Comparative molecular dynamics-Similar folds and similar motions?

Evolutionary conservation of protein dynamics: insights from all-atom molecular dynamics simulations of 'peptidase' domain of Spt16

Protein function is encoded in its sequence, manifested in its three-dimensional structure, and facilitated by its dynamics. Studies have suggested that protein structures with higher sequence similarity could have more similar patterns of dynamics. However, such studies of protein dynamics within and across protein families typically rely on coarse-grained models, or approximate metrics like crystallographic B-factors. This study uses µs scale molecular dynamics (MD) simulations to explore the conservation of dynamics among homologs of ∼50 kDa N-terminal module of Spt16 (Spt16N). Spt16N from Saccharomyces cerevisiae (Sc-Spt16N) and three of its homologs with 30-40% sequence identities were available in the PDB. To make our data-set more comprehensive, the crystal structure of an additional homolog (62% sequence identity with Sc-Spt16N) was solved at 1.7 Å resolution. Cumulative MD simulations of 6 µs were carried out on these Spt16N structures and on two additional protein structures with varying degrees of similarity to it. The simulations revealed that correlation in patterns of backbone fluctuations vary linearly with sequence identity. This trend could not be inferred using crystallographic B-factors. Further, normal mode analysis suggested a similar pattern of inter-domain (inter-lobe) motions not only among Spt16N homologs, but also in the M24 peptidase structure. On the other hand, MD simulation results highlighted conserved motions that were found unique for Spt16N protein, this along with electrostatics trends shed light on functional aspects of Spt16N.Communicated by Ramaswamy H. Sarma.

Role of cis-trans proline isomerization in the function of pathogenic enterobacterial Periplasmic Binding Proteins

Periplasmic Binding Proteins (PBPs) trap nutrients for their internalization into bacteria by ABC transporters. Ligand binding triggers PBP closure by bringing its two domains together like a Venus flytrap. The atomic determinants that control PBP opening and closure for nutrient capture and release are not known, although it is proposed that opening and ligand release occur while in contact with the ABC transporter for concurrent substrate translocation. In this paper we evaluated the effect of the isomerization of a conserved proline, located near the binding site, on the propensity of PBPs to open and close. ArgT/LAO from Salmonella typhimurium and HisJ from Escherichia coli were studied through molecular mechanics at two different temperatures: 300 and 323 K. Eight microseconds were simulated per protein to analyze protein opening and closure in the absence of the ABC transporter. We show that when the studied proline is in trans, closed empty LAO and HisJ can open. In contrast, with the proline in cis, opening transitions were much less frequent and characterized by smaller changes. The proline in trans also renders the open trap prone to close over a ligand. Our data suggest that the isomerization of this conserved proline modulates the PBP mechanism: the proline in trans allows the exploration of conformational space to produce trap opening and closure, while in cis it restricts PBP movement and could limit ligand release until in productive contact with the ABC transporter. This is the first time that a proline isomerization has been related to the control of a large conformational change like the PBP flytrap mechanism.

Selection on protein structure, interaction, and sequence

Characterizing the probabilities of observing amino acid substitutions at specific sites in a protein over evolutionary time is a major goal in the field of molecular evolution. While purely statistical approaches at different levels of complexity exist, approaches rooted in underlying biological processes are necessary to characterize both the context-dependence of sequence changes (epistasis) and to extrapolate to sequences not observed in biological databases. To develop such approaches, an understanding of the different selective forces that act on amino acid substitution is necessary. Here, an overview of selection on and corresponding modeling of folding stability, folding specificity, binding affinity and specificity for ligands, the evolution of new binding sites on protein surfaces, protein dynamics, intrinsic disorder, and protein aggregation as well as the interplay with protein expression level (concentration) and biased mutational processes are presented.

