Conformational equilibria and free energy profiles for the allosteric transition of the ribose-binding protein

Rosetta Energy Analysis of AlphaFold2 models: Point Mutations and Conformational Ensembles

There has been an explosive growth in the applications of AlphaFold2, and other structure prediction platforms, to accurately predict protein structures from a multiple sequence alignment (MSA) for downstream structural analysis. However, two outstanding questions persist in the field regarding the robustness of AlphaFold2 predictions of the consequences of point mutations and the completeness of its prediction of protein conformational ensembles. We combined our previously developed method SPEACH_AF with model relaxation and energetic analysis with Rosetta to address these questions. SPEACH_AF introduces residue substitutions across the MSA and not just within the input sequence. With respect to conformational ensembles, we combined SPEACH_AF and a new MSA subsampling method, AF_cluster, and for a benchmarked set of proteins, we found that the energetics of the conformational ensembles generated by AlphaFold2 correspond to those of experimental structures and explored by standard molecular dynamic methods. With respect to point mutations, we compared the structural and energetic consequences of having the mutation(s) in the input sequence versus in the whole MSA (SPEACH_AF). Both methods yielded models different from the wild-type sequence, with more robust changes when the mutation(s) were in the whole MSA. While our findings demonstrate the robustness of AlphaFold2 in analyzing point mutations and exploring conformational ensembles, they highlight the need for multi parameter structural and energetic analyses of these models to generate experimentally testable hypotheses.

Computation of the Protein Conformational Transition Pathway on Ligand Binding by Linear Response-Driven Molecular Dynamics

While extremely important for relating the protein structure to its biological function, determination of the protein conformational transition pathway upon ligand binding is made difficult due to the transient nature of intermediates, a large and rugged conformational space, and coupling between protein dynamics and ligand-protein interactions. Existing methods that rely on prior knowledge of the bound (holo) state structure are restrictive. A second concern relates to the correspondence of intermediates obtained to the metastable states on the apo → holo transition pathway. Here, we have taken the protein apo structure and ligand-binding site as only inputs and combined an elastic network model (ENM) representation of the protein Hamiltonian with linear response theory (LRT) for protein-ligand interactions to identify the set of slow normal modes of protein vibrations that have a high overlap with the direction of the protein conformational change. The structural displacement along the chosen direction was performed using excited normal modes molecular dynamics (MDeNM) simulations rather than by the direct use of LRT. Herein, the MDeNM excitation velocity was optimized on-the-fly on the basis of its coupling to protein dynamics and ligand-protein interactions. Thus, a determined set of structures was validated against crystallographic and simulation data on four protein-ligand systems, namely, adenylate kinase-di(adenosine-5')pentaphosphate, ribose binding protein-β-d-ribopyranose, DNA β-glucosyltransferase-uridine-5'-diphosphate, and G-protein α subunit-guanosine-5'-triphosphate, which present important differences in protein conformational heterogeneity, ligand binding mechanism, viz. induced-fit or conformational selection, extent, and nonlinearity in protein conformational changes upon ligand binding, and presence of allosteric effects. The obtained set of intermediates was used as an input to path metadynamics simulations to obtain the free energy profile for the apo → holo transition.

Multiscale Enhanced Sampling Using Machine Learning

Multiscale enhanced sampling (MSES) allows for an enhanced sampling of all-atom protein structures by coupling with the accelerated dynamics of the associated coarse-grained (CG) model. In this paper, we propose an MSES extension to replace the CG model with the dynamics on the reduced subspace generated by a machine learning approach, the variational autoencoder (VAE). The molecular dynamic (MD) trajectories of the ribose-binding protein (RBP) in both the closed and open forms were used as the input by extracting the inter-residue distances as the structural features in order to train the VAE model, allowing the encoded latent layer to characterize the difference in the structural dynamics of the closed and open forms. The interpolated data characterizing the RBP structural change in between the closed and open forms were thus efficiently generated in the low-dimensional latent space of the VAE, which was then decoded into the time-series data of the inter-residue distances and was useful for driving the structural sampling at an atomistic resolution via the MSES scheme. The free energy surfaces on the latent space demonstrated the refinement of the generated data that had a single basin into the simulated data containing two closed and open basins, thus illustrating the usefulness of the MD simulation together with the molecular mechanics force field in recovering the correct structural ensemble.

Ribose-Binding Protein Mutants With Improved Interaction Towards the Non-natural Ligand 1,3-Cyclohexanediol

Bioreporters consist of genetically modified living organisms that respond to the presence of target chemical compounds by production of an easily measurable signal. The central element in a bioreporter is a sensory protein or aptamer, which, upon ligand binding, modifies expression of the reporter signal protein. A variety of naturally occurring or modified versions of sensory elements has been exploited, but it has proven to be challenging to generate elements that recognize non-natural ligands. Bacterial periplasmic binding proteins have been proposed as a general scaffold to design receptor proteins for non-natural ligands, but despite various efforts, with only limited success. Here, we show how combinations of randomized mutagenesis and reporter screening improved the performance of a set of mutants in the ribose binding protein (RbsB) of Escherichia coli, which had been designed based on computational simulations to bind the non-natural ligand 1,3-cyclohexanediol (13CHD). Randomized mutant libraries were constructed that used the initially designed mutants as scaffolds, which were cloned in an appropriate E. coli bioreporter system and screened for improved induction of the GFPmut2 reporter fluorescence in presence of 1,3-cyclohexanediol. Multiple rounds of library screening, sorting, renewed mutagenesis and screening resulted in 4.5-fold improvement of the response to 1,3-cyclohexanediol and a lower detection limit of 0.25 mM. All observed mutations except one were located outside the direct ligand-binding pocket, suggesting they were compensatory and helping protein folding or functional behavior other than interaction with the ligand. Our results thus demonstrate that combinations of ligand-binding-pocket redesign and randomized mutagenesis can indeed lead to the selection and recovery of periplasmic-binding protein mutants with non-natural compound recognition. However, current lack of understanding of the intermolecular movement and ligand-binding in periplasmic binding proteins such as RbsB are limiting the rational production of further and better sensory mutants.

