Molecular dynamics simulation of the Escherichia coli NikR protein: equilibrium conformational fluctuations reveal interdomain allosteric communication pathways

Bacterial Metallostasis: Metal Sensing, Metalloproteome Remodeling, and Metal Trafficking

Transition metals function as structural and catalytic cofactors for a large diversity of proteins and enzymes that collectively comprise the metalloproteome. Metallostasis considers all cellular processes, notably metal sensing, metalloproteome remodeling, and trafficking (or allocation) of metals that collectively ensure the functional integrity and adaptability of the metalloproteome. Bacteria employ both protein and RNA-based mechanisms that sense intracellular transition metal bioavailability and orchestrate systems-level outputs that maintain metallostasis. In this review, we contextualize metallostasis by briefly discussing the metalloproteome and specialized roles that metals play in biology. We then offer a comprehensive perspective on the diversity of metalloregulatory proteins and metal-sensing riboswitches, defining general principles within each sensor superfamily that capture how specificity is encoded in the sequence, and how selectivity can be leveraged in downstream synthetic biology and biotechnology applications. This is followed by a discussion of recent work that highlights selected metalloregulatory outputs, including metalloproteome remodeling and metal allocation by metallochaperones to both client proteins and compartments. We close by briefly discussing places where more work is needed to fill in gaps in our understanding of metallostasis.

The quaternary question: Determining allostery in spastin through dynamics classification learning and bioinformatics

The nanomachine from the ATPases associated with various cellular activities superfamily, called spastin, severs microtubules during cellular processes. To characterize the functionally important allostery in spastin, we employed methods from evolutionary information, to graph-based networks, to machine learning applied to atomistic molecular dynamics simulations of spastin in its monomeric and the functional hexameric forms, in the presence or absence of ligands. Feature selection, using machine learning approaches, for transitions between spastin states recognizes all the regions that have been proposed as allosteric or functional in the literature. The analysis of the composition of the Markov State Model macrostates in the spastin monomer, and the analysis of the direction of change in the top machine learning features for the transitions, indicate that the monomer favors the binding of ATP, which primes the regions involved in the formation of the inter-protomer interfaces for binding to other protomer(s). Allosteric path analysis of graph networks, built based on the cross-correlations between residues in simulations, shows that perturbations to a hub specific for the pre-hydrolysis hexamer propagate throughout the structure by passing through two obligatory regions: the ATP binding pocket, and pore loop 3, which connects the substrate binding site to the ATP binding site. Our findings support a model where the changes in the terminal protomers due to the binding of ligands play an active role in the force generation in spastin. The secondary structures in spastin, which are found to be highly degenerative within the network paths, are also critical for feature transitions of the classification models, which can guide the design of allosteric effectors to enhance or block allosteric signaling.

Bacterial Transcriptional Regulators: A Road Map for Functional, Structural, and Biophysical Characterization

The different niches through which bacteria move during their life cycle require a fast response to the many environmental queues they encounter. The sensing of these stimuli and their correct response is driven primarily by transcriptional regulators. This kind of protein is involved in sensing a wide array of chemical species, a process that ultimately leads to the regulation of gene transcription. The allosteric-coupling mechanism of sensing and regulation is a central aspect of biological systems and has become an important field of research during the last decades. In this review, we summarize the state-of-the-art techniques applied to unravel these complex mechanisms. We introduce a roadmap that may serve for experimental design, depending on the answers we seek and the initial information we have about the system of study. We also provide information on databases containing available structural information on each family of transcriptional regulators. Finally, we discuss the recent results of research about the allosteric mechanisms of sensing and regulation involving many transcriptional regulators of interest, highlighting multipronged strategies and novel experimental techniques. The aim of the experiments discussed here was to provide a better understanding at a molecular level of how bacteria adapt to the different environmental threats they face.

