Simulations of a G protein-coupled receptor homology model predict dynamic features and a ligand binding site

Learning Protein-Ligand Unbinding Pathways via Single-Parameter Community Detection

Understanding the dynamics of biomolecular complexes, e.g., of protein-ligand (un)binding, requires the comprehension of paths such systems take between metastable states. In MD simulations, paths are usually not observable per se, but they need to be inferred from simulation trajectories. Here, we present a novel approach to cluster trajectories based on a community detection algorithm that necessitates only the definition of a single parameter. The unbinding of the streptavidin-biotin complex is used as a benchmark system and the A2a adenosine receptor in complex with the inhibitor ZM241385 as an elaborate application. We demonstrate how such clusters of trajectories correspond to pathways and how the approach helps in the identification of reaction coordinates for a considered (un)binding process.

Steric and energetic characterizations of mouse and human musk receptors activated by nitro musk smelling compounds at molecular level: Statistical physics treatment and molecular docking analysis

Understanding olfaction process at a microscopic or molecular level needs more elucidation of the multiple stages involved in the olfaction mechanism. A worth full elucidation and a better understanding of this molecular mechanism, a necessary preamble should be achieved. The content of this work is a preamble for that. A study of the mouse and human olfactory receptors activation in response to two nitro musks stimuli, which are the musk xylol and the musk ketone, are considered here, first, for their wide expanded use in perfumery, but also to show some particular aspects of this process in the case of these two stimuli, which could help to deduce more details and more general aspects in the global olfactory mechanism. A statistical physics modeling using the monolayer model with two independent types of receptor binding sites of the response of the mouse olfactory receptor MOR215-1 and the human olfactory receptor OR5AN1, which are identified as specifically responding to musk compounds, is used to characterize the interaction between the two nitro musk molecules, the mouse and the human olfactory receptors and to determine the olfactory band of these two odorants through the determination of the molar adsorption energies and the adsorption energy distributions. The physico-chemical model parameters can be used for the steric characterization via the calculation of the receptor site size distributions. The docking computation between these two nitro musks and the human olfactory receptor OR5AN1 is performed demonstrating a large similarity in receptor-ligand detection process. Thus, docking finding results prove that the calculated binding affinities were belonging to the spectrum of adsorption energies.

Molecular mechanism of activation of human musk receptors OR5AN1 and OR1A1 by (R)-muscone and diverse other musk-smelling compounds

Understanding olfaction at the molecular level is challenging due to the lack of crystallographic models of odorant receptors (ORs). To better understand the molecular mechanism of OR activation, we focused on chiral (R)-muscone and other musk-smelling odorants due to their great importance and widespread use in perfumery and traditional medicine, as well as environmental concerns associated with bioaccumulation of musks with estrogenic/antiestrogenic properties. We experimentally and computationally examined the activation of human receptors OR5AN1 and OR1A1, recently identified as specifically responding to musk compounds. OR5AN1 responds at nanomolar concentrations to musk ketone and robustly to macrocyclic sulfoxides and fluorine-substituted macrocyclic ketones; OR1A1 responds only to nitromusks. Structural models of OR5AN1 and OR1A1 based on quantum mechanics/molecular mechanics (QM/MM) hybrid methods were validated through direct comparisons with activation profiles from site-directed mutagenesis experiments and analysis of binding energies for 35 musk-related odorants. The experimentally found chiral selectivity of OR5AN1 to (R)- over (S)-muscone was also computationally confirmed for muscone and fluorinated (R)-muscone analogs. Structural models show that OR5AN1, highly responsive to nitromusks over macrocyclic musks, stabilizes odorants by hydrogen bonding to Tyr260 of transmembrane α-helix 6 and hydrophobic interactions with surrounding aromatic residues Phe105, Phe194, and Phe207. The binding of OR1A1 to nitromusks is stabilized by hydrogen bonding to Tyr258 along with hydrophobic interactions with surrounding aromatic residues Tyr251 and Phe206. Hydrophobic/nonpolar and hydrogen bonding interactions contribute, respectively, 77% and 13% to the odorant binding affinities, as shown by an atom-based quantitative structure-activity relationship model.

