Convergent Dynamics in the Protease Enzymatic Superfamily

Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations

The initial phases of drug discovery - in silico drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of ∼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.

Internal Normal Mode Analysis Applied to RNA Flexibility and Conformational Changes

We investigated the capability of internal normal modes to reproduce RNA flexibility and predict observed RNA conformational changes and, notably, those induced by the formation of RNA-protein and RNA-ligand complexes. Here, we extended our iNMA approach developed for proteins to study RNA molecules using a simplified representation of the RNA structure and its potential energy. Three data sets were also created to investigate different aspects. Despite all the approximations, our study shows that iNMA is a suitable method to take into account RNA flexibility and describe its conformational changes opening the route to its applicability in any integrative approach where these properties are crucial.

Modulation of global stability, ligand binding and catalytic properties of trypsin by anions

Specific salts effect is well-known on stability and solubility of proteins, however, relatively limited knowledge is known regarding the effect on catalytic properties of enzymes. Here, we examined the effect of four sodium anions on thermal stability and catalytic properties of trypsin and binding of the fluorescent probe, p-aminobenzamidine (PAB), to the enzyme. We show that the specific anions effect on trypsin properties agrees with the localization of the anions in the Hofmeister series. Thermal stability of trypsin, T_m, the affinity of the fluorescent probe to the binding site, K_d, and the rate constant, k_cat, of trypsin-catalyzed hydrolysis of the substrate N-benzoyl-L-arginine ethyl ester (BAEE) increase with increasing kosmotropic character of anions in the order: perchlorate<bromide<chloride<sulfate, while the value of Michaelis constant, K_M, decreases. Correlations between the values of T_m, K_d for PAB, k_cat, and K_M for BAEE in the presence of 1 M studied salts suggest interrelation among these parameters of the enzyme. Global stabilization as well as increased rigidity of trypsin is accompanied by strengthening of interaction with fluorescent probe PAB and in accordance with decreasing values of K_M for the substrate BAEE. Strong correlations between parameters characterizing the trypsin properties with the charge densities of anions clearly indicate direct electrostatic interaction as a basis of the specific anion effect on the conformational and functional properties of the enzyme.

Ligand-protein interactions in lysozyme investigated through a dual-resolution model

A fully atomistic (AT) modeling of biological macromolecules at relevant length- and time-scales is often cumbersome or not even desirable, both in terms of computational effort required and a posteriori analysis. This difficulty can be overcome with the use of multiresolution models, in which different regions of the same system are concurrently described at different levels of detail. In enzymes, computationally expensive AT detail is crucial in the modeling of the active site in order to capture, for example, the chemically subtle process of ligand binding. In contrast, important yet more collective properties of the remainder of the protein can be reproduced with a coarser description. In the present work, we demonstrate the effectiveness of this approach through the calculation of the binding free energy of hen egg white lysozyme with the inhibitor di-N-acetylchitotriose. Particular attention is payed to the impact of the mapping, that is, the selection of AT and coarse-grained residues, on the binding free energy. It is shown that, in spite of small variations of the binding free energy with respect to the active site resolution, the separate contributions coming from different energetic terms (such as electrostatic and van der Waals interactions) manifest a stronger dependence on the mapping, thus pointing to the existence of an optimal level of intermediate resolution.

Dynamics-function relationship in the catalytic domains of N-terminal acetyltransferases

N-terminal acetyltransferases (NATs) belong to the superfamily of acetyltransferases. They are enzymes catalysing the transfer of an acetyl group from acetyl coenzyme A to the N-terminus of polypeptide chains. N-terminal acetylation is one of the most common protein modifications. To date, not much is known on the molecular basis for the exclusive substrate specificity of NATs. All NATs share a common fold called GNAT. A characteristic of NATs is the β6β7 hairpin loop covering the active site and forming with the α1α2 loop a narrow tunnel surrounding the catalytic site in which cofactor and polypeptide meet and exchange an acetyl group. We investigated the dynamics-function relationships of all available structures of NATs covering the three domains of Life. Using an elastic network model and normal mode analysis, we found a common dynamics pattern conserved through the GNAT fold; a rigid V-shaped groove formed by the β4 and β5 strands and splitting the fold in two dynamical subdomains. Loops α1α2, β3β4 and β6β7 all show clear displacements in the low frequency normal modes. We characterized the mobility of the loops and show that even limited conformational changes of the loops along the low-frequency modes are able to significantly change the size and shape of the ligand binding sites. Based on the fact that these movements are present in most low-frequency modes, and common to all NATs, we suggest that the α1α2 and β6β7 loops may regulate ligand uptake and the release of the acetylated polypeptide.

