Dynamic Conformational Ensembles Research Articles

Accelerating the Conformational Sampling of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) are a class of proteins lacking a well-defined secondary structure. Instead, they are able to attain multiple conformations, bind to multiple targets, and respond to changes in their surroundings. Functionally, IDPs have been associated with molecular recognition, cell regulation, and signal transduction. The dynamic conformational ensemble of IDPs is highly environmental and binding partner dependent, rendering the characterization of IDPs extremely challenging. Here, we compare the sampling efficiencies of conventional molecular dynamics (MD), well-tempered metadynamics (WT-META), and bias-exchange metadynamics (BE-META). The total simulation time was over 10 μs, and a 20-mer peptide derived from the Neh2 domain of the Nuclear factor erythroid 2-related factor 2 (Nrf2) protein was simulated. BE-META, with a neutral replica and seven biased replicas employing a set of seven relevant collective variables (CVs), provided the most reliable and efficient sampling. Finally, we propose a free-energy reconstruction method based on the probability distribution of the secondary structure contents. This postprocessing analysis confirms the presence of not only the β-hairpin conformation of the free Neh2 peptide but also its rare bound-state-like conformation, both of that have been experimentally observed. In addition, our simulations also predict other possible conformations to be verified with future experiments.

Exploration of conformational spaces of high-mannose-type oligosaccharides by an NMR-validated simulation.

Exploration of the conformational spaces of flexible biomacromolecules is essential for quantitatively understanding the energetics of their molecular recognition processes. We employed stable isotope- and lanthanide-assisted NMR approaches in conjunction with replica-exchange molecular dynamics (REMD) simulations to obtain atomic descriptions of the conformational dynamics of high-mannose-type oligosaccharides, which harbor intracellular glycoprotein-fate determinants in their triantennary structures. The experimentally validated REMD simulation provided quantitative views of the dynamic conformational ensembles of the complicated, branched oligosaccharides, and indicated significant expansion of the conformational space upon removal of a terminal mannose residue during the functional glycan-processing pathway.

Exploration of Conformational Spaces of High‐Mannose‐Type Oligosaccharides by an NMR‐Validated Simulation

AbstractExploration of the conformational spaces of flexible biomacromolecules is essential for quantitatively understanding the energetics of their molecular recognition processes. We employed stable isotope‐ and lanthanide‐assisted NMR approaches in conjunction with replica‐exchange molecular dynamics (REMD) simulations to obtain atomic descriptions of the conformational dynamics of high‐mannose‐type oligosaccharides, which harbor intracellular glycoprotein‐fate determinants in their triantennary structures. The experimentally validated REMD simulation provided quantitative views of the dynamic conformational ensembles of the complicated, branched oligosaccharides, and indicated significant expansion of the conformational space upon removal of a terminal mannose residue during the functional glycan‐processing pathway.

Electrostatics-Dependent Shape of the Intrinsically-Disordered Protein Sic1

For intrinsically disordered proteins (IDPs) containing a high density of charged residues, a Gaussian chain is an inadequate description of the protein's shape. One such IDP is Sic1, a highly positively charged IDP in the budding yeast Saccharomyces Cerevisiae which prevents the cell cycle from entering the S-phase from the G1-phase. Sic1's binding affinity for Cdc4 is highly phosphorylation state dependent, although the corresponding physical basis is not fully understood. NMR data supports the presence of a dynamic complex of Sic1:Cdc4 and a poly-electrostatic model has been proposed by Forman-Kay and coworkers.We studied the Sic1 N-terminal targeting region (1-90) to better understand the role of intrachain electrostatics, and to compare with the structural ensembles calculated from NMR and SAXS data. Sic1 is characterized using time-resolved fluorescence anisotropy (TRFA), which is sensitive to rotational and conformational dynamics. Sic1 exists in a dynamic ensemble of conformations and ensemble-averaged experiments have limitations in identifying and characterizing static and/or dynamic inhomogeneity in the motional dynamics. Therefore, we also performed burst spectroscopy and single-molecule TRFA on freely diffusing Sic1. Shape and flexibility were probed by varying the degree of intrachain repulsion screening through adjusting salt concentrations and described within a polymer physics framework, the polyelectrolyte model. To investigate the relative contributions of “global rotation” and “conformational flexibility”, Sic1 was labelled at three different sites. Sic1 is found to be well modelled as a prolate ellipsoid with internal flexibility.The single-molecule derived TRFA distribution data may be valuable as a constraint incorporated in future conformational ensemble calculations, complementary to SAXS and NMR data. Additionally, these measurements raise questions about the accuracy of highly charged IDP's radii of gyration when calculated from sm-FRET derived end-to-end distances, which often assume a Gaussian chain model for the end-to-end distance probability distribution.