Dynamical Binding Modes Determine Agonistic and Antagonistic Ligand Effects in the Prostate-Specific G-Protein Coupled Receptor (PSGR)

We analysed the ligand-based activation mechanism of the prostate-specific G-protein coupled receptor (PSGR), which is an olfactory receptor that mediates cellular growth in prostate cancer cells. Furthermore, it is an olfactory receptor with a known chemically near identic antagonist/agonist pair, α- and β-ionone. Using a combined theoretical and experimental approach, we propose that this receptor is activated by a ligand-induced rearrangement of a protein-internal hydrogen bond network. Surprisingly, this rearrangement is not induced by interaction of the ligand with the network, but by dynamic van der Waals contacts of the ligand with the involved amino acid side chains, altering their conformations and intraprotein connectivity. Ligand recognition in this GPCR is therefore highly stereo selective, but seemingly lacks any ligand recognition via polar contacts. A putative olfactory receptor-based drug design scheme will have to take this unique mode of protein/ligand action into account.

Evidence for a shape-based recognition of odorants in vivo in the human nose from an analysis of the molecular mechanism of lily-of-the-valley odorants detection in the Lilial and Bourgeonal family using the C/Si/Ge/Sn switch strategy

We performed an analysis of possible mechanisms of ligand recognition in the human nose. The analysis is based on in vivo odor threshold determination and in vitro Ca2+ imaging assays with a C/Si/Ge/Sn switch strategy applied to the compounds Lilial and Bourgeonal, to differentiate between different molecular mechanisms of odorant detection. Our results suggest that odorant detection under threshold conditions is mainly based on the molecular shape, i.e. the van der Waals surface, and electrostatics of the odorants. Furthermore, we show that a single olfactory receptor type is responsible for odor detection of Bourgeonal at the threshold level in humans in vivo. Carrying out a QM analysis of vibrational energies contained in the odorants, there is no evidence for a vibration-based recognition.

Galaxy7TM: flexible GPCR-ligand docking by structure refinement

G-protein-coupled receptors (GPCRs) play important physiological roles related to signal transduction and form a major group of drug targets. Prediction of GPCR-ligand complex structures has therefore important implications to drug discovery. With previously available servers, it was only possible to first predict GPCR structures by homology modeling and then perform ligand docking on the model structures. However, model structures generated without explicit consideration of specific ligands of interest can be inaccurate because GPCR structures can be affected by ligand binding. The Galaxy7TM server, freely accessible at http://galaxy.seoklab.org/7TM, improves an input GPCR structure by simultaneous ligand docking and flexible structure refinement using GALAXY methods. The server shows better performance in both ligand docking and GPCR structure refinement than commonly used programs AutoDock Vina and Rosetta MPrelax, respectively.

Molecular Insights into the Transmembrane Domain of the Thyrotropin Receptor

The thyrotropin receptor (TSHR) is a G protein-coupled receptor (GPCR) that is member of the leucine-rich repeat subfamily (LGR). In the absence of crystal structure, the success of rational design of ligands targeting the receptor internal cavity depends on the quality of the TSHR models built. In this subfamily, transmembrane helices (TM) 2 and 5 are characterized by the absence of proline compared to most receptors, raising the question of the structural conformation of these helices. To gain insight into the structural properties of these helices, we carried out bioinformatics and experimental studies. Evolutionary analysis of the LGR family revealed a deletion in TM5 but provided no information on TM2. Wild type residues at positions 2.58, 2.59 or 2.60 in TM2 and/or at position 5.50 in TM5 were substituted to proline. Depending on the position of the proline substitution, different effects were observed on membrane expression, glycosylation, constitutive cAMP activity and responses to thyrotropin. Only proline substitution at position 2.59 maintained complex glycosylation and high membrane expression, supporting occurrence of a bulged TM2. The TSHR transmembrane domain was modeled by homology with the orexin 2 receptor, using a protocol that forced the deletion of one residue in the TM5 bulge of the template. The stability of the model was assessed by molecular dynamics simulations. TM5 straightened during the equilibration phase and was stable for the remainder of the simulations. Our data support a structural model of the TSHR transmembrane domain with a bulged TM2 and a straight TM5 that is specific of glycoprotein hormone receptors.

