Modeling the 3D structure of GPCRs from sequence

G-protein-coupled receptors (GPCRs) are a large and functionally diverse pr otein superfamily, which form a seven transmembrane (TM) helices bundle wit h alternating extracellular and intracellular loops. GPCRs are considered t o be one of the most important groups of drug targets because they are invo lved in a broad range of body functions and processes and are related to ma jor diseases. In this paper we present a new technology, named PREDICT, for modeling the 3D structure of any GPCR from its amino acid sequence. This a pproach takes into account both internal protein properties (i.e., the amin o acid sequence) and the properties of the membrane environment. Unlike com peting approaches, the new technology does not rely on the single known str ucture of rhodopsin, and is thus capable of predicting novel GPCR conformat ions. We demonstrate the capabilities of PREDICT in reproducing the known e xperimental structure of rhodopsin. In principle, PREDICT generated models offer new opportunities for structure-based drug discovery towards GPCR tar gets. (C) 2001 John Wiley & Sons, Inc.