A Time-Dependent Quantum Approach to Allostery and a Comparison With Light-Harvesting in Photosynthetic Phenomenon

The allosteric effect is one of the most important processes in regulating the function of proteins, and the elucidation of this phenomenon plays a significant role in understanding emergent behaviors in biological regulation. In this process, a perturbation, generated by a ligand in a part of the macromolecule (the allosteric site), moves along this system and reaches a specific (active) site, dozens of Ångströms away, with a great efficiency. The dynamics of this perturbation in the macromolecule can model precisely the allosteric process. In this article, we will be studying the general characteristics of allostery, using a time-dependent quantum approach to obtain rules that apply to this kind of process. Considering the perturbation as a wave that moves within the molecular system, we will characterize the allosteric process with three of the properties of this wave in the active site: (1) t_a, the characteristic time for reaching that site, (2) A_a, the amplitude of the wave in this site, and (3) B_a, its corresponding spectral broadening. These three parameters, together with the process mechanism and the perturbation efficiency in the process, can describe the phenomenon. One of the main purposes of this paper is to link the parameters t_a, A_a, and B_a and the perturbation efficiency to the characteristics of the system. There is another fundamental process for life that has some characteristics similar to allostery: the light-harvesting (LH) process in photosynthesis. Here, as in allostery, two distant macromolecular sites are involved—two sites dozens of Ångströms away. In both processes, it is particularly important that the perturbation is distributed efficiently without dissipating in the infinite degrees of freedom within the macromolecule. The importance of considering quantum effects in the LH process is well documented in literature, and the quantum coherences are experimentally proven by time-dependent spectroscopic techniques. Given the existing similarities between these two processes in macromolecules, in this work, we suggest using Quantum Mechanics (QM) to study allostery.

An investigation into the allosteric mechanism of GPCR A2A adenosine receptor with trajectory-based information theory and complex network model

G protein-coupled receptors (GPCRs), a large superfamily of transmembrane (TM) proteins, allosterically transduce the signal of ligand binding in the extracellular (EC) domain to couple to effector proteins in the intracellular (IC) domain, therefore forming the largest class of drug targets. The A_2A adenosine receptor (A_2AAR), a class-A GPCR, has been extensively studied as it offers numerous possibilities for therapeutic applications. However, the mechanism of allosteric communication between EC and IC domains is not completely clear. In this work, we utilize torsional mutual information to quantify the correlated motions of residue pairs from its molecular dynamics (MD) simulation trajectories, and further use the complex network model to obtain allosteric pipelines and hubs. The identified allosteric communication pipelines mainly transmit the signal from EC domain to the cytoplasmic ends of TM helix 5 (TM5), TM6 and TM7. The allosteric hubs, mostly located at TM5, TM6 and TM7, play an important role in mediating allosteric signal transmission to keep the receptor rigid and prevent G protein from binding to IC domain, which can explain the reason why their mutations distant from ligand-binding site do not affect the ligand binding affinity but affect the ligand efficacy. Additionally, we identify the key residues located in antagonist ZM241385 binding pocket which mediate multiple allosteric pathways and have been experimentally proven to play a critical role in affecting the ligand potency. This study is helpful for understanding the allosteric communication mechanism of A_2AAR, and can provide valuable information for the structure-based drug design of GPCRs.Communicated by Ramaswamy H. Sarma.

Revisiting allostery in CREB-binding protein (CBP) using residue-based interaction energy

CREB-binding protein (CBP) is a multi-subunit scaffold protein complex in transcription regulation process, binding and interacting with ligands such as mixed-lineage leukemia (MLL) and c-Myb allosterically. Here in this study, we have revisited the concept of allostery in CBP via residue-based interaction energy calculation based on molecular dynamics (MD) simulations. To this end, we conducted MD simulations of KIX:MLL:c-Myb ternary complex, its binary components and kinase-inducible domain (KID) interacting domain (KIX) backbone. Interaction energy profiles and cross correlation analysis were performed and the results indicated that KIX:MLL and KIX:c-Myb:MLL complexes demonstrate significant similarities according to both analysis methods. Two regions in the KIX backbone were apparent from the interaction energy and cross correlation maps that hold a key to allostery phenomena observed in CBP. While one of these regions are related to the ligand binding residues, the other comprises of L₁₂-G₂ loop and α₃ helix regions that have been found to have a significant role in allosteric signal propagation. All in all, residue-based interaction energy calculation method is demonstrated to be a valuable calculation technique for the detection of allosteric signal propagation and ligand interaction regions.

