Cyanine Dye Coupling Mediates Self-assembly of a pH Sensitive Peptide into Novel 3D Architectures.

Synthetic multichromophore systems are of great importance in artificial light harvesting devices, organic optoelectronics, tumor imaging and therapy. Here, we introduce a promising strategy for the construction of self-assembled peptide templated dye stacks based on coupling of a de novo designed pH sensitive peptide with a cyanine dye Cy5 at its N-terminus. Microscopic techniques, in particular cryogenic TEM (cryo-TEM) and cryo-electron tomography technique (cryo-ET), reveal two types of highly ordered three-dimensional assembly structures on the micrometer scale. Unbranched compact layered rods are observed at pH 7.4 and two-dimensional membrane-like assemblies at pH 3.4, both species displaying spectral features of H-aggregates. Molecular dynamics simulations reveal that the coupling of Cy5 moieties promotes the formation of both ultrastructures, whereas the protonation states of acidic and basic amino acid side chains dictates their ultimate three-dimensional organization.

Allosteric modulation of the sarcoplasmic reticulum Ca2+ ATPase by thapsigargin via decoupling of functional motions.

The sarcoplasmic reticulum Ca2+-ATPase (SERCA) is a widely studied member of the large family of phosphorylation(P)-type ATPase membrane transporters. Ligands and nucleotide binding naturally modulate the conformational space of P-type ATPases through allosteric inter-domain communications. Whereas many inhibitory ATPase ligands act by directly blocking substrate uptake or release, SERCA is a target for thapsigargin (TG), a plant-derived natural product that allosterically inhibits the transport cycle. While thapsigargin's inhibitory effects on SERCA have been widely studied experimentally, the molecular mechanisms underlying these remain incompletely understood. Here, we apply modelling and molecular simulations to probe the effects of TG binding to the major functional states along SERCA's reaction cycle. Our results provide insight into the atomic-level details of the conformational changes induced by TG binding to SERCA, and suggest mechanisms for its effect. Since other P-type ATPases share closely related reaction cycles, our data suggests that similar modulators might exist for these.

Binding, Thermodynamics, and Selectivity of a Non-peptide Antagonist to the Melanocortin-4 Receptor.

The melanocortin-4 receptor (MC4R) is a potential drug target for treatment of obesity, anxiety, depression, and sexual dysfunction. Crystal structures for MC4R are not yet available, which has hindered successful structure-based drug design. Using microsecond-scale molecular-dynamics simulations, we have investigated selective binding of the non-peptide antagonist MCL0129 to a homology model of human MC4R (hMC4R). This approach revealed that, at the end of a multi-step binding process, MCL0129 spontaneously adopts a binding mode in which it blocks the agonistic-binding site. This binding mode was confirmed in subsequent metadynamics simulations, which gave an affinity for human hMC4R that matches the experimentally determined value. Extending our simulations of MCL0129 binding to hMC1R and hMC3R, we find that receptor subtype selectivity for hMC4R depends on few amino acids located in various structural elements of the receptor. These insights may support rational drug design targeting the melanocortin systems.

Multiple Binding Sites Contribute to the Mechanism of Mixed Agonistic and Positive Allosteric Modulators of the Cannabinoid CB1 Receptor.

The cannabinoid CB1 receptor (CB1R) is an abundant metabotropic G-protein-coupled receptor that has been difficult to address therapeutically because of CNS side effects exerted by orthosteric drug candidates. Recent efforts have focused on developing allosteric modulators that target CB1R. Compounds from the recently discovered class of mixed agonistic and positive allosteric modulators (Ago-PAMs) based on 2-phenylindoles have shown promising functional and binding properties as CB1R ligands. Here, we identify binding modes of both the CP 55,940 agonist and GAT228, a 2-phenylindole allosteric modulator, by using our metadynamics simulation protocol, and quantify their affinity and cooperativity by atomistic simulations. We demonstrate the involvement of multiple adjunct binding sites in the Ago-PAM characteristics of the 2-phenylindole modulators and explain their ability to compete with orthosteric agonists at higher concentrations. We validate these results experimentally by showing the contribution of multiple sites on the allosteric binding of ZCZ011, another homologous member of the class, together with the orthosteric agonist.