Shared Signature Dynamics Tempered by Local Fluctuations Enables Fold Adaptability and Specificity

Recent studies have drawn attention to the evolution of protein dynamics, in addition to sequence and structure, based on the premise structure-encodes-dynamics-encodes-function. Of interest is to understand how functional differentiation is accomplished while maintaining the fold, or how intrinsic dynamics plays out in the evolution of structural variations and functional specificity. We performed a systematic computational analysis of 26,899 proteins belonging to 116 CATH superfamilies. Characterizing cooperative mechanisms and convergent/divergent features that underlie the shared/differentiated dynamics of family members required a methodology that lends itself to efficient analyses of large ensembles of proteins. We therefore introduced, SignDy, an integrated pipeline for evaluating the signature dynamics of families based on elastic network models. Our analysis confirmed that family members share conserved, highly cooperative (global) modes of motion. Importantly, our analysis discloses a subset of motions that sharply distinguishes subfamilies, which lie in a low-to-intermediate frequency regime of the mode spectrum. This regime has maximal impact on functional differentiation of families into subfamilies, while being evolutionarily conserved among subfamily members. Notably, the high-frequency end of the spectrum also reveals evolutionary conserved features across and within subfamilies; but in sharp contrast to global motions, high-frequency modes are minimally collective. Modulation of robust/conserved global dynamics by low-to-intermediate frequency fluctuations thus emerges as a versatile mechanism ensuring the adaptability of selected folds and the specificity of their subfamilies. SignDy further allows for dynamics-based categorization as a new layer of information relevant to distinctive mechanisms of action of subfamilies, beyond sequence or structural classifications.

Optimal Coarse-Grained Site Selection in Elastic Network Models of Biomolecules

Elastic network models, simple structure-based representations of biomolecules where atoms interact via short-range harmonic potentials, provide great insight into a molecule's internal dynamics and mechanical properties at extremely low computational cost. Their efficiency and effectiveness have made them a pivotal instrument in the computer-aided study of proteins and, since a few years, also of nucleic acids. In general, the coarse-grained sites, i.e. those effective force centers onto which the all-atom structure is mapped, are constructed based on intuitive rules: a typical choice for proteins is to retain only the C _α atoms of each amino acid. However, a mapping strategy relying only on the atom type and not the local properties of its embedding can be suboptimal compared to a more careful selection. Here, we present a strategy in which the subset of atoms, each of which is mapped onto a unique coarse-grained site of the model, is selected in a stochastic search aimed at optimizing a cost function. The latter is taken to be a simple measure of the consistency between the harmonic approximation of an elastic network model and the harmonic model obtained through exact integration of the discarded degrees of freedom. The method is applied to two representatives of structurally very different types of biomolecules: the protein adenylate kinase and the RNA molecule adenine riboswitch. Our analysis quantifies the substantial impact that an algorithm-driven selection of coarse-grained sites can have on a model's properties.

Patterns of coevolving amino acids unveil structural and dynamical domains

Patterns of interacting amino acids are so preserved within protein families that the sole analysis of evolutionary comutations can identify pairs of contacting residues. It is also known that evolution conserves functional dynamics, i.e., the concerted motion or displacement of large protein regions or domains. Is it, therefore, possible to use a pure sequence-based analysis to identify these dynamical domains? To address this question, we introduce here a general coevolutionary coupling analysis strategy and apply it to a curated sequence database of hundreds of protein families. For most families, the sequence-based method partitions amino acids into a few clusters. When viewed in the context of the native structure, these clusters have the signature characteristics of viable protein domains: They are spatially separated but individually compact. They have a direct functional bearing too, as shown for various reference cases. We conclude that even large-scale structural and functionally related properties can be recovered from inference methods applied to evolutionary-related sequences. The method introduced here is available as a software package and web server (spectrus.sissa.it/spectrus-evo_webserver).