Dynamic allostery-based molecular workings of kinase:peptide complexes

A dense interplay between structure and dynamics underlies the working of proteins, especially enzymes. Protein kinases are molecular switches that are optimized for their regulation rather than catalytic turnover rates. Using long-simulations dynamic allostery analysis, this study describes an exploration of the dynamic kinase:peptide complex. We have used protein kinase A (PKA) as a model system as a generic prototype of the protein kinase superfamily of signaling enzymes. Our results explain the role of dynamic coupling of active-site residues that must work in coherence to provide for a successful activation or inhibition response from the kinase. Amino acid networks-based community analysis allows us to ponder the conformational entropy of the kinase:nucleotide:peptide ternary complex. We use a combination of 7 peptides that include 3 types of PKA-binding partners: Substrates, products, and inhibitors. The substrate peptides provide for dynamic insights into the enzyme:substrate complex, while the product phospho-peptide allows for accessing modes of enzyme:product release. Mapping of allosteric communities onto the PKA structure allows us to locate the more unvarying and flexible dynamic regions of the kinase. These distributions, when correlated with the structural elements of the kinase core, allow for a detailed exploration of key dynamics-based signatures that could affect peptide recognition and binding at the kinase active site. These studies provide a unique dynamic allostery-based perspective to kinase:peptide complexes that have previously been explored only in a structural or thermodynamic context.

ProSNEx: a web-based application for exploration and analysis of protein structures using network formalism

ProSNEx (Protein Structure Network Explorer) is a web service for construction and analysis of Protein Structure Networks (PSNs) alongside amino acid flexibility, sequence conservation and annotation features. ProSNEx constructs a PSN by adding nodes to represent residues and edges between these nodes using user-specified interaction distance cutoffs for either carbon-alpha, carbon-beta or atom-pair contact networks. Different types of weighted networks can also be constructed by using either (i) the residue-residue interaction energies in the format returned by gRINN, resulting in a Protein Energy Network (PEN); (ii) the dynamical cross correlations from a coarse-grained Normal Mode Analysis (NMA) of the protein structure; (iii) interaction strength. Upon construction of the network, common network metrics (such as node centralities) as well as shortest paths between nodes and k-cliques are calculated. Moreover, additional features of each residue in the form of conservation scores and mutation/natural variant information are included in the analysis. By this way, tool offers an enhanced and direct comparison of network-based residue metrics with other types of biological information. ProSNEx is free and open to all users without login requirement at http://prosnex-tool.com.

Singular value decomposition for the correlation of atomic fluctuations with arbitrary angle

Many proteins exhibit a critical property called allostery, which enables intra-molecular transmission of information between distal sites. Microscopically, allosteric response is closely related to correlated atomic fluctuations. Conventional correlation analysis correlates the atomic fluctuations at two sites by taking the dot product (DP) between the fluctuations, which accounts only for the parallel and antiparallel components. Here, we present a singular value decomposition (SVD) method that analyzes the correlation coefficient of fluctuation dynamics with an arbitrary angle between the correlated directions. In a model allosteric system, the second PDZ domain (PDZ2) in the human PTP1E protein, approximately one third of the strong correlations have near-perpendicular directions, which are underestimated in the conventional method. The discrimination becomes more prominent for residue pairs with larger separation. The results of the proposed SVD method are more consistent with the experimentally determined PDZ2 dynamics than those of conventional method. In addition, the SVD method improved the prediction accuracy of the allosteric sites in a dataset of 23 known allosteric monomer proteins. The proposed method may inspire extended investigation not only into allostery, but also into protein dynamics and drug design.

Allosteric Communication Networks in Proteins Revealed through Pocket Crosstalk Analysis

The detection and characterization of binding pockets and allosteric communication in proteins is crucial for studying biological regulation and performing drug design. Nowadays, ever-longer molecular dynamics (MD) simulations are routinely used to investigate the spatiotemporal evolution of proteins. Yet, there is no computational tool that can automatically detect all the pockets and potential allosteric communication networks along these extended MD simulations. Here, we use a novel and fully automated algorithm that examines pocket formation, dynamics, and allosteric communication embedded in microsecond-long MD simulations of three pharmaceutically relevant proteins, namely, PNP, A2A, and Abl kinase. This dynamic analysis uses pocket crosstalk, defined as the temporal exchange of atoms between adjacent pockets, along the MD trajectories as a fingerprint of hidden allosteric communication networks. Importantly, this study indicates that dynamic pocket crosstalk analysis provides new mechanistic understandings on allosteric communication networks, enriching the available experimental data. Thus, our results suggest the prospective use of this unprecedented dynamic analysis to characterize transient binding pockets for structure-based drug design.