Identification of amino acids involved in histamine potentiation of GABA A receptors

Histamine is a neurotransmitter involved in a number of physiological and neuronal functions. In mammals, such as humans, and rodents, the histaminergic neurons found in the tuberomamillary nucleus project widely throughout the central nervous system. Histamine acts as positive modulator of GABA_A receptors (GABA_ARs) and, in high concentrations (10 mM), as negative modulator of the strychnine-sensitive glycine receptor. However, the exact molecular mechanisms by which histamine acts on GABA_ARs are unknown. In our study, we aimed to identify amino acids potentially involved in the modulatory effect of histamine on GABA_ARs. We expressed GABA_ARs with 12 different point mutations in Xenopus laevis oocytes and characterized the effect of histamine on GABA-induced currents using the two-electrode voltage clamp technique. Our data demonstrate that the amino acid residues β2(N265) and β2(M286), which are important for modulation by propofol, are not involved in the action of histamine. However, we found that histamine modulation is dependent on the amino acid residues α1(R120), β2(Y157), β2(D163), β3(V175), and β3(Q185). We showed that the amino acid residues β2(Y157) and β3(Q185) mediate the positive modulatory effect of histamine on GABA-induced currents, whereas α1(R120) and β2(D163) form a potential histamine interaction site in GABA_ARs.

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

We show the key role of structural homology models in GPCR structure-based lead discovery and optimization, highlighting methodological aspects, recent progress and future directions.

Structure prediction and molecular dynamics simulations of a G-protein coupled receptor: human CCR2 receptor

CC chemokine receptor type-2 (CCR2) is a member of G-protein coupled receptors superfamily, expressed on the cell surface of monocytes and macrophages. It binds to the monocyte chemoattractant protein-1, a CC chemokine, produced at the sites of inflammation and infection. A homology model of human CCR2 receptor based on the recently available C-X-C chemokine recepor-4 crystal structure has been reported. Ligand information was used as an essential element in the homology modeling process. Six known CCR2 antagonists were docked into the model using simple and induced fit docking procedure. Docked complexes were then subjected to visual inspection to check their suitability to explain the experimental data obtained from site directed mutagenesis and structure-activity relationship studies. The homology model was refined, validated, and assessed for its performance in docking-based virtual screening on a set of CCR2 antagonists and decoys. The docked complexes of CCR2 with the known antagonists, TAK779, a dual CCR2/CCR5 antagonist, and Teijin-comp1, a CCR2 specific antagonist were subjected to molecular dynamics (MD) simulations, which further validated the binding modes of these antagonists. B-factor analysis of 20 ns MD simulations demonstrated that Cys190 is helpful in providing structural rigidity to the extracellular loop (EL2). Residues important for CCR2 antagonism were recognized using free energy decomposition studies. The acidic residue Glu291 from TM7, a conserved residue in chemokine receptors, is favorable for the binding of Teijin-comp1 with CCR2 by ΔG of -11.4 kcal/mol. Its contribution arises more from the side chains than the backbone atoms. In addition, Tyr193 from EL2 contributes -0.9 kcal/mol towards the binding of the CCR2 specific antagonist with the receptor. Here, the homology modeling and subsequent molecular modeling studies proved successful in probing the structure of human CCR2 chemokine receptor for the structure-based virtual screening and predicting the binding modes of CCR2 antagonists.

