A molecular dynamics approach to receptor mapping: Application to the 5HT sub(3) and beta sub(2)-adrenergic receptors

A molecular dynamics-based approach to receptor mapping is proposed, based on the method of Rizzi (Rizzi, J. P.; et al. J. Med. Chem. 1990, 33, 2721). In Rizzi's method, the interaction energy between a series of drug molecules and probe atoms (which mimic functional groups on the receptor, such as hydrogen bond donors) was calculated. These interactions were calculated on a three-dimensional grid within a molecular mechanics framework, and the minima in the grid were associated with the binding site on the receptor. In this extension, dummy atoms, bonded to the drug with appropriate molecular mechanics parameters, were placed at these minima. The distances between the dummy atom sites were monitored during molecular dynamics simulations and plotted as distance distribution functions. Important distances within the receptor became apparent, as drugs with a common mode of binding share similar peaks in the distance distribution functions. In the case of specific 5HT sub(3) ligands, the important donor-acceptor distance within the receptor has a range of ca. 7.9-8.9 angstrom. In the case of specific beta sub(2)-adrenergic ligands, the important donor-acceptor distances within the receptor lie between ca. 7-9 angstrom and between 8 and 10 angstrom. These distance distribution functions were used to assess three different models of the beta sub(2)-adrenergic G-protein-coupled receptor. The comparison of the distance distribution functions for the simulation with the actual donor-acceptor distances in the receptor models suggested that two of the three receptor models were much more consistent with the receptor-mapping studies. These receptor-mapping studies gave support for the use of rhodopsin, rather than the bacteriorhodopsin template, for modeling G-protein-coupled receptors but also sounded a warning that agreement with binding data from site-directed mutagenesis experiments does not necessarily validate a receptor model.