Molecular Mechanisms of Biased and Probe-Dependent Signaling at CXC-Motif Chemokine Receptor CXCR3 Induced by Negative Allosteric Modulators.

Our recent explorations of allosteric modulators with improved properties resulted in the identification of two biased negative allosteric modulators, BD103 (N-1-{[3-(4-ethoxyphenyl)-4-oxo-3,4-dihydropyrido[2,3-d]pyrimi-din2yl]ethyl}-4-(4-fluorobutoxy)-N-[(1-methylpiperidin-4-yl)methyl}]butanamide) and BD064 (5-[(N-{1-[3-(4-ethoxyphenyl)-4-oxo-3,4-dihydropyrido[2,3-d]pyrimidin-2-yl]ethyl-2-[4-fluoro-3-(trifluoromethyl)phenyl]acetamido)methyl]-2-fluorophenyl}boronic acid), that exhibited probe-dependent inhibition of CXC-motif chemokine receptor CXCR3 signaling. With the intention to elucidate the structural mechanisms underlying their selectivity and probe dependence, we used site-directed mutagenesis combined with homology modeling and docking to identify amino acids of CXCR3 that contribute to modulator binding, signaling, and transmission of cooperativity. With the use of allosteric radioligand RAMX3 ([3H]N-{1-[3-(4-ethoxyphenyl)-4-oxo-3,4-dihydropyrido[2,3-d]pyrimidin-2-yl]ethyl}-2-[4-fluoro-3-(trifluoromethyl)phenyl]-N-[(1-methylpiperidin-4-yl)methyl]acetamide), we identified that F1313.32 and Y3087.43 contribute specifically to the binding pocket of BD064, whereas D1864.60 solely participates in the stabilization of binding conformation of BD103. The influence of mutations on the ability of negative allosteric modulators to inhibit chemokine-mediated activation (CXCL11 and CXCL10) was assessed with the bioluminescence resonance energy transfer-based cAMP and ß-arrestin recruitment assay. Obtained data revealed complex molecular mechanisms governing biased and probe-dependent signaling at CXCR3. In particular, F1313.32, S3047.39, and Y3087.43 emerged as key residues for the compounds to modulate the chemokine response. Notably, D1864.60, W2686.48, and S3047.39 turned out to play a role in signal pathway selectivity of CXCL10, as mutations of these residues led to a G protein-active but ß-arrestin-inactive conformation. These diverse effects of mutations suggest the existence of ligand- and pathway-specific receptor conformations and give new insights in the sophisticated signaling machinery between allosteric ligands, chemokines, and their receptors, which can provide a powerful platform for the development of new allosteric drugs with improved pharmacological properties.

Differences between G-Protein-Stabilized Agonist-GPCR Complexes and their Nanobody-Stabilized Equivalents.

Protein nanobodies have been used successfully as surrogates for unstable G-proteins in order to crystallize G-protein-coupled receptors (GPCRs) in their active states. We used molecular dynamics (MD) simulations, including metadynamics enhanced sampling, to investigate the similarities and differences between GPCR-agonist ternary complexes with the α-subunits of the appropriate G-proteins and those with the protein nanobodies (intracellular binding partners, IBPs) used for crystallization. In two of the three receptors considered, the agonist-binding mode differs significantly between the two alternative ternary complexes. The ternary-complex model of GPCR activation entails enhancement of ligand binding by bound IBPs: Our results show that IBP-specific changes can alter the agonist binding modes and thus also the criteria for designing GPCR agonists.

An Efficient Metadynamics-Based Protocol To Model the Binding Affinity and the Transition State Ensemble of G-Protein-Coupled Receptor Ligands.

A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites. The protocol can be used with X-ray structures or high-quality homology models (based on a high-quality template and after thorough refinement) for the receptor and is universally applicable to agonists, antagonists, and partial and reverse agonists. The root-mean-square error (RMSE) in predicted binding free energies for 12 diverse ligands in five receptors (a total of 23 data points) is surprisingly small (less than 1 kcal mol-1). The RMSEs for simulations that use receptor X-ray structures and homology models are very similar.

Investigating allosteric effects on the functional dynamics of ß2-adrenergic ternary complexes with enhanced-sampling simulations.

