Ian D. Wall

Bioinformatics and molecular modelling approaches to GPCR oligomerization

The elusive nature of the structure and function of the G-protein coupled receptor (GPCR) dimer or oligomer has led to a variety of computational studies, most of which have been directed primarily towards understanding structure. Here we review some of the recent studies based on sequence analysis and docking experiments and the recent developments in GPCR structure that have underpinned dimerization studies. In addition, we review recent nanosecond molecular dynamics simulations and coarse-grained methods for investigating the dynamic consequences of dimerization. The strengths and weaknesses of these complementary methods are discussed. The consensus of a variety of studies is that several transmembrane helices are involved in the dimerization/oligomerization interface(s); computation has been particularly effective in elucidating the experiments that seem to indicate a key role for transmembrane helix 4.

Modeling GPCR active state conformations: The β2‐adrenergic receptor

The recent publication of several G protein‐coupled receptor (GPCR) structures has increased the information available for homology modeling inactive class A GPCRs. Moreover, the opsin crystal structure shows some active features. We have therefore combined information from these two sources to generate an extensively validated model of the active conformation of the β2‐adrenergic receptor. Experimental information on fully active GPCRs from zinc binding studies, site‐directed spin labeling, and other spectroscopic techniques has been used in molecular dynamics simulations. The observed conformational changes reside mainly in transmembrane helix 6 (TM6), with additional small but significant changes in TM5 and TM7. The active model has been validated by manual docking and is in agreement with a large amount of experimental work, including site‐directed mutagenesis information. Virtual screening experiments show that the models are selective for β‐adrenergic agonists over other GPCR ligands, for (R)‐ over (S)‐β‐hydroxy agonists and for β2‐selective agonists over β1‐selective agonists. The virtual screens reproduce interactions similar to those generated by manual docking. The C‐terminal peptide from a model of the stimulatory G protein, readily docks into the active model in a similar manner to which the C‐terminal peptide from transducin, docks into opsin, as shown in a recent opsin crystal structure. This GPCR‐G protein model has been used to explain site‐directed mutagenesis data on activation. The agreement with experiment suggests a robust model of an active state of the β2‐adrenergic receptor has been produced. The methodology used here should be transferable to modeling the active state of other GPCRs. Proteins 2011.

Pyridine-3-carboxamides as novel CB 2 agonists for analgesia

We describe herein the medicinal chemistry approach which led to the discovery of a novel pyridine-3-carboxamide series of CB(2) receptor agonists. The SAR of this new template was evaluated and culminated in the identification of analogue 14a which demonstrated efficacy in an in vivo model of inflammatory pain.

Crystal Structures of Ask1-Inhibtor Complexes Provide a Platform for Structure Based Drug Design.

ASK1, a member of the MAPK Kinase Kinase family of proteins has been shown to play a key role in cancer, neurodegeneration and cardiovascular diseases and is emerging as a possible drug target. Here we describe a ‘replacement‐soaking’ method that has enabled the high‐throughput X‐ray structure determination of ASK1/ligand complexes. Comparison of the X‐ray structures of five ASK1/ligand complexes from 3 different chemotypes illustrates that the ASK1 ATP binding site is able to accommodate a range of chemical diversity and different binding modes. The replacement‐soaking system is also able to tolerate some protein flexibility. This crystal system provides a robust platform for ASK1/ligand structure determination and future structure based drug design.

Modeling active GPCR conformations.

The most significant advance in modeling GPCR active states has been the β(2)-adrenergic receptor-Gs complex as this essentially transforms active-state modeling into homology modeling. Various different molecular dynamics-based approaches for modeling active states are presented, and a number of key applications discussed. These simulations have given insights into the activation pathway, conformational changes, dimerization, hydration, the ionic lock, ligand binding, protonation, and sodium binding. Crystallography and simulations have shown that the presence of agonist alone is unlikely to be sufficient to form the active state and that restraints applied to the G protein-binding region are required. The role of various microswitches in activation is discussed, including the controversial rotamer toggle switch. The importance of explicitly simulating experimental molecular probes to understand activation is highlighted, along with the need to ensure that such molecules are well parameterized. Approaches to loop modeling are discussed. We argue that the role of successful virtual screening against active models should not be overestimated as the main conformational changes on activation occur in the intracellular region.