Structural model of channelrhodopsin

Channelrhodopsins (ChRs) are light-gated cation channels that mediate ion transport across membranes in microalgae (vectorial catalysis). ChRs are now widely used for the analysis of neural networks in tissues and living animals with light (optogenetics). For elucidation of functional mechanisms at the atomic level, as well as for further engineering and application, a detailed structure is urgently needed. In the absence of an experimental structure, here we develop a structural ChR model based on several molecular computational approaches, capitalizing on characteristic patterns in amino acid sequences of ChR1, ChR2, Volvox ChRs, Mesostigma ChR, and the recently identified ChR of the halophilic alga Dunaliella salina. In the present model, we identify remarkable structural motifs that may explain fundamental electrophysiological properties of ChR2, ChR1, and their mutants, and in a crucial validation of the model, we successfully reproduce the excitation energy predicted by absorption spectra.

In channelrhodopsin-2 Glu-90 is crucial for ion selectivity and is deprotonated during the photocycle

The light-activated microbial ion channel channelrhodopsin-2 (ChR2) is a powerful tool to study cellular processes with high spatiotemporal resolution in the emerging field of optogenetics. To customize the channel properties for optogenetic experiments, a detailed understanding of its molecular reaction mechanism is essential. Here, Glu-90, a key residue involved in the gating and selectivity mechanism of the ion channel is characterized in detail. The deprotonation of Glu-90 during the photocycle is elucidated by time-resolved FTIR spectroscopy, which seems to be part of the opening mechanism of the conductive pore. Furthermore, Glu-90 is crucial to ion selectivity as also revealed by mutation of this residue combined with voltage clamp experiments. By dynamic homology modeling, we further hypothesized that the conductive pore is flanked by Glu-90 and located between helices A, B, C, and G.

The structure of active opsin as a basis for identification of GPCR agonists by dynamic homology modelling and virtual screening assays

Most of the currently available G protein-coupled receptor (GPCR) crystal structures represent an inactive receptor state, which has been considered to be suitable only for the discovery of antagonists and inverse agonists in structure-based computational ligand screening. Using the β(2)-adrenergic receptor (B2AR) as a model system, we show that a dynamic homology model based on an "active" opsin structure without further incorporation of experimental data performs better than the crystal structure of the inactive B2AR in finding agonists over antagonists/inverse agonists. Such "active-like state" dynamic homology models can therefore be used to selectively identify GPCR agonists in in silico ligand libraries.

The use of G-protein coupled receptor models in lead optimization

With the emerging new crystal structures of G-protein coupled receptors (GPCRs), the number of reported in silico receptor models vastly increases every year. The use of these models in lead optimization (LO) is investigated here. Although there are many studies where GPCR models are used to identify new chemotypes by virtual screening, the classical application in LO is rarely reported. The reason for this may be that the quality of a model, which is appropriate for atomistic modeling, must be very high, and the biology of GPCR ligand-dependent signaling is still not fully understood. However, the few reported studies show that GPCR models can be used efficiently in LO for various problems, such as affinity optimization or tuning of physicochemical parameters.

Prediction of the Human EP1 Receptor Binding Site by Homology Modeling and Molecular Dynamics Simulation

The prostanoid receptor EP1 is a G-protein-coupled receptor (GPCR) known to be involved in a variety of pathological disorders such as pain, fever and inflammation. These receptors are important drug targets, but design of subtype specific agonists and antagonists has been partially hampered by the absence of three-dimensional structures for these receptors. To understand the molecular interactions of the PGE2, an endogen ligand, with the EP1 receptor, a homology model of the human EP1 receptor (hEP1R) with all connecting loops was constructed from the 2.6 Å resolution crystal structure (PDB code: 1L9H) of bovine rhodopsin. The initial model generated by MODELLER was subjected to molecular dynamics simulation to assess quality of the model. Also, a step by step ligand-supported model refinement was performed, including initial docking of PGE2 and iloprost in the putative binding site, followed by several rounds of energy minimizations and molecular dynamics simulations. Docking studies were performed for PGE2 and some other related compounds in the active site of the final hEP1 receptor model. The docking enabled us to identify key molecular interactions supported by the mutagenesis data. Also, the correlation of r²=0.81 was observed between the Ki values and the docking scores of 15 prostanoid compounds. The results obtained in this study may provide new insights toward understanding the active site conformation of the hEP1 receptor and can be used for the structure-based design of novel specific ligands.