Protein Loop Conformational Free Energy Changes via an Alchemical Path without Reaction Coordinates

We introduce a method called restrain-free energy perturbation-release 2.0 (R-FEP-R 2.0) to estimate conformational free energy changes of protein loops via an alchemical path. R-FEP-R 2.0 is a generalization of the method called restrain-free energy perturbation-release (R-FEP-R) that can only estimate conformational free energy changes of protein side chains but not loops. The reorganization of protein loops is a central feature of many biological processes. Unlike other advanced sampling algorithms such as umbrella sampling and metadynamics, R-FEP-R and R-FEP-R 2.0 do not require predetermined collective coordinates and transition pathways that connect the two endpoint conformational states. The R-FEP-R 2.0 method was applied to estimate the conformational free energy change of a β-turn flip in the protein ubiquitin. The result obtained by R-FEP-R 2.0 agrees with the benchmarks very well. We also comment on problems commonly encountered when applying umbrella sampling to calculate protein conformational free energy changes.

Unraveling the Coupling between Conformational Changes and Ligand Binding in Ribose Binding Protein Using Multiscale Molecular Dynamics and Free-Energy Calculations

Conformational changes of proteins upon ligand binding are usually explained in terms of several mechanisms including the induced fit, conformational selection, or their mixtures. Due to the slow time scales, conventional molecular dynamics (cMD) simulations based on the atomistic models cannot easily simulate the open-to-closed conformational transition in proteins. In our previous study, we have developed an enhanced sampling scheme (generalized replica exchange with solute tempering selected surface charged residues: gREST_SSCR) for multidomain proteins and applied it to ligand-mediated conformational changes in the G134R mutant of ribose-binding protein (RBPG134R) in solution. The free-energy landscape (FEL) of RBPG134R in the presence of a ribose at the binding site included the open and closed states and two intermediates, open-like and closed-like forms. Only the open and open-like forms existed in the FEL without a ribose. In the current study, the coupling between the conformational changes and ligand binding is further investigated using coarse-grained MD, multiple atomistic cMD, and free-energy calculations. The ribose is easily dissociated from the binding site of wild-type RBP and RBPG134R in the cMD simulations starting from the open and open-like forms. In contrast, it is stable at the binding site in the simulations from the closed and closed-like forms. The free-energy calculations provide the binding affinities of different structures, supporting the results of cMD simulations. Importantly, cMD simulations from the closed-like structures reveal transitions toward the closed one in the presence of a bound ribose. On the basis of the computational results, we propose a molecular mechanism in which conformational selection and induced fit happen in the first and second halves of the open-to-closed transition in RBP, respectively.

Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations

BACKGROUND

The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations.

OBJECTIVE

With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models.

METHODS

Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations.

RESULTS

The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation.

CONCLUSIONS

The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

Exploring Large Domain Motions in Proteins Using Atomistic Molecular Dynamics with Enhanced Conformational Sampling

Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains’ stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.

Building a macro-mixing dual-basin Gō model using the Multistate Bennett Acceptance Ratio

The dual-basin Gō-model is a structural-based coarsegrained model for simulating a conformational transition between two known structures of a protein. Two parameters are required to produce a dual-basin potential mixed using two single-basin potentials, although the determination of mixing parameters is usually not straightforward. Here, we have developed an efficient scheme to determine the mixing parameters using the Multistate Bennett Acceptance Ratio (MBAR) method after short simulations with a set of parameters. In the scheme, MBAR allows us to predict observables at various unsimulated conditions, which are useful to improve the mixing parameters in the next round of iterative simulations. The number of iterations that are necessary for obtaining the converged mixing parameters are significantly reduced in the scheme. We applied the scheme to two proteins, the glutamine binding protein and the ribose binding protein, for showing the effectiveness in the parameter determination. After obtaining the converged parameters, both proteins show frequent conformational transitions between open and closed states, providing the theoretical basis to investigate structure-dynamics-function relationships of the proteins.

Massive-Scale Binding Free Energy Simulations of HIV Integrase Complexes Using Asynchronous Replica Exchange Framework Implemented on the IBM WCG Distributed Network

To perform massive-scale replica exchange molecular dynamics (REMD) simulations for calculating binding free energies of protein-ligand complexes, we implemented the asynchronous replica exchange (AsyncRE) framework of the binding energy distribution analysis method (BEDAM) in implicit solvent on the IBM World Community Grid (WCG) and optimized the simulation parameters to reduce the overhead and improve the prediction power of the WCG AsyncRE simulations. We also performed the first massive-scale binding free energy calculations using the WCG distributed computing grid and 301 ligands from the SAMPL4 challenge for large-scale binding free energy predictions of HIV-1 integrase complexes. In total there are ∼10000 simulated complexes, ∼1 million replicas, and ∼2000 μs of aggregated MD simulations. Running AsyncRE MD simulations on the WCG requires accepting a trade-off between the number of replicas that can be run (breadth) and the number of full RE cycles that can be completed per replica (depth). As compared with synchronous Replica Exchange (SyncRE) running on tightly coupled clusters like XSEDE, on the WCG many more replicas can be launched simultaneously on heterogeneous distributed hardware, but each full RE cycle requires more overhead. We compared the WCG results with that from AutoDock and more advanced RE simulations including the use of flattening potentials to accelerate sampling of selected degrees of freedom of ligands and/or receptors related to slow dynamics due to high energy barriers. We propose a suitable strategy of RE simulations to refine high throughput docking results which can be matched to corresponding computing resources: from HPC clusters, to small or medium-size distributed campus grids, and finally to massive-scale computing networks including millions of CPUs like the resources available on the WCG.

