Hierarchical clustering analysis of flexible GBR 12909 dialkyl piperazine and piperidine analogs

Singular value decomposition analysis of the torsional angles of dopamine reuptake inhibitor GBR 12909 analogs: effect of force field and charges

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis of large, flexible molecules, such as the dopamine reuptake inhibitor GBR 12909 (1), is complicated by the fact that they can take on a wide range of closely-related conformations. The first step in the analysis is to classify the conformers into groups. Over 600 conformers each of a piperazine (2) and piperidine (3) analog of 1 were generated by random search conformational analysis using the Merck Molecular Force Field (MMFF94). Singular value decomposition (SVD) was used to group the conformers of 2 and 3 by the similarity of their non-ring torsional angles. SVD uncovered subtle differences in their conformer populations due to that fact that the conformers separate along different principal components, and ultimately to the fact that different torsional angles are the chief contributors to these components. The results were compared to our previous SVD analysis (Fiorentino, et al., Journal of Computational Chemistry, 2006, 27, 609-620) of conformer populations of 2 and 3 generated by the Tripos force field and Gasteiger-Hückel charges. Except for the dominant contribution of angle B3 to principal component 8 seen with both force fields, the angles which are chiefly responsible for the grouping of the conformers of 2 and 3 are different with both force fields. This illustrates that SVD is useful in identifying unique groupings of conformers in large data sets of flexible molecules-a first step in selecting representative conformers for 3D-QSAR modeling studies.

Conformational analysis of piperazine and piperidine analogs of GBR 12909: stochastic approach to evaluating the effects of force fields and solvent

Analogs of the flexible dopamine reuptake inhibitor, GBR 12909 (1), may have potential utility in the treatment of cocaine abuse. As a first step in the 3D-QSAR modeling of the dopamine transporter (DAT)/serotonin transporter (SERT) selectivity of these compounds, we carried out conformational analyses of two analogs of 1: a piperazine (2) and a related piperidine (3). Ensembles of conformers consisting of local minima on the potential energy surface of the molecule were generated in the vacuum phase and in implicit solvent by random search conformational analysis using the Tripos and MMFF94 force fields. Some differences were noted in the conformer populations due to differences in the treatment of the tertiary amine nitrogen and ether oxygen atom types by the force fields. The force fields also differed in their descriptions of internal rotation around the C(sp³)-O(sp³) bond proximal to the bisphenyl moiety. Molecular orbital calculations at the HF/6-31G(d) and B3LYP/6-31G(d) levels of C-O internal rotation in model compound (5), designed to model the effect of the proximity of the bisphenyl group on C-O internal rotation, showed a broad region of low energy between -60° to 60° with minima at both -60° and 30° and a low rotational barrier at 0°, in closer agreement with the MMFF94 results than the Tripos results. Molecular mechanics calculations on model compound (6) showed that the MMFF94 force field was much more sensitive than the Tripos force field to the effects of the bisphenyl moiety on C-O internal rotation.

Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor

Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule-specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 31, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of the corresponding rigid-body (or "planes") parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.

Quantitative conformationally sampled pharmacophore for delta opioid ligands: reevaluation of hydrophobic moieties essential for biological activity

Recent studies have indicated several therapeutic applications for delta opioid agonists and antagonists. To exploit the therapeutic potential of delta opioids developing a structural basis for the activity of ligands at the delta opioid receptor is essential. The conformationally sampled pharmacophore (CSP) method (Bernard et al. J. Am. Chem. Soc. 2003, 125, 3103-3107) is extended here to obtain quantitative models of delta opioid ligand efficacy and affinity. Quantification is performed via overlap integrals of the conformational space sampled by ligands with respect to a reference compound. Iterative refinement of the CSP model identified hydrophobic groups other than the traditional phenylalanine residues as important for efficacy and affinity in DSLET and ICI 174 864. The obtained models for a structurally diverse set of peptidic and nonpeptidic delta opioid ligands offer good predictions with R2 values>0.9, and the predicted efficacy for a set of test compounds was consistent with the experimental values.

DAT/SERT selectivity of flexible GBR 12909 analogs modeled using 3D-QSAR methods

The dopamine reuptake inhibitor GBR 12909 (1-{2-[bis(4-fluorophenyl)methoxy]ethyl}-4-(3-phenylpropyl)piperazine, 1) and its analogs have been developed as tools to test the hypothesis that selective dopamine transporter (DAT) inhibitors will be useful therapeutics for cocaine addiction. This 3D-QSAR study focuses on the effect of substitutions in the phenylpropyl region of 1. CoMFA and CoMSIA techniques were used to determine a predictive and stable model for the DAT/serotonin transporter (SERT) selectivity (represented by pK(i) (DAT/SERT)) of a set of flexible analogs of 1, most of which have eight rotatable bonds. In the absence of a rigid analog to use as a 3D-QSAR template, six conformational families of analogs were constructed from six pairs of piperazine and piperidine template conformers identified by hierarchical clustering as representative molecular conformations. Three models stable to y-value scrambling were identified after a comprehensive CoMFA and CoMSIA survey with Region Focusing. Test set correlation validation led to an acceptable model, with q(2)=0.508, standard error of prediction=0.601, two components, r(2)=0.685, standard error of estimate=0.481, F value=39, percent steric contribution=65, and percent electrostatic contribution=35. A CoMFA contour map identified areas of the molecule that affect pK(i) (DAT/SERT). This work outlines a protocol for deriving a stable and predictive model of the biological activity of a set of very flexible molecules.