Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Modeled structure of the whole regulator G-protein signaling-2

There is an increasing interest towards the mechanism by which regulators of G-protein signaling regulate signals of G-protein-coupled receptors. RGS2 is a regulator of Gq protein signaling (RGS), the N-terminal region of which is known to contain determinants for G protein-coupled receptor recognition, but its structure is still unknown. To understand the molecular basis for this recognition, the three-dimensional model of RGS2, including N-terminal region and RGS box, was modeled. For this, RGS4 box structure and data from circular dichroism study of RGS2 N-terminal region were used. Then, membrane-targeting activity of the RGS2 amphipathic helix contained in the N-terminal region was investigated. Furthermore, in cellulo study provided first evidence that an internal sequence within the N-terminal region of RGS2 is involved in RGS2 regulation of cholecystokinin receptor-2 signal. RGS2 modeled structure can now serve to study molecular recognition of RGS2 by signaling molecules. © 2006 Elsevier Inc. All rights reserved.

Modeled structure of a G-protein-coupled receptor:The cholecystokinin-1 receptor

The Cholecystokinin-1 receptor (CCK1R) mediates actions of CCK in areas of the central nervous system and of the gut. It is a potential target to treat a number of diseases. As for all G-protein-coupled receptors, docking of ligands into modeled CCK1R binding site should greatly help to understand intrinsic mechanisms of activation. Here, we describe the procedure we used to progressively build a structural model for the CCK1R, to integrated, and on the basis of site-directed mutagenesis data on its binding site. Reliability of the CCK1R model was confirmed by interaction networks that involved conserved and functionally crucial motifs in G-protein-coupled receptors, such as Glu/Asp-Arg-Tyr and Asn-Pro-Xaa-Xaa-Tyr motifs. In addition, the 3-D structure of CCK1R-bound CCK resembled that determined by NMR in a lipid environment. The derived computational model was also used for revealing binding modes of several nonpeptide ligands and for rationalizing ligand structure-activity relationships known from experiments. Our findings indeed support that our "validated CCK1R model" could be used to study the intrinsic mechanism of CCK1R activation and design new ligands.

Toxicity of non-abeta component of Alzheimer's disease amyloid, and N-terminal fragments thereof, correlates to formation of beta-sheet structure and fibrils.

Synucleins are small proteins that are highly expressed in brain tissue and are localised at presynaptic terminals in neurons. alpha-Synuclein has been identified as a component of intracellular fibrillar protein deposits in several neurodegenerative diseases, and two mutant forms of alpha-synuclein have been associated with autosomal-dominant Parkinson's Disease. A fragment of alpha-synuclein has also been identified as the non-Abeta component of Alzheimer's Disease amyloid. In this review we describe some structural properties of alpha-synuclein and the two mutant forms, as well as alpha-synuclein fragments, with particular emphasis on their ability to form beta-sheet on ageing and aggregate to form amyloid-like fibrils. Differences in the rates of aggregation and morphologies of the fibrils formed by alpha-synuclein and the two mutant proteins are highlighted. Interactions between alpha-synuclein and other proteins, especially those that are components of amyloid or Lewy bodies, are considered. The toxicity of alpha-synuclein and related peptides towards neurons is also discussing in relation to the aetiology of neurodegenerative diseases.