Free Energy Profile of Domain Movement in Ligand-Free Citrate Synthase

Citrate synthase plays a fundamental role in the metabolic cycle of the cell. Its catalytic mechanism is complex involving the binding of two substrates that cause a domain movement. In this paper, we used classical molecular dynamics simulations and umbrella-sampling simulations to determine the potential of mean force along a reaction coordinate for the domain movement in ligand-free citrate synthase from pig ( Sus scrofa). The results show that, at 293 K, the closed-domain conformation has a ∼4 k_b T higher energy than the open-domain conformation. In a simple two-state model, this difference means that the enzyme spends 98% of the time in the open-domain conformation ready to receive the substrate, oxaloacetate, rather than the closed-domain conformation where the binding site would be inaccessible to the substrate. Given that experimental evidence indicates that the binding of oxaloacetate induces at least partial closure, this would imply an induced-fit mechanism which we argue is applicable to all enzymes with a functional domain movement for reasons of catalytic efficiency. A barrier of 4 k_b T gives an estimation of the mean first passage time in the range 1-10 μs.

Conformational Free Energy Changes via an Alchemical Path without Reaction Coordinates

We introduce a novel method called restrain-free energy perturbation-release (R-FEP-R) to estimate conformational free energy changes via an alchemical path, which for some conformational landscapes like those associated with cellular signaling proteins in the kinase family is more direct and readily converged than the corresponding free energy changes along the physical path. The R-FEP-R method was developed from the dual topology free energy perturbation method that is widely applied to estimate the binding free energy difference between two ligands. In R-FEP-R, the free energy change between two conformational basins is calculated by free energy perturbations that remove those atoms involved in the conformational change from their initial conformational basin while simultaneously growing them back according to the final conformational basin. Both the initial and final dual topology states are unphysical, but they are designed in a way such that the unphysical contributions to the initial and final partition functions cancel. Compared with other advanced sampling algorithms such as umbrella sampling and metadynamics, the R-FEP-R method does not require predetermined transition pathways or reaction coordinates that connect the two conformational states. As a first illustration, the R-FEP-R method was applied to calculate the free energy change between conformational basins for alanine dipeptide in solution and for a side chain in the binding pocket of T4 lysozyme. The results obtained by R-FEP-R agree with the benchmarks very well.

An integrated perspective on RNA aptamer ligand-recognition models: clearing muddy waters

Riboswitches are short RNA motifs that sensitively and selectively bind cognate ligands to modulate gene expression. Like protein receptor-ligand pairs, their binding dynamics are traditionally categorized as following one of two paradigmatic mechanisms: conformational selection and induced fit. In conformational selection, ligand binding stabilizes a particular state already present in the receptor's dynamic ensemble. In induced fit, ligand-receptor interactions enable the system to overcome the energetic barrier into a previously inaccessible state. In this article, we question whether a polarized division of RNA binding mechanisms truly meets the conceptual needs of the field. We will review the history behind this classification of RNA-ligand interactions, and the way induced fit in particular has been rehabilitated by single-molecule studies of RNA aptamers. We will highlight several recent results from single-molecule experimental studies of riboswitches that reveal gaps or even contradictions between common definitions of the two terms, and we will conclude by proposing a more robust framework that considers the range of RNA behaviors unveiled in recent years as a reality to be described, rather than an increasingly unwieldy set of exceptions to the traditional models.

Osmolyte-Like Stabilizing Effects of Low GdnHCl Concentrations on d-Glucose/d-Galactose-Binding Protein

The ability of d-glucose/d-galactose-binding protein (GGBP) to reversibly interact with its ligands, glucose and galactose, makes this protein an attractive candidate for sensing elements of glucose biosensors. This potential is largely responsible for attracting researchers to study the conformational properties of this protein. Previously, we showed that an increase in the fluorescence intensity of the fluorescent dye 6-bromoacetyl-2-dimetylaminonaphtalene (BADAN) is linked to the holo-form of the GGBP/H152C mutant in solutions containing sub-denaturing concentrations of guanidine hydrochloride (GdnHCl). It was hypothesized that low GdnHCl concentrations might lead to compaction of the protein, thereby facilitating ligand binding. In this work, we utilize BADAN fluorescence spectroscopy, intrinsic protein UV fluorescence spectroscopy, and isothermal titration calorimetry (ITC) to show that the sub-denaturing GdnHCl concentrations possess osmolyte-like stabilizing effects on the structural dynamics, conformational stability, and functional activity of GGBP/H152C and the wild type of this protein (wtGGBP). Our data are consistent with the model where low GdnHCl concentrations promote a shift in the dynamic distribution of the protein molecules toward a conformational ensemble enriched in molecules with a tighter structure and a more closed conformation. This promotes the increase in the configurational complementarity between the protein and glucose molecules that leads to the increase in glucose affinity in both GGBP/H152C and wtGGBP.

Quantifying Allosteric Communication via Both Concerted Structural Changes and Conformational Disorder with CARDS

Allosteric (i.e., long-range) communication within proteins is crucial for many biological processes, such as the activation of signaling cascades in response to specific stimuli. However, the physical basis for this communication remains unclear. Existing computational methods for identifying allostery focus on the role of concerted structural changes, but recent experimental work demonstrates that disorder is also an important factor. Here, we introduce the Correlation of All Rotameric and Dynamical States (CARDS) framework for quantifying correlations between both the structure and disorder of different regions of a protein. To quantify disorder, we draw inspiration from methods for quantifying "dynamic heterogeneity" from chemical physics to classify segments of a dihedral's time evolution as being in either ordered or disordered regimes. To demonstrate the utility of this approach, we apply CARDS to the Catabolite Activator Protein (CAP), a transcriptional activator that is regulated by Cyclic Adenosine MonoPhosphate (cAMP) binding. We find that CARDS captures allosteric communication between the two cAMP-Binding Domains (CBDs). Importantly, CARDS reveals that this coupling is dominated by disorder-mediated correlations, consistent with NMR experiments that establish allosteric coupling between the CBDs occurs without a concerted structural change. CARDS also recapitulates an enhanced role for disorder in the communication between the DNA-Binding Domains (DBDs) and CBDs in the S62F variant of CAP. Finally, we demonstrate that using CARDS to find communication hotspots identifies regions of CAP that are in allosteric communication without foreknowledge of their identities. Therefore, we expect CARDS to be of great utility for both understanding and predicting allostery.