Comparison of the Internal Dynamics of Metalloproteases Provides New Insights on Their Function and Evolution

Metalloproteases have evolved in a vast number of biological systems, being one of the most diverse types of proteases and presenting a wide range of folds and catalytic metal ions. Given the increasing understanding of protein internal dynamics and its role in enzyme function, we are interested in assessing how the structural heterogeneity of metalloproteases translates into their dynamics. Therefore, the dynamical profile of the clan MA type protein thermolysin, derived from an Elastic Network Model of protein structure, was evaluated against those obtained from a set of experimental structures and molecular dynamics simulation trajectories. A close correspondence was obtained between modes derived from the coarse-grained model and the subspace of functionally-relevant motions observed experimentally, the later being shown to be encoded in the internal dynamics of the protein. This prompted the use of dynamics-based comparison methods that employ such coarse-grained models in a representative set of clan members, allowing for its quantitative description in terms of structural and dynamical variability. Although members show structural similarity, they nonetheless present distinct dynamical profiles, with no apparent correlation between structural and dynamical relatedness. However, previously unnoticed dynamical similarity was found between the relevant members Carboxypeptidase Pfu, Leishmanolysin, and Botulinum Neurotoxin Type A, despite sharing no structural similarity. Inspection of the respective alignments shows that dynamical similarity has a functional basis, namely the need for maintaining proper intermolecular interactions with the respective substrates. These results suggest that distinct selective pressure mechanisms act on metalloproteases at structural and dynamical levels through the course of their evolution. This work shows how new insights on metalloprotease function and evolution can be assessed with comparison schemes that incorporate information on protein dynamics. The integration of these newly developed tools, if applied to other protein families, can lead to more accurate and descriptive protein classification systems.

Conformational state distributions and catalytically relevant dynamics of a hinge-bending enzyme studied by single-molecule FRET and a coarse-grained simulation

Over the last few decades, a view has emerged showing that multidomain enzymes are biological machines evolved to harness stochastic kicks of solvent particles into highly directional functional motions. These intrinsic motions are structurally encoded, and Nature makes use of them to catalyze chemical reactions by means of ligand-induced conformational changes and states redistribution. Such mechanisms align reactive groups for efficient chemistry and stabilize conformers most proficient for catalysis. By combining single-molecule Förster resonance energy transfer measurements with normal mode analysis and coarse-grained mesoscopic simulations, we obtained results for a hinge-bending enzyme, namely phosphoglycerate kinase (PGK), which support and extend these ideas. From single-molecule Förster resonance energy transfer, we obtained insight into the distribution of conformational states and the dynamical properties of the domains. The simulations allowed for the characterization of interdomain motions of a compact state of PGK. The data show that PGK is intrinsically a highly dynamic system sampling a wealth of conformations on timescales ranging from nanoseconds to milliseconds and above. Functional motions encoded in the fold are performed by the PGK domains already in its ligand-free form, and substrate binding is not required to enable them. Compared to other multidomain proteins, these motions are rather fast and presumably not rate-limiting in the enzymatic reaction. Ligand binding slightly readjusts the orientation of the domains and feasibly locks the protein motions along a preferential direction. In addition, the functionally relevant compact state is stabilized by the substrates, and acts as a prestate to reach active conformations by means of Brownian motions.

Evolution of conformational dynamics determines the conversion of a promiscuous generalist into a specialist enzyme

β-Lactamases are produced by many modern bacteria as a mechanism of resistance toward β-lactam antibiotics, the most common antibiotics in use. β-Lactamases, however, are ancient enzymes that originated billions of years ago. Recently, proteins corresponding to 2- to 3-Gy-old Precambrian nodes in the evolution of Class A β-lactamases have been prepared and shown to be moderately efficient promiscuous catalysts, able to degrade a variety of antibiotics with catalytic efficiency levels similar to those of an average modern enzyme. Remarkably, there are few structural differences (in particular at the active-site regions) between the resurrected enzymes and a penicillin-specialist modern β-lactamase. Here, we propose that the ancestral promiscuity originates from conformational dynamics. We investigate the differences in conformational dynamics of the ancient and extant β-lactamases through MD simulations and quantify the contribution of each position to functionally related dynamics through Dynamic Flexibility Index. The modern TEM-1 lactamase shows a comparatively rigid active-site region, likely reflecting adaptation for efficient degradation of a specific substrate (penicillin), whereas enhanced deformability at the active-site neighborhood in the ancestral resurrected proteins likely accounts for the binding and subsequent degradation of antibiotic molecules of different size and shape. Clustering of the conformational dynamics on the basis of Principal Component Analysis is in agreement with the functional divergence, as the ancient β-lactamases cluster together, separated from their modern descendant. Finally, our analysis leads to testable predictions, as sites of potential relevance for the evolution of dynamics are identified and mutations at those sites are expected to alter substrate-specificity.