Signalling by G-protein coupled receptors usually occurs via ternary complexes formed under cooperative binding between the receptor, a ligand and an intracellular binding partner (a G-protein or ß-arrestin). While a global rational for allosteric effects in ternary complexes would be of great help in designing ligands with specific effects, the paucity of structural data for ternary complexes with ß-arrestin, together with the intrinsic difficulty of characterizing the dynamics involved in the allosteric coupling, have hindered the efforts to devise such a model. Here we have used enhanced-sampling atomistic molecular-dynamics simulations to investigate the dynamics and complex formation mechanisms of both ß-arrestin- and Gs-complexes with the ß2-adrenergic receptor (ADRB2) in its apo-form and in the presence of four small ligands that exert different allosteric effects. Our results suggest that the structure and dynamics of arrestin-ADRB2 complexes depend strongly on the nature of the small ligands. The complexes exhibit a variety of different coupling orientations in terms of the depth of the finger loop in the receptor and activation states of ADRB2. The simulations also allow us to characterize the cooperativity between the ligand and intracellular binding partner (IBP). Based on the complete and consistent results, we propose an experimentally testable extended ternary complex model, where direction of the cooperative effect between ligand and IBP (positive or negative) and its magnitude are predicted to be a characteristic of the ligand signaling bias. This paves the avenue to the rational design of ligands with specific functional effects.

Identification of Two Distinct Sites for Antagonist and Biased Agonist Binding to the Human Chemokine Receptor CXCR3.

The chemokine receptor CXCR3 is a G protein-coupled receptor that conveys extracellular signals into cells by changing its conformation upon ligand binding. We previously hypothesized that small-molecule allosteric CXCR3-agonists do not bind to the same allosteric binding pocket as 8-azaquinazolinone-based negative allosteric modulators. We have now performed molecular-dynamics (MD) simulations with metadynamics enhanced sampling on the CXCR3 system to refine structures and binding modes and to predict the CXCR3-binding affinities of the biased allosteric agonist FAUC1036 and the negative allosteric modulator RAMX3. We have identified two distinct binding sites; a "shallow" and a second "deeper" pocket to which the biased allosteric agonist FAUC1036 and negative allosteric modulator RAMX3 bind, respectively.

Can Simulations and Modeling Decipher NMR Data for Conformational Equilibria? Arginine-Vasopressin.

Arginine vasopressin (AVP) has been suggested by molecular-dynamics (MD) simulations to exist as a mixture of conformations in solution. The (1)H and (13)C NMR chemical shifts of AVP in solution have been calculated for this conformational ensemble of ring conformations (identified from a 23 µs molecular-dynamics simulation). The relative free energies of these conformations were calculated using classical metadynamics simulations in explicit water. Chemical shifts for representative conformations were calculated using density-functional theory. Comparison with experiment and analysis of the results suggests that the (1)H chemical shifts are most useful for assigning equilibrium concentrations of the conformations in this case. (13)C chemical shifts distinguish less clearly between conformations, and the distances calculated from the nuclear Overhauser effect do not allow the conformations to be assigned clearly. The (1)H chemical shifts can be reproduced with a standard error of less than 0.24 ppm (<2.2 ppm for (13)C). The combined experimental and theoretical results suggest that AVP exists in an equilibrium of approximately 70% saddlelike and 30% clinched open conformations. Both newly introduced statistical metrics designed to judge the significance of the results and Smith and Goodman's DP4 probabilities are presented.

A Three-Site Mechanism for Agonist/Antagonist Selective Binding to Vasopressin Receptors.

Molecular-dynamics simulations with metadynamics enhanced sampling reveal three distinct binding sites for arginine vasopressin (AVP) within its V2 -receptor (V2 R). Two of these, the vestibule and intermediate sites, block (antagonize) the receptor, and the third is the orthosteric activation (agonist) site. The contacts found for the orthosteric site satisfy all the requirements deduced from mutagenesis experiments. Metadynamics simulations for V2 R and its V1a R-analog give an excellent correlation with experimental binding free energies by assuming that the most stable binding site in the simulations corresponds to the experimental binding free energy in each case. The resulting three-site mechanism separates agonists from antagonists and explains subtype selectivity.

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology.

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r(2) of 0.71 and root-mean-squared-error of 1.25 kcal/mol (N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.