Identification Methods of G Protein-Coupled Receptors

Identification Methods of G Protein-Coupled Receptors

Meriem Zekri, Karima Alem, Labiba Souici-Meslati
Copyright: © 2011 |Pages: 18
DOI: 10.4018/jkdb.2011100103
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Abstract

The G protein-coupled receptors (GPCRs) include one of the largest and most important families of multifunctional proteins known to molecular biology. They play a key role in cell signaling networks that regulate many physiological processes, such as vision, smell, taste, neurotransmission, secretion, immune responses, metabolism, and cell growth. These proteins are thus very important for understanding human physiology and they are involved in several diseases. Therefore, many efforts in pharmaceutical research are to understand their structures and functions, which is not an easy task, because although thousands GPCR sequences are known, many of them remain orphans. To remedy this, many methods have been developed using methods such as statistics, machine learning algorithms, and bio-inspired approaches. In this article, the authors review the approaches used to develop algorithms for classification GPCRs by trying to highlight the strengths and weaknesses of these different approaches and providing a comparison of their performances.
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Introduction

The body, permanently biased by its environment, is led to analyze simultaneously thousands of information of various types varying from simple photons at odor molecules through hormones, amino acids and nucleotides. Receipt of this information and their decoding by the cells require the presence of specific receptors at the interface between the extracellular and intracellular side of the cell. A receptor is thus a protein having ligand to an informational molecule from the external environment. One of the largest families of receptors is formed by G protein-coupled receptors (GPCRs). These receptors are membrane proteins with molecular mass mostly varying from 40 to 85 kDa (kilo Dalton) (Suwa, Sugihara & Ono, 2011). They are characterized by seven transmembrane helices (TM) and respond to different ligands, such as amino acids, peptides, hormones and odorants from the extracellular side of the cell. These stimulations induce GPCRs to activate G proteins and to transmit the signals within the cell, GPCRs exist in most of the cells and abnormal signal transduction of GPCRs is linked to various abnormal conditions such as allergy, heart disease, cancer, hypertension, etc. As shown in Figure 1, the structure of the vast majority of GPCRs is characterized by: (1) an extracellular N-terminal that can undergo post-translational modifications of N-glycosylation, (2) seven transmembrane α helices (TM1 to TM7) connected by three intracellular loops (I1, I2, I3) and three extracellular loops (El, E2, E3), (3) a disulfide bridge between the loops El and E2; and (4) a C-terminal intracellular has sometimes lipid docking sites in the membrane (creation of a fourth loop, I4) (Hamm, 2001).

Figure 1.

Schematic representation of a G protein coupled receptor (Alem, 2011)

jkdb.2011100103.f01

The mechanism of GPCRs is as follows: the GPCR is activated by an external signal in the form of a ligand or other signal of a mediator. Creating a conformational change in the receptor, this causes the activation of a G-protein. Additional effect depends on the type of protein G. GPCRs that act as receptors for stimuli which have not yet been identified are called orphan receptors. For example, physiological agonists and functional role for a large number of GPCRs orphans remain unknown, although these orphan receptors may be as important, perhaps even more, than the currently highlighted GPCRs in physiological studies. Signal transduction across the membrane by the receptor is not completely understood. It was identified that the inactive protein G is bound to the receptor in its inactive state. Once the ligand is known, the receiver moves and mechanically activates the G protein, which is removed from the receiver. The receiver can then activate another G protein or either returns to its inactive state (Suwa, Sugihara & Ono, 2011).

The identification of GPCRs function is an area of current interest in pharmaceutical research, in fact, about 80% of marketed drugs target GPCRs (Chou & Elrod, 2002). Although thousands of GPCR sequences are known, many of them remain as orphan sequences of unknown functions. This article is an overview of approaches for GPCRs classification; it reviews a set of research works performed, over the past decade, to address the problem of identifying GPCRs functions using statistical methods, machine learning algorithms or bio-inspired approaches. Table 1 summarizes some of these works.

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