QUANTITATIVE MOLAR ABSORPTIVITY-STRUCTURE RELATIONSHIPS OF CERTAIN CATECHOLAMINES

Determination of the molar absorptivity of NADH.

The molar absorptivity of NADH at 340 nm has been determined by an indirect procedure in which high-purity glucose is phosphorylated by ATP in the presence of hexokinase, coupled to oxidation of the glucose-6-phosphate by NAD+ in the presence of glucose-6-phosphate dehydrogenase. The average value from 85 independent determinations is 6317 liter mol-1 cm-1 at 25 degrees C and pH 7.8. The overal...

Quantitative Structure - Activity Relationships Study of Carbonic Anhydrase Inhibitors Using Logistic Regression Model

Binary Logistic Regression (BLR) has been developed as non-linear models to establish quantitative structure- activity relationships (QSAR) between structural descriptors and biochemical activity of carbonic anhydrase inhibitors. Using a training set consisted of 21 compounds with known ki values, the model was trained and tested to solve two-class problems as active or inactive on the basi...

History of Quantitative Structure-Activity Relationships

Development of quantitative structure-pharmacokinetic relationships.

Quantitative structure-activity relationships (QSAR) relating biological activity to physiochemical descriptors have been successfully used for a number of years. It is also long recognized that pharmacokinetic parameters may play an important and even determinant role in drug action. This prompted several researchers to focus attention to pharmacokinetic parameters as potential descriptors in ...

Nonlinear Prediction of Quantitative Structure-Activity Relationships

Predicting the log of the partition coefficient P is a long-standing benchmark problem in Quantitative Structure-Activity Relationships (QSAR). In this paper we show that a relatively simple molecular representation (using 14 variables) can be combined with leading edge machine learning algorithms to predict logP on new compounds more accurately than existing benchmark algorithms which use comp...