Influence of Secondary-Structure Folding on the Mutually Exclusive Folding Process of GL5/I27 Protein: Evidence from Molecular Dynamics Simulations

Mutually exclusive folding proteins are a class of multidomain proteins in which the host domain remains folded while the guest domain is unfolded, and both domains achieve exchange of their folding status by a mutual exclusive folding (MEF) process. We carried out conventional and targeted molecular dynamics simulations for the mutually exclusive folding protein of GL5/I27 to address the MEF transition mechanisms. We constructed two starting models and two targeted models, i.e., the starting models GL5/I27-S and GL5/I27-ST in which the first model involves the host domain GL5 and the secondary-structure unfolded guest domain I27-S, while the second model involves the host domain GL5 and the secondary/tertiary-structure extending guest domain I27-ST, and the target models GL5-S/I27 and GL5-ST/I27 in which GL5-S and GL5-ST represent the secondary-structure unfolding and the secondary/tertiary-structure extending, respectively. We investigated four MEF transition processes from both starting models to both target models. Based on structural changes and the variations of the radius of gyration (R_g) and the fractions of native contacts (Q), the formation of the secondary structure of the I27-guest domain induces significant extending of the GL5-host domain; but the primary shrinking of the tertiary structure of the I27-guest domain causes insignificant extending of the GL5-host domain during the processes. The results indicate that only formation of the secondary structure in the I27-guest domain provides the main driving force for the mutually exclusive folding/unfolding between the I27-guest and GL5-host domains. A special structure as an intermediate with both host and guest domains being folded at the same time was found, which was suggested by the experiment. The analysis of hydrogen bonds and correlation motions supported the studied transition mechanism with the dynamical "tug-of-war" phenomenon.

Conformational analysis of short polar side-chain amino-acids through umbrella sampling and DFT calculations

Molecular and quantum mechanics calculations were carried out in a series of tripeptides (GXG, where X = D, N and C) as models of the unfolded states of proteins. The selected central amino acids, especially aspartic acid (D) and asparagine (N) are known to present significant average conformations in partially allowed areas of the Ramachandran plot, which have been suggested to be important in unfolded protein regions. In this report, we present the calculation of the propensity values through an umbrella sampling procedure in combination with the calculation of the NMR J-coupling constants obtained by a DFT model. The experimental NMR observations can be reasonably explained in terms of a conformational distribution where PP_II and β basins sum up propensities above 0.9. The conformational analysis of the side chain dihedral angle (χ₁), along with the computation of ³J(H^αH^β), revealed a preference for the g _- and g ₊ rotamers. These may be connected with the presence of intermolecular H-bonding and carbonyl-carbonyl interactions sampled in the PP_II and β basins. Taking into account all those results, it can be established that these residues show a similar behavior to other amino acids in short peptides regarding backbone φ,ψ dihedral angle distribution, in agreement with some experimental analysis of capped dipeptides.

Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.

Protein conformational changes are key to a wide range of cellular functions but remain difficult to access experimentally. Here the authors describe eBDIMS, a novel approach to predict intermediates observed in structural transition pathways from experimental ensembles.

Unraveling the Conformational Landscape of Ligand Binding to Glucose/Galactose-Binding Protein by Paramagnetic NMR and MD Simulations

Protein dynamics related to function can nowadays be structurally well characterized (i.e., instances obtained by high resolution structures), but they are still ill-defined energetically, and the energy landscapes are only accessible computationally. This is the case for glucose-galactose binding protein (GGBP), where the crystal structures of the apo and holo states provide structural information for the domain rearrangement upon ligand binding, while the time scale and the energetic determinants for such concerted dynamics have been so far elusive. Here, we use GGBP as a paradigm to define a functional conformational landscape, both structurally and energetically, by using an innovative combination of paramagnetic NMR experiments and MD simulations. Anisotropic NMR parameters induced by self-alignment of paramagnetic metal ions was used to characterize the ensemble of conformations adopted by the protein in solution while the rate of interconversion between conformations was elucidated by long molecular dynamics simulation on two states of GGBP, the closed-liganded (holo_cl) and open-unloaded (apo_op) states. Our results demonstrate that, in its apo state, the protein coexists between open-like (68%) and closed-like (32%) conformations, with an exchange rate around 25 ns. Despite such conformational heterogeneity, the presence of the ligand is the ultimate driving force to unbalance the equilibrium toward the holo_cl form, in a mechanism largely governed by a conformational selection mechanism.

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

Tracking individual membrane proteins and their biochemistry: The power of direct observation

The advent of single molecule fluorescence microscopy has allowed experimental molecular biophysics and biochemistry to transcend traditional ensemble measurements, where the behavior of individual proteins could not be precisely sampled. The recent explosion in popularity of new super-resolution and super-localization techniques coupled with technical advances in optical designs and fast highly sensitive cameras with single photon sensitivity and millisecond time resolution have made it possible to track key motions, reactions, and interactions of individual proteins with high temporal resolution and spatial resolution well beyond the diffraction limit. Within the purview of membrane proteins and ligand gated ion channels (LGICs), these outstanding advances in single molecule microscopy allow for the direct observation of discrete biochemical states and their fluctuation dynamics. Such observations are fundamentally important for understanding molecular-level mechanisms governing these systems. Examples reviewed here include the effects of allostery on the stoichiometry of ligand binding in the presence of fluorescent ligands; the observation of subdomain partitioning of membrane proteins due to microenvironment effects; and the use of single particle tracking experiments to elucidate characteristics of membrane protein diffusion and the direct measurement of thermodynamic properties, which govern the free energy landscape of protein dimerization. The review of such characteristic topics represents a snapshot of efforts to push the boundaries of fluorescence microscopy of membrane proteins to the absolute limit. This article is part of the Special Issue entitled 'Fluorescent Tools in Neuropharmacology'.

