A frequently encountered problem in the design of enzyme inhibitors and other biologically active molecules is the identification of molecular frameworks to serve as templates or linking units that can position functional groups in specific relative orientations. The program CAVEAT was designed to address this problem by searching 3D databases for such molecular fragments. Key innovations introduced in CAVEAT are a focus on relationships between bonds and the provision of automated methods to identify and classify structural frameworks. Performance has been a particular concern in formulating CAVEAT, since it is intended to be used in an interactive manner. The focus in this report is the design and implementation of the principal algorithms and the performance achieved.

A rapid and convenient method for determining the backbone conformation of cyclic peptides results from the combination of ID 1H NMR information and molecular modeling. Φ, Angle torsional constraints calculated from 3JHN,Hx coupling constants are used to determine the position of multiple‐welled potential energy penalty functions that are imposed on the force field used in the structure refinement (Amber* with GB/SA solvation model). Monte Carlo searches and minimizations lead to a collection of structures that are clustered by backbone similarity and then filtered according to hydrogen‐bonding constraints determined by the chemical shift temperature dependencies of the amide protons. This approach was applied to five cyclic peptides whose structures had been determined previously using more extensive 2D NMR techniques, and the importance of the torsional. H‐bonding, and solvation restraints were assessed. For the four peptides that adopt a predominant conformation, this method reproduced the reported structures closely; lack of convergence for the fifth structure reflected the multiple backbone conformations that this macrocycle adopts. © Munksgaard 1996.

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