Influence of orthosteric ligand binding on the conformational dynamics of the β-2-adrenergic receptor via essential dynamics sampling simulation

The influence of the binding of orthosteric ligands on the conformational dynamics of the β-2-adrenoreceptor was identified using the molecular dynamics method. It was found that there was a small fraction of active states of the receptor in its apo (ligand free) ensemble. An analysis of the MD trajectories indicated that this spontaneous activation of the receptor was accompanied by the motion of its VI helix. Thus, the receptor’s constitutive activity is a direct result of its conformational dynamics. On the other hand, the binding of the full agonist resulted in a significant shift in the initial equilibrium towards its active state. Finally, the binding of the inverse agonist stabilized receptor in its inactive state. It is likely that the binding of the inverse agonists might be a universal method of the constitutive activity inhibition. Our results indicate that ligand binding redistributes preexisting conformational degrees of freedom (in accordance to the Monod-Wyman-Changeux Model), rather than causes an induced fit. Therefore, the ensemble of the biologically relevant receptors conformations has been encoded in its spatial structure and individual conformations from that ensemble and might be used by the cell according to the physiological behavior.     

Investigation of the influence of external factors on the conformational dynamics of rhodopsin-like receptors by means of molecular dynamics simulation

Abstract

The study reports about the influence of binding of orthosteric ligands on the conformational dynamics of β-2-adrenoreceptor. Using molecular dynamics (MD) simulation, we found that there was a little fraction of active states of the receptor in its apo (ligand-free) ensemble. Analysis of MD trajectories indicated that such spontaneous activation of the receptor is accompanied by the motion in intracellular part of its alpha-helices. Thus, receptor’s constitutive activity directly results from its conformational dynamics. On the other hand, the binding of a full agonist resulted in a significant shift of the initial equilibrium towards its active state. Finally, the binding of the inverse agonist stabilized the receptor in its inactive state. It is likely that the binding of inverse agonists might be a universal way of constitutive activity inhibition in vivo. Our results indicate that ligand binding redistribute pre-existing conformational degrees of freedom (in accordance to the Monod–Wyman–Changeux Model) of the receptor rather than cause induced fit in it. Therefore, the ensemble of biologically relevant receptor conformations is encoded in its spatial structure, and individual conformations from that ensemble might be used by the cell in conformity with the physiological behavior.     

Systematic exploitation of multiple receptor conformations for virtual ligand screening

The role of virtual ligand screening in modern drug discovery is to mine large chemical collections and to prioritize for experimental testing a comparatively small and diverse set of compounds with expected activity against a target. Several studies have pointed out that the performance of virtual ligand screening can be improved by taking into account receptor flexibility. Here, we systematically assess how multiple crystallographic receptor conformations, a powerful way of discretely representing protein plasticity, can be exploited in screening protocols to separate binders from non-binders. Our analyses encompass 36 targets of pharmaceutical relevance and are based on actual molecules with reported activity against those targets. The results suggest that an ensemble receptor-based protocol displays a stronger discriminating power between active and inactive molecules as compared to its standard single rigid receptor counterpart. Moreover, such a protocol can be engineered not only to enrich a higher number of active compounds, but also to enhance their chemical diversity. Finally, some clear indications can be gathered on how to select a subset of receptor conformations that is most likely to provide the best performance in a real life scenario.     

De novo ligand design to an ensemble of protein structures

We describe a combinatorial method for de novo ligand design to an ensemble of receptor structures. Receptor conformations, protonation states, and structural water molecules are considered consistently within the framework of de novo ligand design. The method relies on Monte Carlo optimization to search the space of ligand structures, conformations, and rigid-body movements as well as receptor models. The method is applied to an ensemble of HIV protease and human collagenase receptor models. Ligand structures generated de novo exhibit the correct hydrogen-bonding pattern in the core of the active site, with hydrophobic groups extending into the receptor S1 and S1' pocket space. Furthermore, it is shown that known ligands are recovered in the correct binding mode and in the native, most tightly binding receptor model.     

