regression (MLR) was carried out for the prediction of immobilized artificial membrane (IAM) retention factors of 40 basic and neutral drugs in two mobile phase compositions. We developed some MLR models by using linear free energy relationships (LFER) parameters and also theoretically derived molecular descriptor. Root mean square error of MLR model in prediction of log k wPBS IAM and k wMOPS IAM are 0.332 and 0.351, respectively, while these values are 0.371 and 0.500 for LFER models. Inspections to these values indicate that the statistical parameters of MLR models are better than LFER models. The credibility of MLR models was evaluated by using leave‐many‐out cross‐validation and y‐scrambling procedures. The results of these tests indicate the applicability of theoretically derived molecular descriptors and LFER parameters prediction of IAM retention of drugs.