Single-Molecule Measurements of the CCR5 mRNA Unfolding Pathways

Secondary or tertiary structure in an mRNA, such as a pseudoknot, can create a physical barrier that requires the ribosome to generate additional force to translocate. The presence of such a barrier can dramatically increase the probability that the ribosome will shift into an alternate reading frame, in which a different set of codons is recognized. The detailed biophysical mechanism by which frameshifting is induced remains unknown. Here we employ optical trapping techniques to investigate the structure of a −1 programmed ribosomal frameshift (−1 PRF) sequence element located in the CCR5 mRNA, which encodes a coreceptor for HIV-1 and is, to our knowledge, the first known human −1 PRF signal of nonviral origin. We begin by presenting a set of computationally predicted structures that include pseudoknots. We then employ what we believe to be new analytical techniques for measuring the effective free energy landscapes of biomolecules. We find that the −1 PRF element manifests several distinct unfolding pathways when subject to end-to-end force, one of which is consistent with a proposed pseudoknot conformation, and another of which we have identified as a folding intermediate. The dynamic ensemble of conformations that CCR5 mRNA exhibits in the single-molecule experiments may be a significant feature of the frameshifting mechanism.

MD Simulation Trajectories of Multiple Intrinsically Disordered Proteins Reveal Order to Disorder Transitions that Bear Functional Significance

Intrinsically disordered proteins (IDPs) explore a dynamic ensemble of conformations and yet retain a functional role inside the cell. However, the correlation of backbone chain dynamics of an IDP correlated with its cellular function is not fully understood. Here in this work we analyze the MD simulation trajectories (12500 timesteps of total 10 nanosecond duration) of one ordered protein (catalytic domain of MutY from E. Coli, pdb code: 1MUN), one partially ordered protein (Apoptosis regulator Bcl-xL, 1LXL) and four IDPs (Brak/CXCL14, 2HDL; sub-domain of staphylococcal nuclease, 2SOB; F6 subunit of ATP synthase, 1VZS and Tyrosyl tRNA synthestase, 1JH3). The analysis included distance variations between chosen multiple points in the protein backbone, probability distributions of the measured distances and their velocities, and full width half maxima of these probability distributions. The results from the analysis yielded a quantitative measure of dynamics at loop regions in comparison to helix and strand regions. In addition the distance probability distributions of loop regions in IDPs specifically displayed multimodal character indicating distinct preferences for certain distances. This was in contrast to velocity probability distributions which were always of unimodal nature for all the six proteins. Further, we attempted to quantify the randomness in disordered chain dynamics by computing the Boltzmann entropy for all c-alpha atoms in each of the proteins. This entropy value for a given c-alpha atom correlated with its wandering ability in space. Disorder-order transition regions were spotted from the created protein movies and analyzed quantitatively by constructing Ramachandran plots for those regions across all time steps. Such regions included lysine residues previously speculated to be involved in post-translational modifications in F6 unit of ATP synthase and RNA binding domain in Tyrosyl tRNA synthestase.