Plant defence induced by PGPR against Spodoptera litura in tomato (Solanum lycopersicum L.)

The research conducted including its rationale: Spodoptera litura is the major pest of tomato causing significant reduction in tomato yield. Application of Plant growth promoting rhizobacteria(PGPR) prevent use of chemical fertilizer and synthetic pesticides through enhancement of plant growth and yield and induction of systemic resistance. Present investigation is an attempt to evaluate the role of PGPR, Pseudomonas putida and Rothia sp. on the physiology and yield of tomato fruit infested with the S. litura. Central methods applied: The surface sterilized seeds of tomato were inoculated with 48 h culture of P. putida and Rothia sp. At 6-7 branching stage of the plant, the larvae of S. litura at 2nd in star was used to infect the tomato plant leaves.

KEY RESULTS

The S. litura infestation decreased dry weight of shoots and roots by 46% and 22%, and significant reduction was recorded in tomato fruit yield. The P. putida and Rothia sp. inoculations alleviated the adverse effects of insect infestation and resulted in 60% increase in plant biomass and 40% increase in yield over infested plants. Main conclusions including key points of discussion: PGPR: Defense appears to be mediated via increase in proline production, enhanced activities of antioxidant enzymes, stimulation in the activities of protease and polyphenol oxidases, increased contents of phenolics, protein and chlorophyll. The formulation of biopesticide involving PGPR comprise an environment friendly and sustainable approach to overcome insect infestation.

Similarity in Shape Dictates Signature Intrinsic Dynamics Despite No Functional Conservation in TIM Barrel Enzymes

The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 β-strand-α-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the β-barrel core is highly rigid, while the α-helices that flank the β-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the α-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design.

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.

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.

Comparing the intrinsic dynamics of multiple protein structures using elastic network models

BACKGROUND

Elastic network models (ENMs) are based on the simple idea that a protein can be described as a set of particles connected by springs, which can then be used to describe its intrinsic flexibility using, for example, normal mode analysis. Since the introduction of the first ENM by Monique Tirion in 1996, several variants using coarser protein models have been proposed and their reliability for the description of protein intrinsic dynamics has been widely demonstrated. Lately an increasing number of studies have focused on the meaning of slow dynamics for protein function and its potential conservation through evolution. This leads naturally to comparisons of the intrinsic dynamics of multiple protein structures with varying levels of similarity.

SCOPE OF REVIEW

We describe computational strategies for calculating and comparing intrinsic dynamics of multiple proteins using elastic network models, as well as a selection of examples from the recent literature.

MAJOR CONCLUSIONS

The increasing interest for comparing dynamics across protein structures with various levels of similarity, has led to the establishment and validation of reliable computational strategies using ENMs. Comparing dynamics has been shown to be a viable way for gaining greater understanding for the mechanisms employed by proteins for their function. Choices of ENM parameters, structure alignment or similarity measures will likely influence the interpretation of the comparative analysis of protein motion.

GENERAL SIGNIFICANCE

Understanding the relation between protein function and dynamics is relevant to the fundamental understanding of protein structure-dynamics-function relationship. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Evaluation of Protein Elastic Network Models Based on an Analysis of Collective Motions

Elastic network models (ENMs) are valuable tools for investigating collective motions of proteins, and a rich variety of simple models have been proposed over the past decade. A good representation of the collective motions requires a good approximation of the covariances between the fluctuations of the individual atoms. Nevertheless, most studies have validated such models only by the magnitudes of the single-atom fluctuations they predict. In the present study, we have quantified the agreement between the covariance structure predicted by molecular dynamics (MD) simulations and those predicted by a representative selection of proposed coarse-grained ENMs. We then contrast this approach with the comparison to MD-predicted atomic fluctuations and comparison to crystallographic B-factors. While all the ENMs yield approximations to the MD-predicted covariance structure, we report large and consistent differences between proposed models. We also find that the ability of the ENMs to predict atomic fluctuations is correlated with their ability to capture the covariance structure. In contrast, we find that the models that agree best with B-factors model collective motions less reliably and recommend against using B-factors as a benchmark.

