We introduce a new method for determining pharmacophore or active site geometries by analysis of the structures of a series of active compounds. The method, constrained search, and the key concepts on which it is based, is described and illustrated by its application to 28 potent inhibitors of angiotensin-converting enzyme (ACE). The data set is one utilized by Mayer et al. [J. Comput.-Aided Mol. Design, 1 (1987) 3-16] to determine a unique geometry for the active site. Our experiment validated the previously reported results, obtained by a systematic search, while reducing the computer time requirement by more than two orders of magnitude. The experiment also identified a previously unrecognized alternative active site geometry for the ACE series.
Constrained systematic search was used in an exhaustive conformational analysis of a structurally diverse set of substance P (SP) antagonists to identify a unique hypothesis for their bound conformation at the neurokinin-1 receptor. In this conformation, two aromatic groups essential for high affinity adopt a perpendicular or edge-on arrangement. This pharmacophore hypothesis for the receptor-bound conformation was used in a comparative molecular field analysis (CoMFA) of an expanded set of SP antagonists, and the predictive ability of the resulting three-dimensional quantitative structure-activity relationship (3D-QSAR) was evaluated against a test set of SP antagonists different from those in the training set. This CoMFA model based on the Constrained Search alignment yielded significant cross-validated, conventional, and predictive r2 values equal to 0.70, 0.93, and 0.82, respectively. For comparison, the SP antagonists were forced into an alternative poorer alignment in which the two aromatic rings were parallel and then subjected to a CoMFA analysis. Both the parallel and perpendicular arrangements of the aromatic rings are seen in X-ray structures of SP antagonists and have been proposed as candidates for the receptor-bound conformation. The parallel (or stacked) conformation yielded a poorer correlation with a cross-validated r2 = 0.57, a conventional r2 = 0.90, and a predictive r2 = 0.78. Our results indicate that although both alignments could generate a reasonable CoMFA correlation, the stacked conformation is unlikely to be the receptor-bound conformation, as the covalent structure of the antagonists precludes a common geometry in which the aromatic rings are stacked.
Three new strategies for sampling the conformation space accessible to a series of structurally diverse, flexible molecules are defined and compared to samples obtained using a fixed-grid torsion angle sampling strategy. A set of 28 potent inhibitors of angiotensin converting enzyme selected by Mayer et al. [J. Comput.-Aided Mol. Design, 1 (1987) 3] and the unrestricted active-site model proposed by Waller et al. [to be published] are used to produce a realistic experimental setting. We modified our Constrained Search algorithm [Dammkoehler et al., J. Comput.-Aided Mol. Design, 3 (1989) 3] to support these new sampling strategies, performing a series of 64 simulations (search experiments) and generating a large set of sterically allowed conformations. In each experiment, we systematically vary the internal torsion angles in each molecule using one of the sampling strategies. The common orientations of preselected functional groups thought to represent those dominating the interaction with the enzyme and presented by the set of molecules are classified and recorded for each experiment. Pairwise distances between groups are used to characterize the geometry of the common orientations. The results of each experiment, represented by a set of distance values, are compared and combined to evaluate the completeness of the conformational sampling. While no pure strategy or single search experiment was found to be adequate to fully explore the set of common sterically allowed conformations, a new sampling technique, called adaptive radial sampling, is shown to be significantly more complete than the commonly used fixed grid sampling.
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