Human soluble (S) and membrane-bound (MB) catechol O-methyltransferase (COMT, EC 2.1.1.6) enzymes have been expressed at sufficiently high levels in Escherichia coli and in baculovirus-infected insect cells to allow kinetic characterization of the enzyme forms. The use of tight-binding inhibitors such as entacapone enabled the estimation of actual enzyme concentrations and, thereby, comparison of velocity parameters, substrate selectivity, and regioselectivity of the methylation of both enzyme forms. Kinetics of the methylation reaction of dopamine, (-)-noradrenaline, L-dopa, and 3,4-dihydroxybenzoic acid was studied in detail. Here, the catalytic number (Vmax) of S-COMT was somewhat higher than that of MB-COMT for all four substrates. The Km values varied considerably, depending on both substrate and enzyme form. S-COMT showed about 15 times higher Km values for catecholamines than MB-COMT. The distinctive difference between the enzyme forms was also the higher affinity of MB-COMT for the coenzyme S-adenosyl-L-methionine (AdoMet). The average dissociation constants Ks were 3.4 and 20.2 microM for MB-COMT and S-COMT, respectively. Comparison between the kinetic results and the atomic structure of S-COMT is presented, and a revised mechanism for the reaction cycle is discussed. Two recently published human COMT cDNA sequences differed in the position of S-COMT amino acid 108, the residue being either Val-108 [Lundström et al. (1991) DNA Cell. Biol. 10, 181-189] or Met-108 [Bertocci et al. (1991) Proc. Natl. Acad. Sci. U.S.A. 88, 1416-1420].(ABSTRACT TRUNCATED AT 250 WORDS)

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A method for predicting the aqueous solubility of drug compounds was developed based on topological indices and artificial neural network (ANN) modeling. The aqueous solubility values for 211 drugs and related compounds representing acidic, neutral, and basic drugs of different structural classes were collected from the literature. The data set was divided into a training set (n = 160) and a randomly chosen test set (n = 51). Structural parameters used as inputs in a 23-5-1 artificial neural network included 14 atom-type electrotopological indices and nine other topological indices. For the test set, a predictive r2 = 0.86 and s = 0.53 (log units) were achieved.

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Molecular mechanisms determining the turn-over rate and specificity of catechol O-methylation were studied by combining enzyme kinetic measurements, computational modeling of substrate properties and fitting ligands in a 3D model of the active site of the enzyme. Enzyme kinetic measurements were carried out for 46 compounds, including most clinically used catechol drugs, by using recombinant human soluble catechol O-methyltransferase (COMT). The most important mechanism decreasing the turnover rate and increasing affinity was the electron withdrawing effect of substituents. Several other mechanisms by which substituents affected reactivity and affinity were identified. Highest turnover rates were determined for unsubstituted catechol and pyrogallol. Pyrogallol derivatives generally seemed to be more specific substrates than catechols. Catecholestrogens were the most specific endogenous substrates, whereas catecholamines were rather poor substrates. Among the catechol drugs used in the L-DOPA treatment of Parkinson's disease, the COMT inhibitors entacapone and tolcapone were not methylated, whereas the DOPA decarboxylase inhibitor benserazide was 15 times more specific substrate than L-DOPA, the target of COMT inhibition. The structure-activity relationships found allow the prediction of reactivity, affinity, and specificity with useful accuracy for catechols with a wide range of structures and properties. The knowledge can be used in the evaluation of metabolic interactions of endogenous catechols, drugs and dietary catechols, and in the designing of drugs with the catechol pharmacophore.