Specificity of a protein-protein interface: local dynamics direct substrate recognition of effector caspases

Proteases are prototypes of multispecific protein–protein interfaces. Proteases recognize and cleave protein and peptide substrates at a well-defined position in a substrate binding groove and a plethora of experimental techniques provide insights into their substrate recognition. We investigate the caspase family of cysteine proteases playing a key role in programmed cell death and inflammation, turning caspases into interesting drug targets. Specific ligand binding to one particular caspase is difficult to achieve, as substrate specificities of caspase isoforms are highly similar. In an effort to rationalize substrate specificity of two closely related caspases, we investigate the substrate promiscuity of the effector Caspases 3 and 7 by data mining (cleavage entropy) and by molecular dynamics simulations. We find a strong correlation between binding site rigidity and substrate readout for individual caspase subpockets explaining more stringent substrate readout of Caspase 7 via its narrower conformational space. Caspase 3 subpockets S3 and S4 show elevated local flexibility explaining the more unspecific substrate readout of that isoform in comparison to Caspase 7. We show by in silico exchange mutations in the S3 pocket of the proteases that a proline residue in Caspase 7 contributes to the narrowed conformational space of the binding site. These findings explain the substrate specificities of caspases via a mechanism of conformational selection and highlight the crucial importance of binding site local dynamics in substrate recognition of proteases. Proteins 2014; 82:546–555.

Conservation of flexible residue clusters among structural and functional enzyme homologues

Conformational flexibility between structural ensembles is an essential component of enzyme function. Although the broad dynamical landscape of proteins is known to promote a number of functional events on multiple time scales, it is yet unknown whether structural and functional enzyme homologues rely on the same concerted residue motions to perform their catalytic function. It is hypothesized that networks of contiguous and flexible residue motions occurring on the biologically relevant millisecond time scale evolved to promote and/or preserve optimal enzyme catalysis. In this study, we use a combination of NMR relaxation dispersion, model-free analysis, and ligand titration experiments to successfully capture and compare the role of conformational flexibility between two structural homologues of the pancreatic ribonuclease family: RNase A and eosinophil cationic protein (or RNase 3). In addition to conserving the same catalytic residues and structural fold, both homologues show similar yet functionally distinct clusters of millisecond dynamics, suggesting that conformational flexibility can be conserved among analogous protein folds displaying low sequence identity. Our work shows that the reduced conformational flexibility of eosinophil cationic protein can be dynamically and functionally reproduced in the RNase A scaffold upon creation of a chimeric hybrid between the two proteins. These results support the hypothesis that conformational flexibility is partly required for catalytic function in homologous enzyme folds, further highlighting the importance of dynamic residue sectors in the structural organization of proteins.

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.

Corresponding functional dynamics across the Hsp90 Chaperone family: insights from a multiscale analysis of MD simulations

Understanding how local protein modifications, such as binding small-molecule ligands, can trigger and regulate large-scale motions of large protein domains is a major open issue in molecular biology. We address various aspects of this problem by analyzing and comparing atomistic simulations of Hsp90 family representatives for which crystal structures of the full length protein are available: mammalian Grp94, yeast Hsp90 and E.coli HtpG. These chaperones are studied in complex with the natural ligands ATP, ADP and in the Apo state. Common key aspects of their functional dynamics are elucidated with a novel multi-scale comparison of their internal dynamics. Starting from the atomic resolution investigation of internal fluctuations and geometric strain patterns, a novel analysis of domain dynamics is developed. The results reveal that the ligand-dependent structural modulations mostly consist of relative rigid-like movements of a limited number of quasi-rigid domains, shared by the three proteins. Two common primary hinges for such movements are identified. The first hinge, whose functional role has been demonstrated by several experimental approaches, is located at the boundary between the N-terminal and Middle-domains. The second hinge is located at the end of a three-helix bundle in the Middle-domain and unfolds/unpacks going from the ATP- to the ADP-state. This latter site could represent a promising novel druggable allosteric site common to all chaperones.

