ABSTRACT:Medetomidine is a chiral imidazole derivate whose dextroenantiomer is pharmacologically active.

Three-dimensional QSAR models with different charge calculation methods (MOPAC-AM1-ESP, MOPAC-AM1-Coulson and Gasteiger-Hückel) were developed for predicting all three enzyme kinetic parameters Km, Vmax and Vmax/Km for catecholic substrates of human soluble catechol O-methyltransferase (S-COMT). The empirical parameters of 45 substrates were correlated to the steric and electronic molecular fields of the substrates utilizing Comparative Molecular Field Analysis (CoMFA). Alignment rules for CoMFA were developed based on the catalytic mechanism and crystal structure of S-COMT, and the analysis was optimized using an all-space search technique. Leave-one-out and leave-n-out cross-validation (with 5 and 10 cross-validation groups) was carried out, and all developed models proved to be statistically significant with q2 values up to 0.84. The models based on MOPAC charge calculations predicted the empirical values clearly better than the Gasteiger-Hückel method. The derived CoMFA coefficient contour maps of steric and electrostatic interactions correlated clearly with the S-COMT crystallographic structures.

A structure-based comparison of the ligand-binding domains of 35 nuclear receptors from five different subfamilies is presented. Their ligand and coactivator binding sites are characterized using knowledge-based contact preference fields for hydrophobic and hydrophilic interactions implemented in the MOE modeling environment. Additionally, for polar knowledge-based field points the preference for negative or positive electrostatic interactions is estimated using the Poisson-Boltzmann equation. These molecular-interaction fields are used to cluster the nuclear receptor family based on similarities of their binding sites. By analyzing the similarities and differences of hydrophobic and polar fields in binding pockets of related receptors it is possible to identify conserved interactions in ligand and coactivator binding pockets, which support e.g. design of specific ligands during lead optimization or virtual screening as docking filter. Examples of remarkable similarities between ligand binding sites of members from phylogenetically different nuclear receptor families (RXR, RAR, HNF4, NR5) and differences between closely related subtypes (LXR, RAR, TR) are discussed in more detail. Significant similarities and differences of coactivator binding sites are shown for NR3Cs, LXRs and PPARs.

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Three-dimensional QSAR models were developed for predicting kinetic Michaelis constant (K(m)) values for phenolic substrates of human catecholamine sulfating sulfotransferase (SULT1A3). The K(m) values were correlated to the steric and electronic molecular fields of the substrates utilizing Comparative Molecular Field Analysis (CoMFA). The evaluated SULT1A3 substrate data set consisted of 95 different substituted phenols, catechols, catecholamines, steroids, and related structures for which the K(m) values were available. The data set was divided in three different subgroups in the initial analysis: (1). for the first CoMFA model substrates with only one reacting hydroxyl group were selected (n = 51), (2).the second model was build with structurally rigid substrates (n = 59), and (3). finally all substrates of the data set were included in the analysis (n = 95). Substrate molecules were aligned using the aromatic ring and the reacting hydroxyl group as a template. After the initial analysis different substrate alignment rules based on the existing knowledge of the SULT1A3 active site structure were evaluated. After this optimization a final CoMFA model was built including all 95 substrates of the data set. Cross-validated q(2) values (leave-one-out and leave-n-out) and coefficient contour maps were calculated for all derived CoMFA models. All four CoMFA models were statistically significant with q(2) values up to 0.624. These predictive QSAR models will provide us information about the factors that affect substrate binding at the active site of human catecholamine sulfotransferase SULT1A3.