Structure-based simulations reveal concerted dynamics of GPCR activation

G protein-coupled receptors (GPCRs) are a vital class of proteins that transduce biological signals across the cell membrane. However, their allosteric activation mechanism is not fully understood; crystal structures of active and inactive receptors have been reported, but the functional pathway between these two states remains elusive. Here, we use structure-based (Gō-like) models to simulate activation of two GPCRs, rhodopsin and the β₂ adrenergic receptor (β₂AR). We used data-derived reaction coordinates that capture the activation mechanism for both proteins, showing that activation proceeds through quantitatively different paths in the two systems. Both reaction coordinates are determined from the dominant concerted motions in the simulations so the technique is broadly applicable. There were two surprising results. First, the main structural changes in the simulations were distributed throughout the transmembrane bundle, and not localized to the obvious areas of interest, such as the intracellular portion of Helix 6. Second, the activation (and deactivation) paths were distinctly nonmonotonic, populating states that were not simply interpolations between the inactive and active structures. These transitions also suggest a functional explanation for β₂AR's basal activity: it can proceed through a more broadly defined path during the observed transitions.

Conformational analysis of processivity clamps in solution demonstrates that tertiary structure does not correlate with protein dynamics

The relationship between protein sequence, structure, and dynamics has been elusive. Here, we report a comprehensive analysis using an in-solution experimental approach to study how the conservation of tertiary structure correlates with protein dynamics. Hydrogen exchange measurements of eight processivity clamp proteins from different species revealed that, despite highly similar three-dimensional structures, clamp proteins display a wide range of dynamic behavior. Differences were apparent both for structurally similar domains within proteins and for corresponding domains of different proteins. Several of the clamps contained regions that underwent local unfolding with different half-lives. We also observed a conserved pattern of alternating dynamics of the α helices lining the inner pore of the clamps as well as a correlation between dynamics and the number of salt bridges in these α helices. Our observations reveal that tertiary structure and dynamics are not directly correlated and that primary structure plays an important role in dynamics.

A mechanistic understanding of allosteric immune escape pathways in the HIV-1 envelope glycoprotein

The HIV-1 envelope (Env) spike, which consists of a compact, heterodimeric trimer of the glycoproteins gp120 and gp41, is the target of neutralizing antibodies. However, the high mutation rate of HIV-1 and plasticity of Env facilitates viral evasion from neutralizing antibodies through various mechanisms. Mutations that are distant from the antibody binding site can lead to escape, probably by changing the conformation or dynamics of Env; however, these changes are difficult to identify and define mechanistically. Here we describe a network analysis-based approach to identify potential allosteric immune evasion mechanisms using three known HIV-1 Env gp120 protein structures from two different clades, B and C. First, correlation and principal component analyses of molecular dynamics (MD) simulations identified a high degree of long-distance coupled motions that exist between functionally distant regions within the intrinsic dynamics of the gp120 core, supporting the presence of long-distance communication in the protein. Then, by integrating MD simulations with network theory, we identified the optimal and suboptimal communication pathways and modules within the gp120 core. The results unveil both strain-dependent and -independent characteristics of the communication pathways in gp120. We show that within the context of three structurally homologous gp120 cores, the optimal pathway for communication is sequence sensitive, i.e. a suboptimal pathway in one strain becomes the optimal pathway in another strain. Yet the identification of conserved elements within these communication pathways, termed inter-modular hotspots, could present a new opportunity for immunogen design, as this could be an additional mechanism that HIV-1 uses to shield vulnerable antibody targets in Env that induce neutralizing antibody breadth.

Functional annotation of the mesophilic-like character of mutants in a cold-adapted enzyme by self-organising map analysis of their molecular dynamics