A genetic algorithm-based protocol for docking ensembles of small ligands using experimental restraints

Summary A genetic algorithm (GA) based method for docking ensembles of small, flexible ligands to receptor proteins using NMR-derived constraints is described. In this method, three translations and rotations of the ligand and the dihedral angles of the ligand are represented by binary strings and evolve under the genetic operators of cross-over, mutation, migration and selection. The fitness function for the selection process includes distance and dihedral restraints and a repulsive van der Waals term. The GA was applied to a three-atom model system as well as to the streptavidin-biotin complex using simulated intermolecular distance restraints. In both systems, the GA was able to obtain low-energy conformations when only a single binding site was simulated. Calculations were also performed using distance restraints from two distinct binding sites. In these simulations, the GA was able to obtain low-energy conformations corresponding to ligand molecules in each of the two sites. The inclusion of additional ligands in the ensemble did not result in an energetic benefit, confirming that only two ligand conformations were necessary to fulfill the distance restraints. This method allows for a direct investigation of the minimum number of ligand orientations necessary to fulfill experimental distance restraints, and simultaneously yields detailed structural information about each site.     

Retinal Conformation Changes Rhodopsin’s Dynamic Ensemble

G protein-coupled receptors are vital membrane proteins that allosterically transduce biomolecular signals across the cell membrane. However, the process by which ligand binding induces protein conformation changes is not well understood biophysically. Rhodopsin, the mammalian dim-light receptor, is a unique test case for understanding these processes because of its switch-like activity; the ligand, retinal, is bound throughout the activation cycle, switching from inverse agonist to agonist after absorbing a photon. By contrast, the ligand-free opsin is outside the activation cycle and may behave differently. We find that retinal influences rhodopsin dynamics using an ensemble of all-atom molecular dynamics simulations that in aggregate contain 100 μs of sampling. Active retinal destabilizes the inactive state of the receptor, whereas the active ensemble was more structurally homogenous. By contrast, simulations of an active-like receptor without retinal present were much more heterogeneous than those containing retinal. These results suggest allosteric processes are more complicated than a ligand inducing protein conformational changes or simply capturing a shifted ensemble as outlined in classic models of allostery.     

Protein-protein docking with multiple residue conformations and residue substitutions

The protein docking problem has two major aspects: sampling conformations and orientations, and scoring them for fit. To investigate the extent to which the protein docking problem may be attributed to the sampling of ligand side‐chain conformations, multiple conformations of multiple residues were calculated for the uncomplexed (unbound) structures of protein ligands. These ligand conformations were docked into both the complexed (bound) and unbound conformations of the cognate receptors, and their energies were evaluated using an atomistic potential function. The following questions were considered: (1) does the ensemble of precalculated ligand conformations contain a structure similar to the bound form of the ligand? (2) Can the large number of conformations that are calculated be efficiently docked into the receptors? (3) Can near‐native complexes be distinguished from non‐native complexes? Results from seven test systems suggest that the precalculated ensembles do include side‐chain conformations similar to those adopted in the experimental complexes. By assuming additivity among the side chains, the ensemble can be docked in less than 12 h on a desktop computer. These multiconformer dockings produce near‐native complexes and also non‐native complexes. When docked against the bound conformations of the receptors, the near‐native complexes of the unbound ligand were always distinguishable from the non‐native complexes. When docked against the unbound conformations of the receptors, the near‐native dockings could usually, but not always, be distinguished from the non‐native complexes. In every case, docking the unbound ligands with flexible side chains led to better energies and a better distinction between near‐native and non‐native fits. An extension of this algorithm allowed for docking multiple residue substitutions (mutants) in addition to multiple conformations. The rankings of the docked mutant proteins correlated with experimental binding affinities. These results suggest that sampling multiple residue conformations and residue substitutions of the unbound ligand contributes to, but does not fully provide, a solution to the protein docking problem. Conformational sampling allows a classical atomistic scoring function to be used; such a function may contribute to better selectivity between near‐native and non‐native complexes. Allowing for receptor flexibility may further extend these results.     