Probing Drug-Binding Pathways in P-Glycoprotein with Ensemble Docking

P-glycoprotein (P-gp) is one of the key members of the ATP-binding cassette (ABC) transporters family and the major contributor of multidrug resistance against a broad spectrum of drugs in cancer cells. Powered by ATP, P-gp acts as an efflux pump to export a diverse set of hydrophobic molecules, including drugs, out of the cell. These hydrophobic substrates are assumed to enter the translocation pathway of P-gp either via the intracellular side of the cell or directly from the cytoplasmic leaflet of the membrane. In order to characterize the mechanism, residues facilitating drug entry, and translocation, we have taken an approach combining the strengths of molecular dynamics (MD) and molecular docking. A 100 ns MD simulation of membrane-bound inward facing P-gp with Mg2+ and ATP was performed and subsequently used in ensemble docking. Doxorubicin, one of the drug substrates of P-gp, was docked into the defined active sites of 10,000 different snapshots representing the conformational flexibility of the protein in the membrane. Clustered docked poses identified the binding sites and yielded a picture of the sequence of binding events of the substrate within the translocation pathway. Interestingly, a few of the highly populated clusters were located within the region that interacts with the cytoplasmic leaflet of the membrane supporting the recruitment of the substrate laterally and directly from the membrane. Further MD simulations and energetic calculations of representative substrate poses are then used to characterize their real-time binding behavior and dynamics within the intracellular lumen and at the cytoplasmic leaflet of the membrane. This study, for the first time, explored and utilized the dynamic ensemble of conformations of P-gp in molecular docking and dissected important and complex features of its translocation pathway.

Using enveloping distribution sampling to compute the folding free enthalpy of a β-peptide with a very unstable folded conformation in solution: The advantage of focused sampling using EDS

A peptide or a protein adopts a dynamic ensemble of conformations rather than a single structure in solution, although this ensemble may be dominated by one or a few particular folds. Computer simulation can be used to simulate the folding equilibria of peptides from which free energy differences between different conformations can be calculated. However, standard molecular dynamics (MD) simulation is rather inefficient when the relative free energy of a rather unstable fold is to be calculated. Here, we show, using a hepta-β-peptide with a very unstable 314-helical conformation as an example, that the method of enveloping distribution sampling (EDS) offers a much more efficient alternative to compute the relative free energy of different folds. The folding free energies obtained using the EDS method are compared with those obtained from three other methods: a standard MD simulation, from reweighting trajectories generated using hydrogen-bond restraints as umbrella potential energy term to enhance the sampling of a particular fold, and from one-step perturbation. The EDS method yields the widest sampling of relevant conformations and shows the fastest convergence.

Conformation and dynamics of the periplasmic membrane-protein–chaperone complexes OmpX–Skp and tOmpA–Skp

The biogenesis of integral outer-membrane proteins (OMPs) in Gram-negative bacteria requires molecular chaperones that prevent the aggregation of OMP polypeptides in the aqueous periplasmic space. How these energy-independent chaperones interact with their substrates is not well understood. We have used high-resolution NMR spectroscopy to examine the conformation and dynamics of the Escherichia coli periplasmic chaperone Skp and two of its complexes with OMPs. The Skp trimer constitutes a flexible architectural scaffold that becomes more rigid upon substrate binding. The OMP substrates populate a dynamic conformational ensemble with structural interconversion rates on the submillisecond timescale. The global lifetime of the chaperone-substrate complex is seven orders of magnitude longer, emerging from the short local lifetimes by avidity. The dynamic state allows for energy-independent substrate release and provides a general paradigm for the conformation of OMP polypeptides bound to energy-independent chaperones.