Multiple comparison of the Molecular Dynamics (MD) trajectories of mutants in a cold-adapted α-amylase (AHA) could be used to elucidate functional features required to restore mesophilic-like activity. Unfortunately it is challenging to identify the different dynamic behaviors and correctly relate them to functional activity by routine analysis. We here employed a previously developed and robust two-stage approach that combines Self-Organising Maps (SOMs) and hierarchical clustering to compare conformational ensembles of proteins. Moreover, we designed a novel strategy to identify the specific mutations that more efficiently convert the dynamic signature of the psychrophilic enzyme (AHA) to that of the mesophilic counterpart (PPA). The SOM trained on AHA and its variants was used to classify a PPA MD ensemble and successfully highlighted the relationships between the flexibilities of the target enzyme and of the different mutants. Moreover the local features of the mutants that mostly influence their global flexibility in a mesophilic-like direction were detected. It turns out that mutations of the cold-adapted enzyme to hydrophobic and aromatic residues are the most effective in restoring the PPA dynamic features and could guide the design of more mesophilic-like mutants. In conclusion, our strategy can efficiently extract specific dynamic signatures related to function from multiple comparisons of MD conformational ensembles. Therefore, it can be a promising tool for protein engineering.

Comparing proteins by their internal dynamics: exploring structure-function relationships beyond static structural alignments

The growing interest for comparing protein internal dynamics owes much to the realisation that protein function can be accompanied or assisted by structural fluctuations and conformational changes. Analogously to the case of functional structural elements, those aspects of protein flexibility and dynamics that are functionally oriented should be subject to evolutionary conservation. Accordingly, dynamics-based protein comparisons or alignments could be used to detect protein relationships that are more elusive to sequence and structural alignments. Here we provide an account of the progress that has been made in recent years towards developing and applying general methods for comparing proteins in terms of their internal dynamics and advance the understanding of the structure-function relationship.

Measuring and comparing structural fluctuation patterns in large protein datasets

MOTIVATION

The function of a protein depends not only on its structure but also on its dynamics. This is at the basis of a large body of experimental and theoretical work on protein dynamics. Further insight into the dynamics-function relationship can be gained by studying the evolutionary divergence of protein motions. To investigate this, we need appropriate comparative dynamics methods. The most used dynamical similarity score is the correlation between the root mean square fluctuations (RMSF) of aligned residues. Despite its usefulness, RMSF is in general less evolutionarily conserved than the native structure. A fundamental issue is whether RMSF is not as conserved as structure because dynamics is less conserved or because RMSF is not the best property to use to study its conservation.

RESULTS

We performed a systematic assessment of several scores that quantify the (dis)similarity between protein fluctuation patterns. We show that the best scores perform as well as or better than structural dissimilarity, as assessed by their consistency with the SCOP classification. We conclude that to uncover the full extent of the evolutionary conservation of protein fluctuation patterns, it is important to measure the directions of fluctuations and their correlations between sites.

CONTACT

Nathalie.Reuter@mbi.uib.no

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Online.

Why are the low-energy protein normal modes evolutionarily conserved?

Proteins fluctuate, and such fluctuations are functionally important. As with any functionally relevant trait, it is interesting to study how fluctuations change during evolution. In contrast with sequence and structure, the study of the evolution of protein motions is much more recent. Yet, it has been shown that the overall fluctuation pattern is evolutionarily conserved. Moreover, the lowest-energy normal modes have been found to be the most conserved. The reasons behind such a differential conservation have not been explicitly studied. There are two limiting explanations. A “biological” explanation is that because such modes are functional, there is natural selection pressure against their variation. An alternative “physical” explanation is that the lowest-energy normal modes may be more conserved because they are just more robust with respect to random mutations. To investigate this issue, I studied a set of globin-like proteins using a perturbed elastic network model (ENM) of the effect of random mutations on normal modes. I show that the conservation predicted by the model is in excellent agreement with observations. These results support the physical explanation: the lowest normal modes are more conserved because they are more robust.

The interface of protein structure, protein biophysics, and molecular evolution

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.

Exploring protein dynamics space: the dynasome as the missing link between protein structure and function

Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics.

Changes in Lysozyme Flexibility upon Mutation Are Frequent, Large and Long-Ranged

We investigate changes in human c-type lysozyme flexibility upon mutation via a Distance Constraint Model, which gives a statistical mechanical treatment of network rigidity. Specifically, two dynamical metrics are tracked. Changes in flexibility index quantify differences within backbone flexibility, whereas changes in the cooperativity correlation quantify differences within pairwise mechanical couplings. Regardless of metric, the same general conclusions are drawn. That is, small structural perturbations introduced by single point mutations have a frequent and pronounced affect on lysozyme flexibility that can extend over long distances. Specifically, an appreciable change occurs in backbone flexibility for 48% of the residues, and a change in cooperativity occurs in 42% of residue pairs. The average distance from mutation to a site with a change in flexibility is 17–20 Å. Interestingly, the frequency and scale of the changes within single point mutant structures are generally larger than those observed in the hen egg white lysozyme (HEWL) ortholog, which shares 61% sequence identity with human lysozyme. For example, point mutations often lead to substantial flexibility increases within the β-subdomain, which is consistent with experimental results indicating that it is the nucleation site for amyloid formation. However, β-subdomain flexibility within the human and HEWL orthologs is more similar despite the lowered sequence identity. These results suggest compensating mutations in HEWL reestablish desired properties.