Understanding the connections between structure, binding, dynamics and function in proteins is one of the most fascinating problems in biology and is actively investigated experimentally and computationally. In the latter context, significant advancements are possible by exposing the causal link between the fine atomic-scale protein-ligand interactions and the large-scale protein motions. One ideal avenue to explore this relationship is given by proteins of the Hsp90 chaperones family. Their dynamics is regulated by ATP binding and hydrolysis, which activates the onset of large-scale, functional conformational changes. Herein, we concentrated on three homologs with markedly different structural organization—mammalian Grp94, yeast Hsp90 and prokaryotic HtpG—and developed a novel computational multiscale approach to detect and characterize the salient traits of the functionally-oriented internal dynamics of the three chaperones. The comparative analysis, which exploits a novel highly simplified, yet viable, description of the protein internal dynamics, highlights fundamental mechanical aspects that preside the ligand-dependent conformational arrangements in all chaperones. For the three molecules, two corresponding regions are singled out as ligand-susceptible hinges for the large-scale internal motion. On the basis of this and other evidence it is suggested that these regions represent functionally relevant druggable substructures in the discovery of novel allosteric modulators.

Evolutionarily conserved linkage between enzyme fold, flexibility, and catalysis

Proteins are intrinsically flexible molecules. The role of internal motions in a protein's designated function is widely debated. The role of protein structure in enzyme catalysis is well established, and conservation of structural features provides vital clues to their role in function. Recently, it has been proposed that the protein function may involve multiple conformations: the observed deviations are not random thermodynamic fluctuations; rather, flexibility may be closely linked to protein function, including enzyme catalysis. We hypothesize that the argument of conservation of important structural features can also be extended to identification of protein flexibility in interconnection with enzyme function. Three classes of enzymes (prolyl-peptidyl isomerase, oxidoreductase, and nuclease) that catalyze diverse chemical reactions have been examined using detailed computational modeling. For each class, the identification and characterization of the internal protein motions coupled to the chemical step in enzyme mechanisms in multiple species show identical enzyme conformational fluctuations. In addition to the active-site residues, motions of protein surface loop regions (>10 Å away) are observed to be identical across species, and networks of conserved interactions/residues connect these highly flexible surface regions to the active-site residues that make direct contact with substrates. More interestingly, examination of reaction-coupled motions in non-homologous enzyme systems (with no structural or sequence similarity) that catalyze the same biochemical reaction shows motions that induce remarkably similar changes in the enzyme–substrate interactions during catalysis. The results indicate that the reaction-coupled flexibility is a conserved aspect of the enzyme molecular architecture. Protein motions in distal areas of homologous and non-homologous enzyme systems mediate similar changes in the active-site enzyme–substrate interactions, thereby impacting the mechanism of catalyzed chemistry. These results have implications for understanding the mechanism of allostery, and for protein engineering and drug design.

Comparing interfacial dynamics in protein-protein complexes: an elastic network approach

Background

The transient, or permanent, association of proteins to form organized complexes is one of the most common mechanisms of regulation of biological processes. Systematic physico-chemical studies of the binding interfaces have previously shown that a key mechanism for the formation/stabilization of dimers is the steric and chemical complementarity of the two semi-interfaces. The role of the fluctuation dynamics at the interface of the interacting subunits, although expectedly important, proved more elusive to characterize. The aim of the present computational study is to gain insight into salient dynamics-based aspects of protein-protein interfaces.

Results

The interface dynamics was characterized by means of an elastic network model for 22 representative dimers covering three main interface types. The three groups gather dimers sharing the same interface but with good (type I) or poor (type II) similarity of the overall fold, or dimers sharing only one of the semi-interfaces (type III). The set comprises obligate dimers, which are complexes for which no structural representative of the free form(s) is available. Considerations were accordingly limited to bound and unbound forms of the monomeric subunits of the dimers. We proceeded by first computing the mobility of amino acids at the interface of the bound forms and compare it with the mobility of (i) other surface amino acids (ii) interface amino acids in the unbound forms. In both cases different dynamic patterns were observed across interface types and depending on whether the interface belongs to an obligate or non-obligate complex.