Dynamical persistence of active sites identified in maltose-binding protein

This study identifies dynamical properties of maltose-binding protein (MBP) useful in unveiling active site residues susceptible to ligand binding. The described methodology has been previously used in support of novel topological techniques of persistent homology and statistical inference in complex, multi-scale, high-dimensional data often encountered in computational biophysics. Here we outline a computational protocol that is based on the anisotropic elastic network models of 14 all-atom three-dimensional protein structures. We introduce the notion of dynamical distance matrices as a measure of correlated interactions among 370 amino acid residues that constitute a single protein. The dynamical distance matrices serve as an input for a persistent homology suite of codes to further distinguish a small subset of residues with high affinity for ligand binding and allosteric activity. In addition, we show that ligand-free closed MBP structures require lower deformation energies than open MBP structures, which may be used in categorization of time-evolving molecular dynamics structures. Analysis of the most probable allosteric coupling pathways between active site residues and the protein exterior is also presented.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Discovery of Novel Allosteric Eg5 Inhibitors Through Structure-Based Virtual Screening

Mitotic kinesin Eg5 is an attractive anticancer drug target. Discovery of Eg5 inhibitors has been focused on targeting the 'monastrol-binding site'. However, acquired drug resistance has been reported for such inhibitors. Therefore, identifying new Eg5 inhibitors which function through a different mechanism(s) could complement current drug candidates and improve drug efficacy. In this study, we explored a novel allosteric site of Eg5 and identified new Eg5 inhibitors through structure-based virtual screening. Experiments with the saturation-transfer difference NMR demonstrated that the identified Eg5 inhibitor SRI35566 binds directly to Eg5 without involving microtubules. Moreover, SRI35566 and its two analogs significantly induced monopolar spindle formation in colorectal cancer HCT116 cells and suppressed cancer cell viability and colony formation. Together, our findings reveal a new allosteric regulation mechanism of Eg5 and a novel drug targeting site for cancer therapy.

Evolution of Macromolecular Docking Techniques: The Case Study of Nickel and Iron Metabolism in Pathogenic Bacteria

The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation, in the docking process, of experimentally derived information, together with the possibility of accounting for the flexibility of the interacting molecules. Here we review the results and the evolution of the techniques used to study the interaction between metallo-proteins and DNA operators, all involved in the nickel and iron metabolism of pathogenic bacteria, focusing in particular on Helicobacter pylori (Hp). In the first part of the article we discuss the methods used to calculate the structure of complexes of proteins involved in the activation of the nickel-dependent enzyme urease. In the second part of the article, we concentrate on two applications of protein-DNA docking conducted on the transcription factors HpFur (ferric uptake regulator) and HpNikR (nickel regulator). In both cases we discuss the technical expedients used to take into account the conformational variability of the multi-domain proteins involved in the calculations.

Nickel-responsive transcriptional regulators

The structural features, metal coordination modes and metal binding thermodynamics of known Ni(ii)-dependent transcriptional regulators are highlighted and discussed.

Identification of the binding site of an allosteric ligand using STD-NMR, docking, and CORCEMA-ST calculations

Singling out the truth: A combined application of STD-NMR, molecular docking, and CORCEMA-ST calculations is described as an attractive, easily applicable tool for the identification and validation of the binding site for allosteric ligands, with potential application as an aid in drug discovery research.

Secondary anionic phospholipid binding site and gating mechanism in Kir2.1 inward rectifier channels

Inwardly rectifying potassium (Kir) channels regulate multiple tissues. All Kir channels require interaction of phosphatidyl-4,5-bisphosphate (PIP2) at a crystallographically identified binding site, but an additional nonspecific secondary anionic phospholipid (PL(-)) is required to generate high PIP2 sensitivity of Kir2 channel gating. The PL(-)-binding site and mechanism are yet to be elucidated. Here we report docking simulations that identify a putative PL(-)-binding site, adjacent to the PIP2-binding site, generated by two lysine residues from neighbouring subunits. When either lysine is mutated to cysteine (K64C and K219C), channel activity is significantly decreased in cells and in reconstituted liposomes. Directly tethering K64C to the membrane by modification with decyl-MTS generates high PIP2 sensitivity in liposomes, even in the complete absence of PL(-)s. The results provide a coherent molecular mechanism whereby PL(-) interaction with a discrete binding site results in a conformational change that stabilizes the high-affinity PIP2 activatory site.