The functional importance of protein dynamics is universally accepted, making the study of dynamical similarities and differences among proteins of the same function an intriguing problem. While some metrics are likely to be conserved across family, differences are also very common. In previous works we have used a Distance Constraint Model to quantify flexibility differences across sets of orthologous proteins, which reproduce this diversity. In the same manner, this work investigates changes occurring upon individual point mutations. Somewhat surprisingly, the small structural perturbations caused by mutation lead to changes throughout the protein. These changes can be quite large, actually surpassing the scale for differences between ortholog pairs. Moreover, changes in flexibility frequently occur at sites far from the mutation site. These results underscore the sensitivity of protein dynamics in connection with allostery, and help explain why differences across protein families are so common.

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.

Conformational and functional analysis of molecular dynamics trajectories by self-organising maps

BACKGROUND

Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering.

RESULTS

The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions.

CONCLUSIONS

The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources.

A role for both conformational selection and induced fit in ligand binding by the LAO protein

Molecular recognition is determined by the structure and dynamics of both a protein and its ligand, but it is difficult to directly assess the role of each of these players. In this study, we use Markov State Models (MSMs) built from atomistic simulations to elucidate the mechanism by which the Lysine-, Arginine-, Ornithine-binding (LAO) protein binds to its ligand. We show that our model can predict the bound state, binding free energy, and association rate with reasonable accuracy and then use the model to dissect the binding mechanism. In the past, this binding event has often been assumed to occur via an induced fit mechanism because the protein's binding site is completely closed in the bound state, making it impossible for the ligand to enter the binding site after the protein has adopted the closed conformation. More complex mechanisms have also been hypothesized, but these have remained controversial. Here, we are able to directly observe roles for both the conformational selection and induced fit mechanisms in LAO binding. First, the LAO protein tends to form a partially closed encounter complex via conformational selection (that is, the apo protein can sample this state), though the induced fit mechanism can also play a role here. Then, interactions with the ligand can induce a transition to the bound state. Based on these results, we propose that MSMs built from atomistic simulations may be a powerful way of dissecting ligand-binding mechanisms and may eventually facilitate a deeper understanding of allostery as well as the prediction of new protein-ligand interactions, an important step in drug discovery.

Accessing a hidden conformation of the maltose binding protein using accelerated molecular dynamics

Periplasmic binding proteins (PBPs) are a large family of molecular transporters that play a key role in nutrient uptake and chemotaxis in Gram-negative bacteria. All PBPs have characteristic two-domain architecture with a central interdomain ligand-binding cleft. Upon binding to their respective ligands, PBPs undergo a large conformational change that effectively closes the binding cleft. This conformational change is traditionally viewed as a ligand induced-fit process; however, the intrinsic dynamics of the protein may also be crucial for ligand recognition. Recent NMR paramagnetic relaxation enhancement (PRE) experiments have shown that the maltose binding protein (MBP) - a prototypical member of the PBP superfamily - exists in a rapidly exchanging (ns to µs regime) mixture comprising an open state (approx 95%), and a minor partially closed state (approx 5%). Here we describe accelerated MD simulations that provide a detailed picture of the transition between the open and partially closed states, and confirm the existence of a dynamical equilibrium between these two states in apo MBP. We find that a flexible part of the protein called the balancing interface motif (residues 175-184) is displaced during the transformation. Continuum electrostatic calculations indicate that the repacking of non-polar residues near the hinge region plays an important role in driving the conformational change. Oscillations between open and partially closed states create variations in the shape and size of the binding site. The study provides a detailed description of the conformational space available to ligand-free MBP, and has implications for understanding ligand recognition and allostery in related proteins.