Conclusions

The comparative investigation indicated that the mobility of amino acids at the dimeric interface is generally lower than for other amino acids at the protein surface. The change in interfacial mobility upon removing "in silico" the partner monomer (unbound form) was next found to be correlated with the interface type, size and obligate nature of the complex. In particular, going from the unbound to the bound forms, the interfacial mobility is noticeably reduced for dimers with type I interfaces, while it is largely unchanged for type II ones. The results suggest that these structurally- and biologically-different types of interfaces are stabilized by different balancing mechanisms between enthalpy and conformational entropy.

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.

Systematic study of anharmonic features in a principal component analysis of gramicidin A

We use principal component analysis (PCA) to detect functionally interesting collective motions in molecular-dynamics simulations of membrane-bound gramicidin A. We examine the statistical and structural properties of all PCA eigenvectors and eigenvalues for the backbone and side-chain atoms. All eigenvalue spectra show two distinct power-law scaling regimes, quantitatively separating large from small covariance motions. Time trajectories of the largest PCs converge to Gaussian distributions at long timescales, but groups of small-covariance PCs, which are usually ignored as noise, have subdiffusive distributions. These non-Gaussian distributions imply anharmonic motions on the free-energy surface. We characterize the anharmonic components of motion by analyzing the mean-square displacement for all PCs. The subdiffusive components reveal picosecond-scale oscillations in the mean-square displacement at frequencies consistent with infrared measurements. In this regime, the slowest backbone mode exhibits tilting of the peptide planes, which allows carbonyl oxygen atoms to provide surrogate solvation for water and cation transport in the channel lumen. Higher-frequency modes are also apparent, and we describe their vibrational spectra. Our findings expand the utility of PCA for quantifying the essential features of motion on the anharmonic free-energy surface made accessible by atomistic molecular-dynamics simulations.

Coarse-grained description of protein internal dynamics: an optimal strategy for decomposing proteins in rigid subunits

The possibility of accurately describing the internal dynamics of proteins, in terms of movements of a few approximately-rigid subparts, is an appealing biophysical problem with important implications for the analysis and interpretation of data from experiments or numerical simulations. The problem is tackled here by means of a novel variational approach that exploits information about equilibrium fluctuations of interresidues distances, provided, e.g., by atomistic molecular dynamics simulations or coarse-grained models. No contiguity in primary sequence or in space is enforced a priori for amino acids grouped in the same rigid unit. The identification of the rigid protein moduli, or dynamical domains, provides valuable insight into functionally oriented aspects of protein internal dynamics. To illustrate this point, we first discuss the decomposition of adenylate kinase and HIV-1 protease and then extend the investigation to several representatives of the hydrolase enzymatic class. The known catalytic site of these enzymes is found to be preferentially located close to the boundary separating the two primary dynamical subdomains.

Ru-TsDPEN with formic acid/Hunig's base for asymmetric transfer hydrogenation, a practical synthesis of optically enriched N-propyl pantolactam

The Noyori-Ikariya catalysts, Ru-TsDPEN 1 or 2, in combination with HCOOH/Hunig's base (5:2) have been successfully utilized for catalytic asymmetric transfer hydrogenation of alpha-ketopantolactam, and optically enriched N-substituted pantolactam was prepared (S/C = 500, up to 95% ee and 99% conversion in HCOOH/Hunig's base condition). More than 2 kg of this key intermediate 9 has been synthesized efficiently with excellent chemical yield and chiral purity.

Using dynamics-based comparisons to predict nucleic acid binding sites in proteins: an application to OB-fold domains

MOTIVATION

We have previously demonstrated that proteins may be aligned not only by sequence or structural homology, but also using their dynamical properties. Dynamics-based alignments are sensitive and powerful tools to compare even structurally dissimilar protein families. Here, we propose to use this method to predict protein regions involved in the binding of nucleic acids. We have used the OB-fold, a motif known to promote protein-nucleic acid interactions, to validate our approach.