Inhibition and Reversal of Microbial Attachment by an Antibody with Parasteric Activity against the FimH Adhesin of Uropathogenic E. coli

Attachment proteins from the surface of eukaryotic cells, bacteria and viruses are critical receptors in cell adhesion or signaling and are primary targets for the development of vaccines and therapeutic antibodies. It is proposed that the ligand-binding pocket in receptor proteins can shift between inactive and active conformations with weak and strong ligand-binding capability, respectively. Here, using monoclonal antibodies against a vaccine target protein - fimbrial adhesin FimH of uropathogenic Escherichia coli, we demonstrate that unusually strong receptor inhibition can be achieved by antibody that binds within the binding pocket and displaces the ligand in a non-competitive way. The non-competitive antibody binds to a loop that interacts with the ligand in the active conformation of the pocket but is shifted away from ligand in the inactive conformation. We refer to this as a parasteric inhibition, where the inhibitor binds adjacent to the ligand in the binding pocket. We showed that the receptor-blocking mechanism of parasteric antibody differs from that of orthosteric inhibition, where the inhibitor replaces the ligand or allosteric inhibition where the inhibitor binds at a site distant from the ligand, and is very potent in blocking bacterial adhesion, dissolving surface-adherent biofilms and protecting mice from urinary bladder infection.     

Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking

One approach to incorporate protein flexibility in molecular docking is the use of an ensemble consisting of multiple protein structures. Sequentially docking each ligand into a large number of protein structures is computationally too expensive to allow large-scale database screening. It is challenging to achieve a good balance between docking accuracy and computational efficiency. In this work, we have developed a fast, novel docking algorithm utilizing multiple protein structures, referred to as ensemble docking, to account for protein structural variations. The algorithm can simultaneously dock a ligand into an ensemble of protein structures and automatically select an optimal protein structure that best fits the ligand by optimizing both ligand coordinates and the conformational variable m, where m represents the m-th structure in the protein ensemble. The docking algorithm was validated on 10 protein ensembles containing 105 crystal structures and 87 ligands in terms of binding mode and energy score predictions. A success rate of 93% was obtained with the criterion of root-mean-square deviation <2.5 A if the top five orientations for each ligand were considered, comparable to that of sequential docking in which scores for individual docking are merged into one list by re-ranking, and significantly better than that of single rigid-receptor docking (75% on average). Similar trends were also observed in binding score predictions and enrichment tests of virtual database screening. The ensemble docking algorithm is computationally efficient, with a computational time comparable to that for docking a ligand into a single protein structure. In contrast, the computational time for the sequential docking method increases linearly with the number of protein structures in the ensemble. The algorithm was further evaluated using a more realistic ensemble in which the corresponding bound protein structures of inhibitors were excluded. The results show that ensemble docking successfully predicts the binding modes of the inhibitors, and discriminates the inhibitors from a set of noninhibitors with similar chemical properties. Although multiple experimental structures were used in the present work, our algorithm can be easily applied to multiple protein conformations generated by computational methods, and helps improve the efficiency of other existing multiple protein structure(MPS)-based methods to accommodate protein flexibility.     

Direct assessment of CXCR4 mutant conformations reveals complex link between receptor structure and G(alpha)(i) activation

Ligand binding to G protein-coupled receptors (GPCRs) is thought to induce changes in receptor conformation that translate into activation of downstream effectors. The link between receptor conformation and activity is still insufficiently understood, as current models of GPCR activation fail to take an increasing amount of experimental data into account. To elucidate structure-function relationships in GPCR activation, we used bioluminescence resonance energy transfer to directly assess the conformation of mutants of the chemokine receptor CXCR4. We analyzed substitutions in the arginine cage DRY motif and in the conserved asparagine N(3.35)119, which are pivotal molecular switches for receptor conformation and activation. G(alpha)(i) activation of the mutants was either similar to wild-type CXCR4 (D133N, Y135A, and N119D) or resulted in loss of activity (R134A and N119K). Mutant N119S was constitutively active but further activated by agonist. Bioluminescence resonance energy transfer analysis suggested no simple correlation between conformational changes in response to ligand binding and activation of G(alpha)(i) by the mutants. Different conformations of active receptors were detected (for wild-type CXCR4, D133N, and N119S), suggesting that different receptor conformations are able to trigger G(alpha)(i) activity. Several conformations were also found for inactive mutants. These data provide biophysical evidence for different receptor conformations being active with respect to a single readout. They support models of GPCR structure-activity relationships that take this conformational flexibility of active receptors into account.     