Addressing Selective Polypharmacology of Antipsychotic Drugs Targeting the Bioaminergic Receptors through Receptor Dynamic Conformational Ensembles

Selective polypharmacology, where a drug acts on multiple rather than a single molecular target involved in a disease, emerges to develop a structure-based system biology approach to design drugs selectively targeting a disease-active protein network. We focus on the bioaminergic receptors that belong to the group of G-protein-coupled receptors (GPCRs) and represent targets for therapeutic agents against schizophrenia and depression. Among them, it has been shown that the serotonin (5-HT(2A) and 5-HT₆) and dopamine (D₂ and D₃) receptors induce a cognition-enhancing effect (group 1), while the histamine (H₁) and serotonin (5-HT(2C)) receptors lead to metabolic side effects and the 5-HT(2B) serotonin receptor causes pulmonary hypertension (group 2). Thus, the problem arises to develop an approach that allows identifying drugs targeting only the disease-active receptors, i.e. group 1. The recent release of several crystal structures of the bioaminergic receptors, involving the D₃ and H₁ receptors, provides the possibility to model the structures of all receptors and initiate a study of the structural and dynamic context of selective polypharmacology. In this work, we use molecular dynamics simulations to generate a conformational space of the receptors and subsequently characterize its binding properties applying molecular probe mapping. All-against-all comparison of the generated probe maps of the selected diverse conformations of all receptors with the Tanimoto similarity coefficient (Tc) enable the separation of the receptors of group 1 from group 2. The pharmacophore built based on the Tc-selected receptor conformations, using the multiple probe maps discovers structural features that can be used to design molecules selective toward the receptors of group 1. The importance of several predicted residues to ligand selectivity is supported by the available mutagenesis and ligand structure-activity relationship studies. In addition, the Tc-selected conformations of the receptors for group 1 show good performance in isolation of known ligands from a random decoy. Our computational structure-based protocol to tackle selective polypharmacology of antipsychotic drugs could be applied for other diseases involving multiple drug targets, such as oncologic and infectious disorders.

Probing Local Backbone Geometries in Intrinsically Disordered Proteins by Cross-Correlated NMR Relaxation.

Probing Local Backbone Geometries in Intrinsically Disordered Proteins by Cross-Correlated NMR Relaxation.

On the supertertiary structure of proteins

Intrinsically disordered proteins and complex multidomain proteins are characterized by a dynamic ensemble of conformations that cannot be unequivocally described by traditional static terms of structural biology. The functional importance of this structural complexity necessitates new standards and protocols for the description and deposition of such 'supertertiary' structural ensembles into structural databases.

Application of Paramagnetic NMR-Validated Molecular Dynamics Simulation to the Analysis of a Conformational Ensemble of a Branched Oligosaccharide

Oligosaccharides of biological importance often exhibit branched covalent structures and dynamic conformational multiplicities. Here we report the application of a method that we developed, which combined molecular dynamics (MD) simulations and lanthanide-assisted paramagnetic NMR spectroscopy, to evaluate the dynamic conformational ensemble of a branched oligosaccharide. A lanthanide-chelating tag was attached to the reducing end of the branched tetrasaccharide of GM2 ganglioside to observe pseudocontact shifts as the source of long distance information for validating the conformational ensemble derived from MD simulations. By inspecting the results, the conformational space of the GM2 tetrasaccharide was compared with that of its nonbranched derivative, the GM3 trisaccharide.

Lanthanide-assisted NMR evaluation of a dynamic ensemble of oligosaccharide conformations

A novel methodology is presented for evaluating a dynamic ensemble of oligosaccharide conformations by lanthanide-assisted NMR spectroscopy combined with molecular dynamics (MD) simulations. The results obtained using the GM3 trisaccharide demonstrated that pseudocontact shift measurements offer a valuable experimental tool for the validation of MD simulations of highly flexible biomolecules.

A Systematic Study of the Energetics Involved in Structural Changes upon Association and Connectivity in Protein Interaction Networks

The study of protein binding mechanisms is a major topic of research in structural biology. Here, we implement a combination of metrics to systematically assess the cost of backbone conformational changes that protein domains undergo upon association. Through the analyses of 2090 unique unbound → bound transitions, from over 12,000 structures, we show that two-thirds of these proteins do not suffer significant structural changes upon binding, and could thus fit the lock-and-key model well. Among the remaining proteins, one-third explores the bound conformation in the unbound state (conformational selection model) and, while most transitions are possible from an energetic perspective, a few do require external help to break the thermodynamic barrier (induced fit model). We also analyze the relationship between conformational transitions and protein connectivity, finding that, in general, domains interacting with many partners undergo smaller changes upon association, and are less likely to freely explore larger conformational changes.