RESULTS

We have tested the method using this well-characterized nucleic acid binding family. Protein regions consensually involved in statistically significant dynamics-based alignments were found to correlate with nucleic acid binding regions. The validated scheme was next used as a tool to predict which regions of the AXH-domain representatives (a sub-family of the OB-fold for which no DNA/RNA complex is yet available) are putatively involved in binding nucleic acids. The method, therefore, is a promising general approach for predicting functional regions in protein families on the basis of comparative large-scale dynamics.

AVAILABILITY

The software is available upon request from the authors, free of charge for academic users.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Small- and large-scale conformational changes of adenylate kinase: a molecular dynamics study of the subdomain motion and mechanics

Adenylate kinase, an enzyme that catalyzes the phosphoryl transfer between ATP and AMP, can interconvert between the open and catalytically potent (closed) forms even without binding ligands. Several aspects of the enzyme elasticity and internal dynamics are analyzed here by atomistic molecular dynamics simulations covering a total time span of 100 ns. This duration is sufficiently long to reveal a partial conversion of the enzyme that proceeds through jumps between structurally different substates. The intra- and intersubstates contributions to the enzyme's structural fluctuations are analyzed and compared both in magnitude and directionality. It is found that, despite the structural heterogeneity of the visited conformers, the generalized directions accounting for conformational fluctuations within and across the substates are mutually consistent and can be described by a limited set of collective modes. The functional-oriented nature of the consensus modes is suggested by their good overlap with the deformation vector bridging the open and closed crystal structures. The consistency of adenylate kinase's internal dynamics over timescales wide enough to capture intra- and intersubstates fluctuations adds elements in favor of the recent proposal that the free (apo) enzyme possesses an innate ability to sustain the open/close conformational changes.

Biocatalyst activity in nonaqueous environments correlates with centisecond-range protein motions

Recent studies exploring the relationship between enzymatic catalysis and protein dynamics in the aqueous phase have yielded evidence that dynamics and enzyme activity are strongly correlated. Given that protein dynamics are significantly attenuated in organic solvents and that proteins exhibit a wide range of motions depending on the specific solvent environment, the nonaqueous milieu provides a unique opportunity to examine the role of protein dynamics in enzyme activity. Variable-temperature kinetic measurements, X-band electron spin resonance spectroscopy, (1)H NMR relaxation, and (19)F NMR spectroscopy experiments were performed on subtilisin Carlsberg colyophilized with several inorganic salts and suspended in organic solvents. The results indicate that salt activation induces a greater degree of transition-state flexibility, reflected by a more positive DeltaDeltaS(dagger), for the more active biocatalyst preparations in organic solvents. In contrast, DeltaDeltaH(dagger) was negligible regardless of salt type or salt content. Electron spin resonance spectroscopy and (1)H NMR relaxation measurements, including spin-lattice relaxation, spin-lattice relaxation in the rotating frame, and longitudinal magnetization exchange, revealed that the enzyme's turnover number (k(cat)) was strongly correlated with protein motions in the centisecond time regime, weakly correlated with protein motions in the millisecond regime, and uncorrelated with protein motions on the piconanosecond timescale. In addition, (19)F chemical shift measurements and hyperfine tensor measurements of biocatalyst formulations inhibited with 4-fluorobenzenesulfonyl fluoride and 4-ethoxyfluorophosphinyl-oxy-TEMPO, respectively, suggest that enzyme activation was only weakly affected by changes in active-site polarity.

Correspondences between low-energy modes in enzymes: dynamics-based alignment of enzymatic functional families

Proteins that show similarity in their equilibrium dynamics can be aligned by identifying regions that undergo similar concerted movements. These movements are computed from protein native structures using coarse-grained elastic network models. We show the existence of common large-scale movements in enzymes selected from the main functional and structural classes. Alignment via dynamics does not require prior detection of sequence or structural correspondence. Indeed, a third of the statistically significant dynamics-based alignments involve enzymes that lack substantial global or local structural similarities. The analysis of specific residue-residue correspondences of these structurally dissimilar enzymes in some cases suggests a functional relationship of the detected common dynamic features. Including dynamics-based criteria in protein alignment thus provides a promising avenue for relating and grouping enzymes in terms of dynamic aspects that often, though not always, assist or accompany biological function.