Structures and energies of the transition between two conformations of the alternate frame folding calbindin-D9k protein: a theoretical study

We carried out molecular dynamics simulations and energy calculations for the two states of the alternate frame folding (AFF) calbindin-D_9k protein and their conformational transition in Ca²⁺-free form to address their dynamical transition mechanism.

Protein conformational dynamics dictate the binding affinity for a ligand

Interactions between a protein and a ligand are essential to all biological processes. Binding and dissociation are the two fundamental steps of ligand-protein interactions, and determine the binding affinity. Intrinsic conformational dynamics of proteins have been suggested to play crucial roles in ligand binding and dissociation. Here, we demonstrate how protein dynamics dictate the binding and dissociation of a ligand through a single-molecule kinetic analysis for a series of maltose-binding protein mutants that have different intrinsic conformational dynamics and dissociation constants for maltose. Our results provide direct evidence that the ligand dissociation is determined by the intrinsic opening rate of the protein.

Coevolutionary signals across protein lineages help capture multiple protein conformations

A long-standing problem in molecular biology is the determination of a complete functional conformational landscape of proteins. This includes not only proteins' native structures, but also all their respective functional states, including functionally important intermediates. Here, we reveal a signature of functionally important states in several protein families, using direct coupling analysis, which detects residue pair coevolution of protein sequence composition. This signature is exploited in a protein structure-based model to uncover conformational diversity, including hidden functional configurations. We uncovered, with high resolution (mean ~1.9 Å rmsd for nonapo structures), different functional structural states for medium to large proteins (200-450 aa) belonging to several distinct families. The combination of direct coupling analysis and the structure-based model also predicts several intermediates or hidden states that are of functional importance. This enhanced sampling is broadly applicable and has direct implications in protein structure determination and the design of ligands or drugs to trap intermediate states.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method

Background

Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space.

Methods

We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers.

Results and conclusions

Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.

Computational gibberellin-binding channel discovery unraveling the unexpected perception mechanism of hormone signal by gibberellin receptor

Gibberellins (GAs) are phytohormones essential for many developmental processes in plants. In this work, fundamental mechanism of hormone perception by receptor GID1 has been studied by performing computational simulations, revealing a new GA-binding channel of GID1 and a novel hormone perception mechanism involving only one conformational state of GID1. The novel hormone perception mechanism demonstrated here is remarkably different from the previously proposed/speculated mechanism [Murase et al., Nature 2008, 456, 459] involving two conformational states ("OPEN" and "CLOSED") of GID1. According to the new perception mechanism, GA acts as a "conformational stabilizer," rather than the previously speculated "allosteric inducer," to induce the recognition of protein DELLA by GID1. The novel mechanistic insights obtained in this study provide a new starting point for further studies on the detailed molecular mechanisms of GID1 interacting with DELLA and various hormones and for mechanism-based rational design of novel, potent growth regulators that target crops and ornamental plants.

Analysis of conformational motions and residue fluctuations for Escherichia coli ribose-binding protein revealed with elastic network models

The ribose-binding protein (RBP) is a sugar-binding bacterial periplasmic protein whose function is associated with a large allosteric conformational change from an open to a closed conformation upon binding to ribose. The open (ligand-free) and closed (ligand-bound) forms of RBP have been found. Here we investigate the conformational motions and residue fluctuations of the RBP by analyzing the modes of motion with two coarse-grained elastic network models, the Gaussian Network Model (GNM) and Anisotropic Network Model (ANM). The calculated B-factors in both the calculated models are in good agreement with the experimentally determined B-factors in X-ray crystal structures. The slowest mode analysis by GNM shows that both forms have the same motion hinge axes around residues Ser103, Gln235, Asp264 and the two domains of both structures have similar fluctuation range. The superposition of the first three dominant modes of ANM, consisting of the rotating, bending and twisting motions of the two forms, accounts for large rearrangement of domains from the ligand-free (open) to ligand-bound (closed) conformation and thus constitutes a critical component of the RBP's functions. By analyzing cross-correlations between residue fluctuation and the difference-distance plot, it is revealed that the conformational change can be described as a rigid rotation of the two domains with respect to each other, whereas the internal structure of the two domains remains largely intact. The results directly indicate that the dominant dynamic characteristics of protein structures can be captured from their static native state using coarse-grained models.

Computational study of synthetic agonist ligands of ionotropic glutamate receptors

Neurological glutamate receptors are among the most important and intensely studied protein ligand binding systems in humans. They are crucial for the functioning of the central nervous system and involved in a variety of pathologies. Apart from the neurotransmitter glutamate, several artificial, agonistic and antagonistic ligands are known. Of particular interest here are novel photoswitchable agonists that would open the field of optogenetics to glutamate receptors. The receptor proteins are complex, membrane-bound multidomain oligomers that undergo large scale functional conformational changes, making detailed studies of their atomic structure challenging. Therefore, a thorough understanding of the microscopic details of ligand binding and receptor activation remains elusive in many cases. This topic has been successfully addressed by theoretical studies in the past and in this paper, we present extensive molecular dynamics simulation and free energy calculation results on the binding of AMPA and an AMPA derivative, which is the basis for designing light-sensitive ligands. We provide a two-step model for ligand binding domain activation and predict binding free energies for novel compounds in good agreement to experimental observations.

