Chapter 29. Receptor Modeling by Distance Geometry

Abstract

Publisher Summary Distance geometry is a general molecular model-building method known for determining the three-dimensional solution structures of peptides, proteins, and nucleic acids from nuclear overhauser effect (NOE) distance measurements. It has also been applied to the models of proteins and receptors and the interaction of small molecules with the receptors. A recently published comprehensive review of distance geometry and its application to receptor modeling emphasizes their distance geometry quantitative structure–activity relationship (QSAR) approaches. This chapter discusses the additional distance geometry approaches that have application in receptor modeling and distance geometry QSAR method, protein structure modeling, drug receptor docking, and pharmacophore modeling using the ensemble approach. Crippen applied distance geometry to the problem of three-dimensional receptor mapping. Ghose and Crippen have reviewed the approach in detail. Ghose and Crippen's method proposed the geometric requirements of the receptor site based on the experimental data of binding affinities of a series of ligands that may be conformationally flexible and may be hypothesized binding modes for each ligand. The result was a low-resolution, three-dimensional model of the receptor binding site, which was described as a series of points in space (site points) that interact with specific ligand atoms or groups of atoms (ligand points). Each ligand point was described by atom-centered physicochemical properties (molar refractivity, hydrophobicity, and partial charge). A specific interaction energy was assigned to each site point—ligand point interaction by a modified quadratic programming optimization procedure—yielding a quantitative prediction of the binding affinity of each ligand to the site model. The chapter discusses Voronoi binding site models. Distance geometry software is now more readily available, along with a steadily increasing number of applications and publications that demonstrate molecular models involving drug–receptor docking, pharmacophore modeling, protein structure prediction, and conformational analysis.