Second step of hydrolytic dehalogenation in haloalkane dehalogenase investigated by QM/MM methods

Mechanistic studies on the hydrolytic dehalogenation catalyzed by haloalkane dehalogenases are of importance for environmental and industrial applications. Here, Car-Parrinello (CP) and ONIOM hybrid quantum-mechanical/molecular mechanics (QM/MM) are used investigate the second reaction step of the catalytic cycle, which comprises a general base-catalyzed hydrolysis of an ester intermediate (EI) to alcohol and free enzyme. We focus on the enzyme LinB from Sphingomonas paucimobilis UT26, for which the X-ray structure at atomic resolution is available. In agreement with previous proposals, our calculations suggest that a histidine residue (His272), polarized by glutamate (Glu132), acts as a base, accepting a proton from the catalytic water molecule and transferring it to an alcoholate ion. The reaction proceeds through a metastable tetrahedral intermediate, which shows an easily reversed reaction to the EI. In the formation of the products, the protonated aspartic acid (Asp108) can easily adopt conformation of the relaxed state found in the free enzyme. The overall free energy barrier of the reaction calculated by potential of the mean force integration using CP-QM/MM calculations is equal to 19.5 +/- 2 kcal . mol(-1). The lowering of the energy barrier of catalyzed reaction with respect to the water reaction is caused by strong stabilization of the reaction intermediate and transition state and their preorganization by electrostatic field of the enzyme.

Microseconds dynamics simulations of the outer-membrane protease T

Conformational fluctuations of enzymes may play an important role for substrate recognition and/or catalysis, as it has been suggested in the case of the protease enzymatic superfamily. Unfortunately, theoretically addressing this issue is a problem of formidable complexity, as the number of the involved degrees of freedom is enormous: indeed, the biological function of a protein depends, in principle, on all its atoms and on the surrounding water molecules. Here we investigated a membrane protease enzyme, the OmpT from Escherichia coli, by a hybrid molecular mechanics/coarse-grained approach, in which the active site is treated with the GROMOS force field, whereas the protein scaffold is described with a Go-model. The method has been previously tested against results obtained with all-atom simulations. Our results show that the large-scale motions and fluctuations of the electric field in the microsecond timescale may impact on the biological function and suggest that OmpT employs the same catalytic strategy as aspartic proteases. Such a conclusion cannot be drawn within the 10- to 100-ns timescale typical of current molecular dynamics simulations. In addition, our studies provide a structural explanation for the drop in the catalytic activity of two known mutants (S99A and H212A), suggesting that the coarse-grained approach is a fast and reliable tool for providing structure/function relationships for both wild-type OmpT and mutants.

NMR investigation of Tyr105 mutants in TEM-1 beta-lactamase: dynamics are correlated with function

The existence of coupled residue motions on various time scales in enzymes is now well accepted, and their detailed characterization has become an essential element in understanding the role of dynamics in catalysis. To this day, a handful of enzyme systems has been shown to rely on essential residue motions for catalysis, but the generality of such phenomena remains to be elucidated. Using NMR spectroscopy, we investigated the electronic and dynamic effects of several mutations at position 105 in TEM-1 beta-lactamase, an enzyme responsible for antibiotic resistance. Even in absence of substrate, our results show that the number and magnitude of short and long range effects on (1)H-(15)N chemical shifts are correlated with the catalytic efficiencies of the various Y105X mutants investigated. In addition, (15)N relaxation experiments on mutant Y105D show that several active-site residues of TEM-1 display significantly altered motions on both picosecond-nanosecond and microsecond-millisecond time scales despite many being far away from the site of mutation. The altered motions among various active-site residues in mutant Y105D may account for the observed decrease in catalytic efficiency, therefore suggesting that short and long range residue motions could play an important catalytic role in TEM-1 beta-lactamase. These results support previous observations suggesting that internal motions play a role in promoting protein function.