Protein conformational switches: from nature to design

Protein conformational switches alter their shape upon receiving an input signal, such as ligand binding, chemical modification, or change in environment. The apparent simplicity of this transformation--which can be carried out by a molecule as small as a thousand atoms or so--belies its critical importance to the life of the cell as well as its capacity for engineering by humans. In the realm of molecular switches, proteins are unique because they are capable of performing a variety of biological functions. Switchable proteins are therefore of high interest to the fields of biology, biotechnology, and medicine. These molecules are beginning to be exploited as the core machinery behind a new generation of biosensors, functionally regulated enzymes, and "smart" biomaterials that react to their surroundings. As inspirations for these designs, researchers continue to analyze existing examples of allosteric proteins. Recent years have also witnessed the development of new methodologies for introducing conformational change into proteins that previously had none. Herein we review examples of both natural and engineered protein switches in the context of four basic modes of conformational change: rigid-body domain movement, limited structural rearrangement, global fold switching, and folding-unfolding. Our purpose is to highlight examples that can potentially serve as platforms for the design of custom switches. Accordingly, we focus on inducible conformational changes that are substantial enough to produce a functional response (e.g., in a second protein to which it is fused), yet are relatively simple, structurally well-characterized, and amenable to protein engineering efforts.

Evidence for an allosteric mechanism of substrate release from membrane-transporter accessory binding proteins

Numerous membrane importers rely on accessory water-soluble proteins to capture their substrates. These substrate-binding proteins (SBP) have a strong affinity for their ligands; yet, substrate release onto the low-affinity membrane transporter must occur for uptake to proceed. It is generally accepted that release is facilitated by the association of SBP and transporter, upon which the SBP adopts a conformation similar to the unliganded state, whose affinity is sufficiently reduced. Despite the appeal of this mechanism, however, direct supporting evidence is lacking. Here, we use experimental and theoretical methods to demonstrate that an allosteric mechanism of enhanced substrate release is indeed plausible. First, we report the atomic-resolution structure of apo TeaA, the SBP of the Na(+)-coupled ectoine TRAP transporter TeaBC from Halomonas elongata DSM2581(T), and compare it with the substrate-bound structure previously reported. Conformational free-energy landscape calculations based upon molecular dynamics simulations are then used to dissect the mechanism that couples ectoine binding to structural change in TeaA. These insights allow us to design a triple mutation that biases TeaA toward apo-like conformations without directly perturbing the binding cleft, thus mimicking the influence of the membrane transporter. Calorimetric measurements demonstrate that the ectoine affinity of the conformationally biased triple mutant is 100-fold weaker than that of the wild type. By contrast, a control mutant predicted to be conformationally unbiased displays wild-type affinity. This work thus demonstrates that substrate release from SBPs onto their membrane transporters can be facilitated by the latter through a mechanism of allosteric modulation of the former.

Induced fit or conformational selection? The role of the semi-closed state in the maltose binding protein

A full characterization of the thermodynamic forces underlying ligand-associated conformational changes in proteins is essential for understanding and manipulating diverse biological processes, including transport, signaling, and enzymatic activity. Recent experiments on the maltose binding protein (MBP) have provided valuable data about the different conformational states implicated in the ligand recognition process; however, a complete picture of the accessible pathways and the associated changes in free energy remains elusive. Here we describe results from advanced accelerated molecular dynamics (aMD) simulations, coupled with adaptively biased force (ABF) and thermodynamic integration (TI) free energy methods. The combination of approaches allows us to track the ligand recognition process on the microsecond time scale and provides a detailed characterization of the protein’s dynamic and the relative energy of stable states. We find that an induced-fit (IF) mechanism is most likely and that a mechanism involving both a conformational selection (CS) step and an IF step is also possible. The complete recognition process is best viewed as a “Pac Man” type action where the ligand is initially localized to one domain and naturally occurring hinge-bending vibrations in the protein are able to assist the recognition process by increasing the chances of a favorable encounter with side chains on the other domain, leading to a population shift. This interpretation is consistent with experiments and provides new insight into the complex recognition mechanism. The methods employed here are able to describe IF and CS effects and provide formally rigorous means of computing free energy changes. As such, they are superior to conventional MD and flexible docking alone and hold great promise for future development and applications to drug discovery.

Tracing conformational changes in proteins

Background

Many proteins undergo extensive conformational changes as part of their functionality. Tracing these changes is important for understanding the way these proteins function. Traditional biophysics-based conformational search methods require a large number of calculations and are hard to apply to large-scale conformational motions.

Results

In this work we investigate the application of a robotics-inspired method, using backbone and limited side chain representation and a coarse grained energy function to trace large-scale conformational motions. We tested the algorithm on four well known medium to large proteins and we show that even with relatively little information we are able to trace low-energy conformational pathways efficiently. The conformational pathways produced by our methods can be further filtered and refined to produce more useful information on the way proteins function under physiological conditions.

Conclusions

The proposed method effectively captures large-scale conformational changes and produces pathways that are consistent with experimental data and other computational studies. The method represents an important first step towards a larger scale modeling of more complex biological systems.

Antigenic characteristics of rhinovirus chimeras designed in silico for enhanced presentation of HIV-1 gp41 epitopes [corrected]

The development of an effective AIDS vaccine remains the most promising long-term strategy to combat human immunodeficiency virus (HIV)/AIDS. Here, we report favorable antigenic characteristics of vaccine candidates isolated from a combinatorial library of human rhinoviruses displaying the ELDKWA epitope of the gp41 glycoprotein of HIV-1. The design principles of this library emerged from the application of molecular modeling calculations in conjunction with our knowledge of previously obtained ELDKWA-displaying chimeras, including knowledge of a chimera with one of the best 2F5-binding characteristics obtained to date. The molecular modeling calculations identified the energetic and structural factors affecting the ability of the epitope to assume conformations capable of fitting into the complementarity determining region of the ELDKWA-binding, broadly neutralizing human mAb 2F5. Individual viruses were isolated from the library following competitive immunoselection and were tested using ELISA and fluorescence quenching experiments. Dissociation constants obtained using both techniques revealed that some of the newly isolated chimeras bind 2F5 with greater affinity than previously identified chimeric rhinoviruses. Molecular dynamics simulations of two of these same chimeras confirmed that their HIV inserts were partially preorganized for binding, which is largely responsible for their corresponding gains in binding affinity. The study illustrates the utility of combining structure-based experiments with computational modeling approaches for improving the odds of selecting vaccine component designs with preferred antigenic characteristics. The results obtained also confirm the flexibility of HRV as a presentation vehicle for HIV epitopes and the potential of this platform for the development of vaccine components against AIDS.