A comparative analysis of the role of water in the binding pockets of ionotropic glutamate receptors

The binding pockets within proteins often contain water molecules. The ligand-binding core of ionotropic glutamate receptors represents an example where the binding pocket has many crystallographically reported waters, but the precise role remains unclear. It is also unclear to what extent the dynamic properties of these waters are conserved across the different receptor subtypes. In order to shed some light on these aspects we have performed multiple molecular dynamics simulations of the ligand binding core of four glutamate bound iGluR structures (GluA2, GluK1, GluK2, and GluN2A) and one apo structure (GluA2). We find that the water positions are reproduced from the simulations, but they also reveal that all but one water molecule in the binding site can be rearranged or replaced with water molecules from the bulk that enter the binding site through transient water channels. This one exception is not reported in the apo crystal structure but within 15 ns of simulation, a water molecule enters the site from the bulk suggesting that it is a favoured position regardless of the state of the protein. Further calculations demonstrate that whilst it is not needed in order to be able to predict the correct binding pose, it does contribute a large favourable interaction energy. We also find that one conserved water has a much stronger interaction with the protein in GluA2, GluK1 and GluK2 compared to the GluN2A receptor. The position of this water molecule is such that it can influence the dynamics of the proposed switch in the GluA2 and GluK1/2 receptors.

Deciphering the deformation modes associated with function retention and specialization in members of the Ras superfamily

The evolutionary and physical deformability patterns of members of the Ras GTPase superfamily were investigated by Principal Component and Elastic Network-Normal Mode analyses. The study helped to decipher the dynamics information encrypted into the conserved core and to separate the trans-family intrinsic flexibility associated with a common function from the protein motions related to functional specialization of selected families or family members. The conserved core is dynamically divided into two lobes. The deformation modes, which allow the Ras GTPases to accomplish their switching function, are conserved along evolution and are localized in lobe 1 portions close to the nucleotide. These modes lead to functional specialization when associated with evolution-driven deformations of protein portions essentially located in lobe 2, distal from the nucleotide, and involved in peculiar interactions with membrane, guanine nucleotide exchange factors, or effectors. Overall, a complete picture of the functional and evolutionary dynamics of the Ras superfamily emerges.

ALADYN: a web server for aligning proteins by matching their large-scale motion

The ALADYN web server aligns pairs of protein structures by comparing their internal dynamics and detecting regions that sustain similar large-scale movements. The latter often accompany functional conformational changes in proteins and enzymes. The ALADYN dynamics-based alignment can therefore highlight functionally-oriented correspondences that could be more elusive to sequence- or structure-based comparisons. The ALADYN server takes the structure files of the two proteins as input. The optimal relative positioning of the molecules is found by maximizing the similarity of the pattern of structural fluctuations which are calculated via an elastic network model. The resulting alignment is presented via an interactive graphical Java applet and is accompanied by a number of quantitative indicators and downloadable data files. The ALADYN web server is freely accessible at the http://aladyn.escience-lab.org address.

Dynamics based alignment of proteins: an alternative approach to quantify dynamic similarity

Background

The dynamic motions of many proteins are central to their function. It therefore follows that the dynamic requirements of a protein are evolutionary constrained. In order to assess and quantify this, one needs to compare the dynamic motions of different proteins. Comparing the dynamics of distinct proteins may also provide insight into how protein motions are modified by variations in sequence and, consequently, by structure. The optimal way of comparing complex molecular motions is, however, far from trivial. The majority of comparative molecular dynamics studies performed to date relied upon prior sequence or structural alignment to define which residues were equivalent in 3-dimensional space.

Results

Here we discuss an alternative methodology for comparative molecular dynamics that does not require any prior alignment information. We show it is possible to align proteins based solely on their dynamics and that we can use these dynamics-based alignments to quantify the dynamic similarity of proteins. Our method was tested on 10 representative members of the PDZ domain family.

Conclusions

As a result of creating pair-wise dynamics-based alignments of PDZ domains, we have found evolutionarily conserved patterns in their backbone dynamics. The dynamic similarity of PDZ domains is highly correlated with their structural similarity as calculated with Dali. However, significant differences in their dynamics can be detected indicating that sequence has a more refined role to play in protein dynamics than just dictating the overall fold. We suggest that the method should be generally applicable.