Optimization of Sphingosine-1-phosphate-1 Receptor Agonists: Effects of Acidic, Basic, and Zwitterionic Chemotypes on Pharmacokinetic and Pharmacodynamic Profiles

The efficacy of the recently approved drug fingolimod (FTY720) in multiple sclerosis patients results from the action of its phosphate metabolite on sphingosine-1-phosphate S1P1 receptors, while a variety of side effects have been ascribed to its S1P3 receptor activity. Although S1P and phospho-fingolimod share the same structural elements of a zwitterionic headgroup and lipophilic tail, a variety of chemotypes have been found to show S1P1 receptor agonism. Here we describe a study of the tolerance of the S1P1 and S1P3 receptors toward bicyclic heterocycles of systematically varied shape and connectivity incorporating acidic, basic, or zwitterionic headgroups. We compare their physicochemical properties, their performance in in vitro and in vivo pharmacokinetic models, and their efficacy in peripheral lymphocyte lowering. The campaign resulted in the identification of several potent S1P1 receptor agonists with good selectivity vs S1P3 receptors, efficacy at <1 mg/kg oral doses, and developability properties suitable for progression into preclinical development.

G-protein-coupled receptor dynamics: dimerization and activation models compared with experiment

Our previously derived models of the active state of the β2-adrenergic receptor are compared with recently published X-ray crystallographic structures of activated GPCRs (G-protein-coupled receptors). These molecular dynamics-based models using experimental data derived from biophysical experiments on activation were used to restrain the receptor to an active state that gave high enrichment for agonists in virtual screening. The β2-adrenergic receptor active model and X-ray structures are in good agreement over both the transmembrane region and the orthosteric binding site, although in some regions the active model is more similar to the active rhodopsin X-ray structures. The general features of the microswitches were well reproduced, but with minor differences, partly because of the unexpected X-ray results for the rotamer toggle switch. In addition, most of the interacting residues between the receptor and the G-protein were identified. This analysis of the modelling has also given important additional insight into GPCR dimerization: re-analysis of results on photoaffinity analogues of rhodopsin provided additional evidence that TM4 (transmembrane helix 4) resides at the dimer interface and that ligands such as bivalent ligands may pass between the mobile helices. A comparison, and discussion, is also carried out between the use of implicit and explicit solvent for active-state modelling.

Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study

Binding free energies of bromodomain inhibitors are calculated with recently formulated approaches, namely ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling). A set of compounds is provided by GlaxoSmithKline, which represents a range of chemical functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the experimental data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, we can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches.

OOMMPPAA: a tool to aid directed synthesis by the combined analysis of activity and structural data.

There is an ever increasing resource in terms of both structural information and activity data for many protein targets. In this paper we describe OOMMPPAA, a novel computational tool designed to inform compound design by combining such data. OOMMPPAA uses 3D matched molecular pairs to generate 3D ligand conformations. It then identifies pharmacophoric transformations between pairs of compounds and associates them with their relevant activity changes. OOMMPPAA presents this data in an interactive application providing the user with a visual summary of important interaction regions in the context of the binding site. We present validation of the tool using openly available data for CDK2 and a GlaxoSmithKline data set for a SAM-dependent methyl-transferase. We demonstrate OOMMPPAA’s application in optimizing both potency and cell permeability and use OOMMPPAA to highlight nuanced and cross-series SAR. OOMMPPAA is freely available to download at http://oommppaa.sgc.ox.ac.uk/OOMMPPAA/.

4.26 – Seven Transmembrane G Protein-Coupled Receptors: Insights for Drug Design from Structure and Modeling

This chapter describes modeling techniques that have been reported for the design of G protein-complex receptor (GPCR) ligands, summarizing the success of key methodologies and the targets to which they have been applied. The discussion focuses mainly on the building of GPCR models and their use in structure-based ligand design, although a summary of key ligand-based methods is also included. The first section describes the model building process. The history of receptor modeling and the data on which it is based are reported, explaining how modeling techniques and the resulting models have evolved as the quality and quantity of underlying experimental studies have increased. Both homology modeling and de novo model-building methods are covered. Current challenges and aims for the future are also discussed with particular focus on modeling of activated receptor states and Family B and C GPCRs. The focus of the chapter then moves to the utilization of these models for drug design. Firstly design techniques based on the docking of small numbers of ligands into receptor models are discussed. Then the challenging topic of combining high-throughput docking techniques with receptor models is tackled. Finally, an attempt is made to summarize the wealth of small-molecule modeling methods that have been reported in the literature. Particular attention is paid to methods for selecting compound sets enriched in GPCR ligands which encompass library design. Due to the immensity of that task and the fact that ligand-based methods are discussed in detail elsewhere in this book, the emphasis in this chapter is on those methods that either have special relevance to GPCR ligands, or those that have been shown to be particularly successful when applied to the area.