Transient non-native hydrogen bonds promote activation of a signaling protein

Phosphorylation is a common mechanism for activating proteins within signaling pathways. Yet, the molecular transitions between the inactive and active conformational states are poorly understood. Here we quantitatively characterize the free-energy landscape of activation of a signaling protein, nitrogen regulatory protein C (NtrC), by connecting functional protein dynamics of phosphorylation-dependent activation to protein folding and show that only a rarely populated, pre-existing active conformation is energetically stabilized by phosphorylation. Using nuclear magnetic resonance (NMR) dynamics, we test an atomic scale pathway for the complex conformational transition, inferred from molecular dynamics simulations (Lei et al., 2009). The data show that the loss of native stabilizing contacts during activation is compensated by non-native transient atomic interactions during the transition. The results unravel atomistic details of native-state protein energy landscapes by expanding the knowledge about ground states to transition landscapes.

Collective dynamics of periplasmic glutamine binding protein upon domain closure

The glutamine binding protein is a vital component of the associated ATP binding cassette transport systems responsible for the uptake of glutamine into the cell. We have investigated the global movements of this protein by molecular dynamics simulations and principal component analysis (PCA). We confirm that the most dominant mode corresponds to the biological function of the protein, i.e., a hinge-type motion upon ligand binding. The closure itself was directly observed from two independent trajectories whereby PCA was used to elucidate the nature of this closing reaction. Two intermediary states are identified and described in detail. The ligand binding induces the structural change of the hinge regions from a discontinuous beta-sheet to a continuous one, which also enhances softness of the hinge and modifies the direction of hinge motion to enable closing. We also investigated the convergence behavior of PCA modes, which were found to converge rather quickly when the associated magnitudes of the eigenvalues are well separated.

Structural analysis of the choline-binding protein ChoX in a semi-closed and ligand-free conformation

The periplasmic ligand-binding protein ChoX is part of the ABC transport system ChoVWX that imports choline as a nutrient into the soil bacteriumSinorhizobium meliloti. We have recently reported the crystal structures of ChoX in complex with its ligands choline and acetylcholine and the structure of a fully closed but substrate-free state of ChoX. This latter structure revealed an architecture of the ligand-binding site that is superimposable to the closed, ligand-bound form of ChoX. We report here the crystal structure of ChoX in an unusual, ligand-free conformation that represents a semi-closed form of ChoX. The analysis revealed a subdomain movement in the N-lobe of ChoX. Comparison with the two well-characterized substrate binding proteins, MBP and HisJ, suggests the presence of a similar subdomain in these proteins.

Conformational landscape of the human immunodeficiency virus type 1 reverse transcriptase non-nucleoside inhibitor binding pocket: lessons for inhibitor design from a cluster analysis of many crystal structures

Clustering of 99 available X-ray crystal structures of HIV-1 reverse transcriptase (RT) at the flexible non-nucleoside inhibitor binding pocket (NNIBP) provides information about features of the conformational landscape for binding non-nucleoside inhibitors (NNRTIs), including effects of mutation and crystal forms. The ensemble of NNIBP conformations is separated into eight discrete clusters based primarily on the position of the functionally important primer grip, the displacement of which is believed to be one of the mechanisms of inhibition of RT. Two of these clusters are populated by structures in which the primer grip exhibits novel conformations that differ from the predominant cluster by over 4 A and are induced by the unique inhibitors capravirine and rilpivirine/TMC278. This work identifies a new conformation of the NNIBP that may be used to design NNRTIs. It can also be used to guide more complete exploration of the NNIBP free energy landscape using advanced sampling techniques.

The AGBNP2 Implicit Solvation Model

The AGBNP2 implicit solvent model, an evolution of the Analytical Generalized Born plus Non-Polar (AGBNP) model we have previously reported, is presented with the aim of modeling hydration effects beyond those described by conventional continuum dielectric representations. A new empirical hydration free energy component based on a procedure to locate and score hydration sites on the solute surface is introduced to model first solvation shell effects, such as hydrogen bonding, which are poorly described by continuum dielectric models. This new component is added to the Generalized Born and non-polar AGBNP terms. Also newly introduced is an analytical Solvent Excluded Volume (SEV) model which improves the solute volume description by reducing the effect of spurious high-dielectric interstitial spaces present in conventional van der Waals representations. The AGBNP2 model is parametrized and tested with respect to experimental hydration free energies of small molecules and the results of explicit solvent simulations. Modeling the granularity of water is one of the main design principles employed for the the first shell solvation function and the SEV model, by requiring that water locations have a minimum available volume based on the size of a water molecule. It is shown that the new volumetric model produces Born radii and surface areas in good agreement with accurate numerical evaluations of these quantities. The results of molecular dynamics simulations of a series of mini-proteins show that the new model produces conformational ensembles in substantially better agreement with reference explicit solvent ensembles than the original AGBNP model with respect to both structural and energetics measures.