Biomolecular electrostatics and solvation: a computational perspective

An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

Dynamics of heme complexed with human serum albumin: a theoretical approach

Human serum albumin (HSA) is the most abundant protein in the blood serum. It binds several ligands and has an especially strong affinity for heme, hence becoming a natural candidate for oxygen transport. In order to analyze the interaction of HSA-heme, molecular dynamics simulations of HSA with bound heme were performed. Based on the results of X-ray diffraction, the binding site of the heme, localized in subdomain IB, was considered. We analyzed the fluctuations and their correlations along trajectories to detect collective motions. The role of H bonds and salt bridges in the stabilization of heme in its pocket was also investigated. Complementarily, the localization of water molecules in the hydrophobic pocket and the interaction with heme were discussed.

Nonspecific interactions between Escherichia coli NikR and DNA are critical for nickel-activated DNA binding

The Escherichia coli transcription factor NikR is responsible for nickel-mediated repression of the operon encoding the Nik uptake transporter. The crystal structure of Ni(II)-NikR bound to the nik operator sequence revealed that residues in the loop preceding helix α3 in the metal-binding domain, which becomes structurally ordered upon stoichiometric nickel binding, interact with the DNA backbone. Here, we show that mutating both of these residues that make the nonspecific contacts, K64 and R65, abolishes DNA binding in vitro and nickel-responsive transcriptional repression of the nik promoter in vivo. In contrast, mutation of Q118, which forms a bridge between R65 and a potassium site, does not impact the activities of NikR. These data support the model that the nonspecific interactions between the metal-binding domain of the protein and the DNA phosphodiester backbone are critical for the Ni(II)-responsive activity of E. coli NikR.

Space warping order parameters and symmetry: application to multiscale simulation of macromolecular assemblies

Coarse-grained features of macromolecular assemblies are understood via a set of order parameters (OPs) constructed in terms of their all-atom configuration. OPs are shown to be slowly changing in time and capture the large-scale spatial features of macromolecular assemblies. The relationship of these variables to the classic notion of OPs based on symmetry breaking phase transitions is discussed. OPs based on space warping transformations are analyzed in detail as they naturally provide a connection between overall structure of an assembly and all-atom configuration. These OPs serve as the basis of a multiscale analysis that yields Langevin equations for OP dynamics. In this context, the characteristics of OPs and PCA modes are compared. The OPs enable efficient all-atom multiscale simulations of the dynamics of macromolecular assemblies in response to changes in microenvironmental conditions, as demonstrated on the structural transitions of cowpea chlorotic mottle virus capsid (CCMV) and RNA of the satellite tobacco mosaic virus (STMV).

Exploring residue component contributions to dynamical network models of allostery

Allosteric regulation in biological systems is of considerable interest given the vast number of proteins that exhibit such behavior. Network models obtained from molecular dynamics simulations have been shown to be powerful tools for the analysis of allostery. In this work, different coarse-grain residue representations (nodes) are used together with a dynamical network model to investigate models of allosteric regulation. This model assumes that allosteric signals are dependent on positional correlations of protein substituents, as determined through molecular dynamics simulations, and uses correlated motion to generate a signaling weight between two given nodes. We examine four types of network models using different node representations in Cartesian coordinates: the (i) residue alpha-carbons, (ii) sidechain center of mass, (iii) backbone center of mass, and the entire (iv) residue center of mass. All correlations are filtered by a dynamic contact map that defines the allowable interactions between nodes based on physical proximity. We apply the four models to imidazole glycerol phosphate synthase (IGPS), which provides a well-studied experimental framework in which allosteric communication is known to persist across disparate protein domains (e.g. a protein dimer interface). IGPS is modeled as a network of nodes and weighted edges. Optimal allosteric pathways are traced using the Floyd Warshall algorithm for weighted networks, and community analysis (a form of hierarchical clustering) is performed using the Girvan-Newman algorithm. Our results show that dynamical information encoded in the residue center of mass must be included in order to detect residues that are experimentally known to play a role in allosteric communication for IGPS. More broadly, this new method may be useful for predicting pathways of allosteric communication for any biomolecular system in atomic detail.