An aqueous H+ permeation pathway in the voltage-gated proton channel Hv1

Hv1 voltage-gated proton channels mediate rapid and selective transmembrane H(+) flux and are gated by both voltage and pH gradients. Selective H(+) transfer in membrane proteins is commonly achieved by Grotthuss proton 'hopping' in chains of ionizable amino acid side chains and intraprotein water molecules. To identify whether ionizable residues are required for proton permeation in Hv1, we neutralized candidate residues and measured expressed voltage-gated H(+) currents. Unexpectedly, charge neutralization was insufficient to abrogate either the Hv1 conductance or coupling of pH gradient and voltage-dependent activation. Molecular dynamics simulations revealed water molecules in the central crevice of Hv1 model structures but not in homologous voltage-sensor domain (VSD) structures. Our results indicate that Hv1 most likely forms an internal water wire for selective proton transfer and that interactions between water molecules and S4 arginines may underlie coupling between voltage- and pH-gradient sensing.

Phe369(7.38) at human 5-HT(7) receptors confers interspecies selectivity to antagonists and partial agonists

BACKGROUND AND PURPOSE

Human and rat 5-HT(7) receptors were studied with a particular emphasis on the molecular interactions involved in ligand binding, searching for an explanation to the interspecies selectivity observed for a set of compounds. We performed affinity studies, molecular modelling and site-directed mutagenesis, with special focus on residue Phe(7.38) of the human 5-HT(7) receptor [Cys(7.38) in rat].

EXPERIMENTAL APPROACH

Competition binding studies were performed for seven 5-HT(7) receptor ligands at three different 5-HT(7) receptors. The functional behaviour was evaluated by measuring 5-carboxytryptamine-stimulated cAMP production. Computational simulations were carried out to explore the structural bases in ligand binding observed for these compounds.

KEY RESULTS

Competition experiments showed a remarkable selectivity for the human receptor when compared with the rat receptor. These results indicate that mutating Cys to Phe at position 7.38 profoundly affects the binding affinities at the 5-HT(7) receptor. Computational simulations provide a structural interpretation for this key finding. Pharmacological characterization of compounds mr25020, mr25040 and mr25053 revealed a competitive antagonistic behaviour. Compounds mr22423, mr22433, mr23284 and mr25052 behaved as partial agonists.

CONCLUSIONS AND IMPLICATIONS

We propose that the interspecies difference in binding affinities observed for the compounds at human and rat 5-HT(7) receptors is due to the nature of the residue at position 7.38. Our molecular modelling simulations suggest that Phe(7.38) in the human receptor is integrated in the hydrophobic pocket in the central part of the binding site [Phe(6.51)-Phe(6.52)] and allows a tighter binding of the ligands when compared with the rat receptor.

Homology modeling in drug discovery: current trends and applications

As structural genomics (SG) projects continue to deposit representative 3D structures of proteins, homology modeling methods will play an increasing role in structure-based drug discovery. Although computational structure prediction methods provide a cost-effective alternative in the absence of experimental structures, developing accurate enough models still remains a big challenge. In this contribution, we report the current developments in this field, discuss in silico modeling limitations, and review the successful application of this technique to different stages of the drug discovery process.

How does a membrane protein achieve a vectorial proton transfer via water molecules?

We present a detailed mechanism for the proton transfer from a protein-bound protonated water cluster to the bulk water directed by protein side chains in the membrane protein bacteriorhodopsin. We use a combined approach of time-resolved Fourier transform infrared spectroscopy, molecular dynamics simulations, and X-ray structure analysis to elucidate the functional role of a hydrogen bond between Ser193 and Glu204. These two residues seal the internal protonated water cluster from the bulk water and the protein surface. During the photocycle of bacteriorhodopsin, a transient protonation of Glu204 leads to a breaking of this hydrogen bond. This breaking opens the gate to the extracellular bulk water, leading to a subsequent proton release from the protonated water cluster. We show in detail how the protein achieves vectorial proton transfer via protonated water clusters in contrast to random proton transfer in liquid water.