Premium
Modeling the 3D structure of GPCRs from sequence
Author(s) -
Shacham Sharon,
Topf Maya,
Avisar Noa,
Glaser Fabian,
Marantz Yael,
BarHaim Shay,
Noiman Silvia,
Naor Zvi,
Becker Oren M.
Publication year - 2001
Publication title -
medicinal research reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.868
H-Index - 130
eISSN - 1098-1128
pISSN - 0198-6325
DOI - 10.1002/med.1019
Subject(s) - g protein coupled receptor , rhodopsin , computational biology , sequence (biology) , transmembrane domain , biology , transmembrane protein , peptide sequence , drug discovery , protein structure , amino acid , receptor , bioinformatics , biochemistry , gene , retinal
G‐protein‐coupled receptors (GPCRs) are a large and functionally diverse protein superfamily, which form a seven transmembrane (TM) helices bundle with alternating extra‐cellular and intracellular loops. GPCRs are considered to be one of the most important groups of drug targets because they are involved in a broad range of body functions and processes and are related to major 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 approach takes into account both internal protein properties (i.e., the amino acid sequence) and the properties of the membrane environment. Unlike competing approaches, the new technology does not rely on the single known structure of rhodopsin, and is thus capable of predicting novel GPCR conformations. We demonstrate the capabilities of PREDICT in reproducing the known experimental structure of rhodopsin. In principle, PREDICT‐generated models offer new opportunities for structure‐based drug discovery towards GPCR targets. © 2001 John Wiley & Sons, Inc. Med Res Rev, 21, No. 5, 472–483, 2001