Mapping the druggable allosteric space of G-protein coupled receptors: a fragment-based molecular dynamics approach.

To address the problem of specificity in G-protein coupled receptor (GPCR) drug discovery, there has been tremendous recent interest in allosteric drugs that bind at sites topographically distinct from the orthosteric site. Unfortunately, structure-based drug design of allosteric GPCR ligands has been frustrated by the paucity of structural data for allosteric binding sites, making a strong case for predictive computational methods. In this work, we map the surfaces of the beta1 (beta1AR) and beta2 (beta2AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites. We employ the FTMAP algorithm to identify 'hot spots' with affinity for a variety of organic probe molecules corresponding to drug fragments. Our work is distinguished by an ensemble-based approach, whereby we map diverse receptor conformations taken from molecular dynamics (MD) simulations totaling approximately 0.5 micros. Our results reveal distinct pockets formed at both solvent-exposed and lipid-exposed cavities, which we interpret in light of experimental data and which may constitute novel targets for GPCR drug discovery. This mapping data can now serve to drive a combination of fragment-based and virtual screening approaches for the discovery of small molecules that bind at these sites and which may offer highly selective therapies

Cystic Fibrosis Transmembrane Conductance Regulator: Using Differential Reactivity toward Channel-Permeant and Channel-Impermeant Thiol-Reactive Probes To Test a Molecular Model for the Pore†

ABSTRACT: The sixth transmembrane segment (TM6) of the CFTR chloride channel has been intensively investigated. The effects of amino acid substitutions and chemical modification of engineered cysteines (cysteine scanning) on channel properties strongly suggest that TM6 is a key component of the anion-conducting pore, but previous cysteine-scanning studies of TM6 have produced conflicting results. Our aim was to resolve these conflicts by combining a screening strategy based on multiple, thiol-directed probes with molecular modeling of the pore. CFTR constructs were screened for reactivity toward both channel-permeant and channel-impermeant thiol-directed reagents, and patterns of reactivity in TM6 were mapped onto two new, molecular models of the CFTR pore: one based on homology modeling using Sav1866 as the template and a second derived from the first by molecular dynamics simulation. Comparison of the pattern of cysteine reactivity with model predictions suggests that nonreactive sites are those where the TM6 side chains are occluded by other TMs. Reactive sites, in contrast, are generally situated such that the respective amino acid side chains either project into the predicted pore or lie within a predicted extracellular loop. Sites wher

A combinatorial TIR1/AFB–Aux/IAA co-receptor system for differential sensing of auxin

The plant hormone auxin regulates virtually every aspect of plant growth and development. Auxin acts by binding the F-box protein transport inhibitor response 1 (TIR1) and promotes the degradation of the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Here we show that efficient auxin binding requires assembly of an auxin co-receptor complex consisting of TIR1 and an Aux/IAA protein. Heterologous experiments in yeast and quantitative IAA binding assays using purified proteins showed that different combinations of TIR1 and Aux/IAA proteins form co-receptor complexes with a wide range of auxin-binding affinities. Auxin affinity seems to be largely determined by the Aux/IAA. As there are 6 TIR1/AUXIN SIGNALING F-BOX proteins (AFBs) and 29 Aux/IAA proteins in Arabidopsis thaliana, combinatorial interactions may result in many co-receptors with distinct auxin-sensing properties. We also demonstrate that the AFB5–Aux/IAA co-receptor selectively binds the auxinic herbicide picloram. This co-receptor system broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response

Predictive Power of Molecular Dynamics Receptor Structures in Virtual Screening

Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range

Computational studies of ABC transporters

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Simulations of biased agonists in the β(2) adrenergic receptor with accelerated molecular dynamics.

The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signaling pathway a GPCR promotes intracellular signals though β-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that a GPCR forms a distinct ensemble of conformations signaling through the G protein and β-arrestin. Here we report on the dynamics of the β2 adrenergic receptor bound to the β-arrestin and G protein-biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring of the transition within the nanosecond time scale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the β-arrestin-biased agonist N-cyclopentylbutanepherine, we observe a different pattern of motions in helix 7 when compared to simulations with the G protein-biased agonist salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs

Coarse-grained molecular dynamics simulations of membrane proteins and peptides

Molecular dynamics (MD) simulations provide a valuable approach to the dynamics, structure, and stability of membrane–protein systems. Coarse-grained (CG) models, in which small groups of atoms are treated as single particles, enable extended (>100 ns) timescales to be addressed. In this study, we explore how CG–MD methods that have been developed for detergents and lipids may be extended to membrane proteins. In particular, CG–MD simulations of a number of membrane peptides and proteins are used to characterize their interactions with lipid bilayers. CG–MD is used to simulate the insertion of synthetic model membrane peptides (WALPs and LS3) into a lipid (PC) bilayer. WALP peptides insert in a transmembrane orientation, whilst the LS3 peptide adopts an interfacial location, both in agreement with experimental biophysical data. This approach is extended to a transmembrane fragment of the Vpu protein from HIV-1, and to the coat protein from fd phage. Again, simulated protein/membrane interactions are in good agreement with solid state NMR data for these proteins. CG–MD has also been applied to an M3–M4 fragment from the CFTR protein. Simulations of CFTR M3–M4 in a detergent micelle reveal formation of an -helical hairpin, consistent with a variety of biophysical data. In an I231D mutant, the M3–M4 hairpin is additionally stabilized via an inter-helix Q207/D231 interaction. Finally, CG–MD simulations are extended to a more complex membrane protein, the bacterial sugar transporter LacY. Comparison of a 200 ns CG–MD simulation of LacY in a DPPC bilayer with a 50 ns atomistic simulation of the same protein in a DMPC bilayer shows that the two methods yield comparable predictions of lipid–protein interactions. Taken together, these results demonstrate the utility of CG–MD simulations for studies of membrane/protein interactions