Comparison of molecular dynamics and superfamily spaces of protein domain deformation

BACKGROUND

It is well known the strong relationship between protein structure and flexibility, on one hand, and biological protein function, on the other hand. Technically, protein flexibility exploration is an essential task in many applications, such as protein structure prediction and modeling. In this contribution we have compared two different approaches to explore the flexibility space of protein domains: i) molecular dynamics (MD-space), and ii) the study of the structural changes within superfamily (SF-space).

RESULTS

Our analysis indicates that the MD-space and the SF-space display a significant overlap, but are still different enough to be considered as complementary. The SF-space space is wider but less complex than the MD-space, irrespective of the number of members in the superfamily. Also, the SF-space does not sample all possibilities offered by the MD-space, but often introduces very large changes along just a few deformation modes, whose number tend to a plateau as the number of related folds in the superfamily increases.

CONCLUSION

Theoretically, we obtained two conclusions. First, that function restricts the access to some flexibility patterns to evolution, as we observe that when a superfamily member changes to become another, the path does not completely overlap with the physical deformability. Second, that conformational changes from variation in a superfamily are larger and much simpler than those allowed by physical deformability. Methodologically, the conclusion is that both spaces studied are complementary, and have different size and complexity. We expect this fact to have application in fields as 3D-EM/X-ray hybrid models or ab initio protein folding.

Molecular dynamics simulations of ligand-induced backbone conformational changes in the binding site of the periplasmic lysine-, arginine-, ornithine-binding protein

The periplasmic lysine-, arginine-, ornithine-binding protein (LAOBP) traps its ligands by a large hinge bending movement between two globular domains. The overall geometry of the binding site remains largely unchanged between the open (unliganded) and closed (liganded) forms, with only a small number of residues exhibiting limited movement of their side chains. However, in the case of the ornithine-bound structure, the backbone peptide bond between Asp11 and Thr12 undergoes a large rotation. Molecular dynamics simulations have been used to investigate the origin and mechanism of this backbone movement. Simulations allowing flexibility of a limited region and of the whole binding site, with and without bound ligands, suggest that this conformational change is induced by the binding of ornithine, leading to the stabilisation of an energetically favourable alternative conformation.

Different regions of Mlc and NagC, homologous transcriptional repressors controlling expression of the glucose and N-acetylglucosamine phosphotransferase systems in Escherichia coli, are required for inducer signal recognition

Mlc and NagC are two homologous transcription factors which bind to similar DNA targets but for which the inducing signals and mechanisms of activation are very different. Displacing Mlc from its DNA binding sites necessitates its sequestration to the inner membrane via an interaction with PtsG (EIICB(Glc)), while NagC is displaced from its DNA targets by interacting with GlcNAc6P. We have isolated mutations in both proteins which prevent the inactivation of the repressors by growth on glucose or GlcNAc. These mutations are located in different and specific regions of each protein. For Mlc changes at the C-terminal make it a constitutive repressor and also prevent it from binding to EIIB(Glc). Mutations in NagC, at positions which form a structural motif resembling a glucose binding site in Mlc, produce permanently repressing forms of NagC, suggesting that this motif forms a GlcNAc6P binding site in NagC. The pattern of repression by chimeric proteins of NagC and Mlc confirms the importance of the C-terminal region of Mlc for both repression and inducer binding and demonstrate that the helix-turn-helix DNA-binding motif is not sufficient to determine the specificity of interaction of the repressor with DNA.

Characterization of protein conformational states by normal-mode frequencies

Conformational change in polymers including proteins is central to many molecular processes. Defining conformational states, however, remains a difficult and increasingly common problem, with many existing methods based on arbitrary or potentially unrepresentative measures. Furthermore, the expanding length of molecular dynamics simulations and direct observation of transitions between different energy basins suggest that this issue will only become evermore important. Methods commonly used to characterize conformational states include principal component analysis, root-mean-square deviation-based clustering, and geometric measurements such as hinge angles and distances. Here we present a method where the eigenvector frequencies derived from a Gaussian network model (Bahar, I.; Atilgan, A. R.; Erman, B. Folding Des. 1997, 2, 173-181) of a trajectory of structures from a molecular dynamics simulation are used to describe the state of the protein at each time point. We apply the method to three proteins that share the same fold as the type II periplasmic binding proteins: The lysine-arginine-ornithine-binding protein, the glutamine-binding protein, and the ligand-binding domain from the NR1 N-methyl-D-aspartate receptor. We find that the method can distinguish different states in good agreement with a variety of previous analyses and additionally provides information on the dynamic properties of that system at a given time point.