Physical responses of bacterial chemoreceptors

Chemoreceptors of the bacterium Escherichia coli are thought to form trimers of homodimers that undergo conformational changes upon ligand binding and thereby signal a cytoplasmic kinase. We monitored the physical responses of trimers in living cells lacking other chemotaxis proteins by fluorescently tagging receptors and measuring changes in fluorescence anisotropy. These changes were traced to changes in energy transfer between fluorophores on different dimers of a trimer: attractants move these fluorophores farther apart, and repellents move them closer together. These measurements allowed us to define the responses of bare receptor oligomers to ligand binding and compare them to the corresponding response in kinase activity. Receptor responses could be fit by a simple "two-state" model in which receptor dimers are in either active or inactive conformations, from which energy bias and dissociation constants could be estimated. Comparison with responses in kinase-activity indicated that higher-order interactions are dominant in receptor clusters.     

Flexible ligand docking using conformational ensembles.

Molecular docking algorithms suggest possible structures for molecular complexes. They are used to model biological function and to discover potential ligands. A present challenge for docking algorithms is the treatment of molecular flexibility. Here, the rigid body program, DOCK, is modified to allow it to rapidly fit multiple conformations of ligands. Conformations of a given molecule are pre-calculated in the same frame of reference, so that each conformer shares a common rigid fragment with all other conformations. The ligand conformers are then docked together, as an ensemble, into a receptor binding site. This takes advantage of the redundancy present in differing conformers of the same molecule. The algorithm was tested using three organic ligand protein systems and two protein-protein systems. Both the bound and unbound conformations of the receptors were used. The ligand ensemble method found conformations that resembled those determined in X-ray crystal structures (RMS values typically less than 1.5 A). To test the method's usefulness for inhibitor discovery, multi-compound and multi-conformer databases were screened for compounds known to bind to dihydrofolate reductase and compounds known to bind to thymidylate synthase. In both cases, known inhibitors and substrates were identified in conformations resembling those observed experimentally. The ligand ensemble method was 100-fold faster than docking a single conformation at a time and was able to screen a database of over 34 million conformations from 117,000 molecules in one to four CPU days on a workstation.     

Orientation-specific signalling by thrombopoietin receptor dimers

Ligand binding to the thrombopoietin receptor is thought to stabilize an active receptor dimer that regulates megakaryocyte differentiation and platelet formation, as well as haematopoietic stem cell renewal. By fusing a dimeric coiled coil in all seven possible orientations to the thrombopoietin receptor transmembrane (TM)-cytoplasmic domains, we show that specific biological effects and in vivo phenotypes are imparted by distinct dimeric orientations, which can be visualized by cysteine mutagenesis and crosslinking. Using functional assays and computational searches, we identify one orientation that represents the inactive dimeric state and another similar to a physiologically activated receptor. Several other dimeric orientations are identified that induce proliferation and in vivo myeloproliferative and myelodysplastic disorders, indicating the receptor can signal from several dimeric interfaces. The set of dimeric thrombopoietin receptors with different TM orientations may offer new insights into the activation of distinct signalling pathways by a single receptor and suggests that subtle differences in cytokine receptor dimerization provide a new layer of signalling regulation that is relevant for disease.     

Selectivity by Small-Molecule Inhibitors of Protein Interactions Can Be Driven by Protein Surface Fluctuations

Small-molecules that inhibit interactions between specific pairs of proteins have long represented a promising avenue for therapeutic intervention in a variety of settings. Structural studies have shown that in many cases, the inhibitor-bound protein adopts a conformation that is distinct from its unbound and its protein-bound conformations. This plasticity of the protein surface presents a major challenge in predicting which members of a protein family will be inhibited by a given ligand. Here, we use biased simulations of Bcl-2-family proteins to generate ensembles of low-energy conformations that contain surface pockets suitable for small molecule binding. We find that the resulting conformational ensembles include surface pockets that mimic those observed in inhibitor-bound crystal structures. Next, we find that the ensembles generated using different members of this protein family are overlapping but distinct, and that the activity of a given compound against a particular family member (ligand selectivity) can be predicted from whether the corresponding ensemble samples a complementary surface pocket. Finally, we find that each ensemble includes certain surface pockets that are not shared by any other family member: while no inhibitors have yet been identified to take advantage of these pockets, we expect that chemical scaffolds complementing these “distinct” pockets will prove highly selective for their targets. The opportunity to achieve target selectivity within a protein family by exploiting differences in surface fluctuations represents a new paradigm that may facilitate design of family-selective small-molecule inhibitors of protein-protein interactions.