A physicogenetic method to assign ligand-binding relationships between 7TM receptors

doi:10.1016/j.bmcl.2005.05.102

Bioorganic & Medicinal Chemistry Letters

Volume 15, Issue 16, 15 August 2005, Pages 3707-3712

https://doi.org/10.1016/j.bmcl.2005.05.102 Get rights and content

Abstract

A computational protocol has been devised to relate 7TM receptor proteins (GPCRs) with respect to physicochemical features of the core ligand-binding site as defined from the crystal structure of bovine rhodopsin. The identification of such receptors that already are associated with ligand information (e.g., small molecule ligands with mutagenesis or SAR data) is used to support structure-guided drug design of novel ligands. A case targeting the newly identified prostaglandin D2 receptor CRTH2 serves as a primary example to illustrate the procedure.

Graphical abstract

A computational protocol has been devised to relate 7TM receptor proteins (GPCRs) with respect to physicochemical features of the core ligand-binding site. A case targeting the newly identified prostaglandin D2 receptor CRTH2 serves as a primary example to illustrate the procedure.

Introduction

The G protein-coupled receptors (GPCRs) allow signals from the exterior of cells to be communicated to second messenger systems within the cells. The receptors are integral membrane proteins characterized by seven transmembrane (7TM) helical segments traversing the membrane in an antiparallel way, with the N-terminal on the extracellular side of the membrane and the C-terminal on the intracellular side. This generic protein structure is extensively used for a variety of stimuli spanning from protons, fatty acids, monoamines, peptide hormones, glycoproteins to olfactory agents and light. The 7TM receptor superfamily is composed of many hundreds of receptors that can be further divided into smaller sub-families of receptors.¹ The largest of these sub-families is composed of the rhodopsin-like receptors, also termed family A receptors, named after the light-sensor in our eye.

Despite the fact that drugs have been successfully developed for 7TM receptors, efficient structure-based drug discovery is hampered by the lack of detailed structural information. Hitherto only one G protein-coupled receptor, bovine rhodopsin, has been subject to structural determination by X-ray crystallography at atomic resolution in its inactive conformation with 11-cis-retinal.² Since the three-dimensional structure of only a single receptor has been solved to date, the helical lengths, and the beginning, centre and ends relative to the lipid bilayer membrane of each of the seven helices for target receptors are dissected by sequence analysis.³ Homology models of other rhodopsin-like 7TM receptors have been derived from the bovine rhodopsin structure.² These models have been used with varying success to drive the design and optimisation of novel ligands.⁴ Mutagenesis, metal-site engineering, biophysical and spectroscopic studies have supported the identification of a core-binding site located in the upper part of the transmembrane helical bundle.⁵

Much of the success in structure-based drug design in general for other target protein classes is driven by iterative processes utilising target protein as well as ligand information—especially ligand–protein complexes—in the design. To compensate for the lack of detailed structural information for the 7TM receptors it was reasoned that identification of receptors that already were associated with ligand information (e.g., small molecule ligands with mutagenesis or SAR data) and which were closely related to the target receptor could be used to improve the rational drug design process.

7TM receptor proteins have traditionally been classified based on their primary amino acid sequences, evolutionary phylogeny,⁶ or their pharmacological profile.¹ However, from a drug discovery perspective, it is more relevant to classify and characterize 7TM receptors according to their ligand recognition properties.

Here, we describe a computational strategy which classifies 7TM receptors with respect to physicochemical features of selected aminoacid residues located in a common structural framework constituting a core ligand-binding site as defined from the crystal structure of rhodopsin. The classification procedure involves the following steps: (i) primary sequence alignment (TM domain) of all 7TM receptors;3, 7 (ii) identification and selection of core-binding site residues potentially involved in small molecule ligand binding and recognition;4, 5, 8 (iii) create binding site signatures and pseudo-sequence strings; (iv) assign physicochemical descriptors or indicator variables;9, 10 (v) compare, rank and cluster 7TM receptors of interest.

Section snippets

7TM sequence alignment (step i)

To allow for this type of comparison the protein sequences must be properly aligned using conventional alignment algorithms such as ClustalW.⁷ The resulting alignment is manually inspected and refined if necessary, so that conserved generic sequence signatures within the seven transmembrane helices are satisfied.

Definition of core-binding site (step ii)

Based on the conserved key residues in each transmembrane segment, a generic numbering system has been suggested.3, 8 For example, in TM-II the highly conserved aspartate (Asp) is given the generic number 10, i.e., AspII:10, and all other residues in the helix are hence numbered on this basis (cf. Fig. 1).⁸ A large body of research has been dedicated to identify which amino acid residues that are associated with binding of small molecules.4, 5 A proposed core-binding site consisting of 22 amino

Descriptors applied to binding site signatures (steps iii and iv)

The binding site signature, represented by a ‘pseudo-sequence string’ of the 22 amino acid positions, is encoded with physicochemical descriptors relevant for ligand binding and recognition, such as ionic, ion–dipole, dipole–dipole, hydrogen bonding, hydrophobic, π-stacking, edge-on aromatic, and cation-interaction forces. The physicochemical descriptors can be experimentally derived and/or theoretically calculated.9, 10 Such descriptors have successfully been employed in various types of

Computational classification procedure (step v)

Having defined the core ligand-binding site and associated physicochemical descriptors it is possible to compare, rank and cluster 7TM receptors with respect to their potential to interact with a given ligand or structurally similar ligands. By analogy to phylogenetic analysis, this process has been referred to as physicogenetic analysis.

Following the procedure above it is possible to quantify how similar a given receptor-binding site or subsite is to other receptor-binding sites and/or

Results and discussion

The rhodopsin-like receptor, CRTH2, was recently identified as the second high-affinity prostaglandin D2 receptor.¹³ It is expressed on eosinophils, basophils and Th2 cells, and it has attracted attention as a novel target for treatment of allergic diseases like asthma and rhinitis. It was selected as an appropriate target for applying a structure-guided approach of identifying ligands since indomethacin was the only identified ligand for this receptor at the time we initiated the study

Acknowledgment

The authors are grateful to Thue W. Schwartz for insightful support and stimulating discussions.

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A physicogenetic method to assign ligand-binding relationships between 7TM receptors

Abstract

Graphical abstract

Introduction

Section snippets

7TM sequence alignment (step i)

Definition of core-binding site (step ii)

Descriptors applied to binding site signatures (steps iii and iv)

Computational classification procedure (step v)

Results and discussion

Acknowledgment

J. Mol. Biol.

J. Mol. Biol.

Proc. Natl. Acad. Sci. U.S.A.

Proc. Natl. Acad. Sci. U.S.A.

Proteins

J. Mol. Biol.

J. Mol. Evol.

Int. J. Quant. Chem.

J. Chem. Inf. Comput. Sci.

J. Med. Chem.

J. Pept. Res.

J. Comput. Chem.

J. Med. Chem.

J. Chem. Inf. Comput. Sci.

Mol. Pharmacol.

Protein Eng.

J. Med. Chem.

Mol. Pharmacol.

Mol. Pharmacol.

Science

Annu. Rev. Biophys. Biomol. Struct.

EMBO J.

J. Mol. Biol.

ChemBioChem

J. Med. Chem.

Biochim. Biophys. Acta

Pharmacol. Ther.