Three hydrolases and a transferase: comparative analysis of active-site dynamics via the BioSimGrid database

Comparative molecular dynamics (MD) simulations enable us to explore the conformational dynamics of the active sites of distantly related enzymes. We have used the BioSimGrid (http://www.biosimgrid.org) database to facilitate such a comparison. Simulations of four enzymes were analyzed. These included three hydrolases and a transferase, namely acetylcholinesterase, outer-membrane phospholipase A, outer-membrane protease T, and PagP (an outer-membrane enzyme which transfers a palmitate chain from a phospholipid to lipid A). A set of 17 simulations were analyzed corresponding to a total of approximately 0.1 micros simulation time. A simple metric for active-site integrity was used to demonstrate the existence of clusters of dynamic conformational behaviour of the active sites. Small (i.e. within a cluster) fluctuations appear to be related to the function of an enzymatically active site. Larger fluctuations (i.e. between clusters) correlate with transitions between catalytically active and inactive states. Overall, these results demonstrate the potential of a comparative MD approach to analysis of enzyme function. This approach could be extended to a wider range of enzymes using current high throughput MD simulation and database methods.

Convergent Dynamics in the Protease Enzymatic Superfamily

Proteases regulate various aspects of the life cycle in all organisms by cleaving specific peptide bonds. Their action is so central for biochemical processes that at least 2% of any known genome encodes for proteolytic enzymes. Here we show that selected proteases pairs, despite differences in oligomeric state, catalytic residues, and fold, share a common structural organization of functionally relevant regions which are further shown to undergo similar concerted movements. The structural and dynamical similarities found pervasively across evolutionarily distant clans point to common mechanisms for peptide hydrolysis.

Molecular dynamics simulations of the ligand-binding domain of an N-methyl-D-aspartate receptor

The mechanism of partial agonism at N-methyl-D-aspartate receptors is an unresolved issue, especially with respect to the role of protein dynamics. We have performed multiple molecular dynamics simulations (7 x 20 ns) to examine the behavior of the ligand-binding core of the NR1 subunit with a series of ligands. Our results show that water plays an important role in stabilizing different conformations of the core and how a closed cleft conformation of the protein might be stabilized in the absence of ligands. In the case of ligand-bound simulations with both full and partial agonists, we observed that ligands within the binding cleft may undergo distinct conformational changes, without grossly influencing the degree of cleft closure within the ligand-binding domain. In agreement with recently published crystallographic data, we also observe similar changes in backbone torsions corresponding to the hinge region between the two lobes for the partial agonist, D-cycloserine. This observation rationalizes the classification of D-cycloserine as a partial agonist and should provide a basis with which to predict partial agonism in this class of receptor by analyzing the behavior of these torsions with other potential ligands.

Binding Site Flexibility: Molecular Simulation of Partial and Full Agonists within a Glutamate Receptor

Ionotropic glutamate receptors mediate fast synaptic transmission in the mammalian central nervous system and play an important role in many different functions, including memory and learning. They have also been implicated in a variety of neuropathologies and as such have generated widespread interest in their structure and function. Molecular Dynamics simulations (5 x 20 ns) of the ligand-binding core of the GluR2 glutamate receptor were performed. Through simulations of both wild type and the L650T mutant, we show that the degree of protein flexibility can be correlated with the extent to which the binding cleft is open. In agreement with recent experiments, the simulations of kainate with the wild-type construct show a slight increase in beta-sheet content that we are able to localize to two specific regions. During one simulation, the protein made a transition from an open-cleft conformation to a closed-cleft conformation. This closed cleft conformation closely resembles the closed-cleft crystal structure, thus indicating a potential pathway for conformational change associated with receptor activation. Analysis of the binding pocket suggests that partial agonists possess a greater degree of flexibility within the pocket that may help to explain why they are less efficient at opening the channel than full agonists. Examination of water molecules surrounding the ligands reveals that mobility in distinct subsites can be a discriminator between full and partial agonism and will be an important consideration in the design of drugs against these receptors.