MD Simulations Highlight the Contrast in Dynamics of Intrinsically Disordered Proteins When Compared with Folded Proteins

Intrinsically Disordered Proteins (IDPs) lack a stable three-dimensional structure in substantial regions or throughout their sequence and exist as highly dynamic conformational ensembles. However, IDPs perform essential biological functions like regulation or signalling where their unique structural plasticity plays a crucial role. They comprise nearly 30% of proteins in the eukaryotic genome. Many IDPs are found to be associated with human diseases like cancer, cardiovascular disease, amyloidoses, neurodegenerative diseases and diabetes.

CoNSEnsX: an ensemble view of protein structures and NMR-derived experimental data

BackgroundIn conjunction with the recognition of the functional role of internal dynamics of proteins at various timescales, there is an emerging use of dynamic structural ensembles instead of individual conformers. These ensembles are usually substantially more diverse than conventional NMR ensembles and eliminate the expectation that a single conformer should fulfill all NMR parameters originating from 1016 - 1017 molecules in the sample tube. Thus, the accuracy of dynamic conformational ensembles should be evaluated differently to that of single conformers.ResultsWe constructed the web application CoNSEnsX (Consistency of NMR-derived Structural Ensembles with eXperimental data) allowing fast, simple and convenient assessment of the correspondence of the ensemble as a whole with diverse independent NMR parameters available. We have chosen different ensembles of three proteins, human ubiquitin, a small protease inhibitor and a disordered subunit of cGMP phosphodiesterase 5/6 for detailed evaluation and demonstration of the capabilities of the CoNSEnsX approach.ConclusionsOur results present a new conceptual method for the evaluation of dynamic conformational ensembles resulting from NMR structure determination. The designed CoNSEnsX approach gives a complete evaluation of these ensembles and is freely available as a web service at http://consensx.chem.elte.hu.

Allostery and population shift in drug discovery.

Proteins can exist in a large number of conformations around their native states that can be characterized by an energy landscape. The landscape illustrates individual valleys, which are the conformational substates. From the functional standpoint, there are two key points: first, all functionally relevant substates pre-exist; and second, the landscape is dynamic and the relative populations of the substates will change following allosteric events. Allosteric events perturb the structure, and the energetic strain propagates and shifts the population. This can lead to changes in the shapes and properties of target binding sites. Here we present an overview of dynamic conformational ensembles focusing on allosteric events in signaling. We propose that combining equilibrium fluctuation concepts with genomic screens could help drug discovery.

Erratum: The role of dynamic conformational ensembles in biomolecular recognition

Erratum: The role of dynamic conformational ensembles in biomolecular recognition

The role of dynamic conformational ensembles in biomolecular recognition

Molecular recognition is central to all biological processes. For the past 50 years, Koshland's 'induced fit' hypothesis has been the textbook explanation for molecular recognition events. However, recent experimental evidence supports an alternative mechanism. 'Conformational selection' postulates that all protein conformations pre-exist, and the ligand selects the most favored conformation. Following binding the ensemble undergoes a population shift, redistributing the conformational states. Both conformational selection and induced fit appear to play roles. Following binding by a primary conformational selection event, optimization of side chain and backbone interactions is likely to proceed by an induced fit mechanism. Conformational selection has been observed for protein-ligand, protein-protein, protein-DNA, protein-RNA and RNA-ligand interactions. These data support a new molecular recognition paradigm for processes as diverse as signaling, catalysis, gene regulation and protein aggregation in disease, which has the potential to significantly impact our views and strategies in drug design, biomolecular engineering and molecular evolution.