Substrate induced population shifts and stochastic gating in the PBCV-1 mRNA capping enzyme

The 317 residue PBCV-1 mRNA capping enzyme catalyzes the second enzymatic reaction in the formation of an N-7-methyl-GMP cap on the 5'-end of the nascent mRNA. It is composed of two globular domains bound by a short flexible peptide linker, which have been shown to undergo opening and closing events. The small size and experimentally demonstrated domain mobility make the PBCV-1 capping enzyme an ideally suited model system to explore domain mobility in context of substrate binding. Here, we specifically address the following four questions: (1) How does substrate binding affect relative domain mobility: is the system better described by an induced fit or population shift mechanism? (2) What are the gross characteristics of a conformation capable of binding substrate? (3) Does "domain gating" of the active site affect the rate of substrate binding? (4) Does the magnitude of receptor conformational fluctuations confer substrate specificity by sterically occluding molecules of a particular size or geometry? We answer these questions using a combination of theory, Brownian dynamics, and molecular dynamics. Our results show that binding efficiency is a function of conformation but that isomerization between efficient and inefficient binding conformations does not impact the substrate association rate. Additionally, we show that conformational flexibility alone is insufficient to explain single stranded mRNA specificity. While our results are specific to the PBCV-1 mRNA capping enzyme, they provide a useful context within which the substrate binding behavior of similarly structured enzymes or proteins may be considered.

Computational approaches for the design of peptides with anti-breast cancer properties

Background: Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Methodology: Recently, a computational approach was used to successfully design peptides that are new lead compounds against breast cancer. We used replica exchange molecular dynamics to predict the structure and dynamics of active peptides, leading to the discovery of smaller bioactive peptides. Conclusions: These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used along with the experimental information that led to the successful completion of this research.

In silico vaccine design based on molecular simulations of rhinovirus chimeras presenting HIV-1 gp41 epitopes

A cluster of promising epitopes for the development of human immunodeficiency virus (HIV) vaccines is located in the membrane-proximal external region (MPER) of the gp41 subunit of the HIV envelope spike structure. The crystal structure of the peptide corresponding to the so-called ELDKWA epitope (HIV-1 HxB2 gp41 residues 662-668), in complex with the corresponding broadly neutralizing human monoclonal antibody 2F5, provides a target for structure-based vaccine design strategies aimed at finding macromolecular carriers that are able to present this MPER-derived epitope with optimal antigenic activity. To this end, a series of replica exchange molecular dynamics computer simulations was conducted to characterize the distributions of conformations of ELDKWA-based epitopes inserted into a rhinovirus carrier and to identify those with the highest fraction of conformations that are able to bind 2F5. The length, hydrophobic character, and precise site of insertion were found to be critical for achieving structural similarity to the target crystal structure. A construct with a high degree of complementarity to the corresponding determinant region of 2F5 was obtained. This construct was employed to build a high-resolution structural model of the complex between the 2F5 antibody and the chimeric human rhinovirus type 14:HIV-1 ELDKWA virus particle. Additional simulations, which were conducted to study the conformational propensities of the ELDKWA region in solution, confirm the hypothesis that the ELDKWA region of gp41 is highly flexible and capable of assuming helical conformations (as in the postfusion helical bundle structure) and beta-turn conformations (as in the complex with the 2F5 antibody). These results also suggest that the ELDKWA epitope can be involved in intramolecular--and likely intermolecular--hydrophobic interactions. This tendency offers an explanation for the observation that mutations decreasing the hydrophobic character of the MPER in many cases result in conformational changes that increase the affinity of this region for the 2F5 antibody.

Structural biology of pectin degradation by Enterobacteriaceae

SUMMARY

Pectin is a structural polysaccharide that is integral for the stability of plant cell walls. During soft rot infection, secreted virulence factors from pectinolytic bacteria such as Erwinia spp. degrade pectin, resulting in characteristic plant cell necrosis and tissue maceration. Catabolism of pectin and its breakdown products by pectinolytic bacteria occurs within distinct cellular environments. This process initiates outside the cell, continues within the periplasmic space, and culminates in the cytoplasm. Although pectin utilization is well understood at the genetic and biochemical levels, an inclusive structural description of pectinases and pectin binding proteins by both extracellular and periplasmic enzymes has been lacking, especially following the recent characterization of several periplasmic components and protein-oligogalacturonide complexes. Here we provide a comprehensive analysis of the protein folds and mechanisms of pectate lyases, polygalacturonases, and carbohydrate esterases and the binding specificities of two periplasmic pectic binding proteins from Enterobacteriaceae. This review provides a structural understanding of the molecular determinants of pectin utilization and the mechanisms driving catabolite selectivity and flow through the pathway.

Catalytically requisite conformational dynamics in the mRNA-capping enzyme probed by targeted molecular dynamics

The addition of a N7-methyl guanosine cap to the 5' end of nascent mRNA is carried out by the mRNA-capping enzyme, a two-domain protein that is a member of the nucleotidyltransferase superfamily. The mRNA-capping enzyme is composed of a catalytic nucleotidyltransferase domain and a noncatalytic oligonucleotide/oligosaccharide binding (OB) domain. Large-scale domain motion triggered by substrate binding mediates catalytically requisite conformational rearrangement of the GTP substrate prior to the chemical step. In this study, we employ targeted molecular dynamics (TMD) on the PBCV-1 capping enzyme to probe the global domain dynamics and internal dynamics of conserved residues during the conformational transformation from the open to the closed state. Analysis of the resulting trajectories along with structural and sequence homology to other members of the superfamily allows us to suggest a conserved mechanism of conformational rearrangements spanning all mRNA-capping enzymes and all ATP-dependent DNA ligases. Our results suggest that the OB domain moves quasi-statically toward the nucleotidyltransferase domain, pivoting about a short linker region. The approach of the OB domain brings a conserved RxDK sequence, an element of conserved motif VI, within proximity of the triphosphate of GTP, destabilizing the unreactive conformation and thereby allowing thermal fluctuations to partition the substrate toward the catalytically competent state.