Structure-based shape pharmacophore modeling for the discovery of novel anesthetic compounds.

Current anesthetics, especially the inhaled ones, have troublesome side effects and may be associated with durable changes in cognition. It is therefore highly desirable to develop novel chemical entities that reduce these effects while preserving or enhancing anesthetic potency. In spite of progress toward identifying protein targets involved in anesthesia, we still do not have the necessary atomic level structural information to delineate their interactions with anesthetic molecules. Recently, we have described a protein target, apoferritin, to which several anesthetics bind specifically and in a pharmacodynamically relevant manner. Further, we have reported the high resolution X-ray structure of two anesthetic/apoferritin complexes (Liu, R.; Loll, P. J.; Eckenhoff, R. G. FASEB J. 2005, 19, 567). Thus, we describe in this paper a structure-based approach to establish validated shape pharmacophore models for future application to virtual and high throughput screening of anesthetic compounds. We use the 3D structure of apoferritin as the basis for the development of several shape pharmacophore models. To validate these models, we demonstrate that (1) they can be used to effectively recover known anesthetic agents from a diverse database of compounds; (2) the shape pharmacophore scores afford a significant linear correlation with the measured binding energetics of several known anesthetic compounds to the apoferritin site; and (3) the computed scores based on the shape pharmacophore models also predict the trend of the EC(50) values of a set of anesthetics. Therefore, we have now obtained a set of structure-based shape pharmacophore models, using ferritin as the surrogate target, which may afford a new way to rationally discover novel anesthetic agents in the future.