Comparing Conformational Ensembles Using the Kullback-Leibler Divergence Expansion

We present a thermodynamical approach to identify changes in macromolecular structure and dynamics in response to perturbations such as mutations or ligand binding, using an expansion of the Kullback-Leibler Divergence that connects local population shifts in torsion angles to changes in the free energy landscape of the protein. While the Kullback-Leibler Divergence is a known formula from information theory, the novelty and power of our implementation lies in its formal developments, connection to thermodynamics, statistical filtering, ease of visualization of results, and extendability by adding higher-order terms. We present a formal derivation of the Kullback-Leibler Divergence expansion and then apply our method at a first-order approximation to molecular dynamics simulations of four protein systems where ligand binding or pH titration is known to cause an effect at a distant site. Our results qualitatively agree with experimental measurements of local changes in structure or dynamics, such as NMR chemical shift perturbations and hydrogen-deuterium exchange mass spectrometry. The approach produces easy-to-analyze results with low background, and as such has the potential to become a routine analysis when molecular dynamics simulations in two or more conditions are available. Our method is implemented in the MutInf code package and is available on the SimTK website at https://simtk.org/home/mutinf.

Metal site occupancy and allosteric switching in bacterial metal sensor proteins

All prokaryotes encode a panel of metal sensor or metalloregulatory proteins that govern the expression of genes that allows an organism to quickly adapt to toxicity or deprivation of both biologically essential transition metal ions, e.g., Zn, Cu, Fe, and heavy metal pollutants. As such, metal sensor proteins can be considered arbiters of intracellular transition metal bioavailability and thus potentially control the metallation state of the metalloproteins in the cell. Metal sensor proteins are specialized allosteric proteins that regulate transcription as a result direct binding of one or two cognate metal ions, to the exclusion of all others. In most cases, the binding of the cognate metal ion induces a structural change in a protein oligomer that either activates or inhibits operator DNA binding. A quantitative measure of the degree to which a particular metal drives metalloregulation of operator DNA-binding is the allosteric coupling free energy, ΔGc. In this review, we summarize recent work directed toward understanding metal occupancy and metal selectivity of these allosteric switches in selected families of metal sensor proteins and examine the structural origins of ΔGc in the functional context a thermodynamic "set-point" model of intracellular metal homeostasis.

Ultrafast dynamics of nonequilibrium resonance energy transfer and probing globular protein flexibility of myoglobin

Protein structural plasticity is critical to many biological activities and accurate determination of its temporal and spatial fluctuations is challenging and difficult. Here, we report our extensive characterization of global flexibility of a globular heme protein of myoglobin using resonance energy transfer as a molecular ruler. With site-directed mutagenesis, we use a tryptophan scan to examine local structural fluctuations from B to H helices utilizing 10 tryptophan-heme energy transfer pairs with femtosecond resolution. We observed ultrafast resonance energy transfer dynamics by following a nearly single exponential behavior in 10-100 ps, strongly indicating that the globular structure of myoglobin is relatively rigid, with no observable static or slow dynamic conformational heterogeneity. The observation is against our molecular dynamics simulations, which show large local fluctuations and give multiple exponential energy transfer behaviors, suggesting too flexible of the global structure and thus raising a serious issue of the force fields used in simulations. Finally, these ultrafast energy transfer dynamics all occur on the similar time scales of local environmental relaxations (solvation), leading to nonexponential processes caused by energy relaxations, not structural fluctuations. Our analyses of such processes reveal an intrinsic compressed- and/or stretched-exponential behaviors and elucidate the nature of inherent nonequilibrium of ultrafast resonance energy transfer in proteins. This new concept of compressed nonequilibrium transfer dynamics should be applied to all protein studies by time-resolved Förster resonance energy transfer (FRET).

Helicobacter pylori NikR protein exhibits distinct conformations when bound to different promoters

Helicobacter pylori NikR (HpNikR) is a ribbon-helix-helix (RHH) DNA-binding protein that binds to several different promoter regions. The binding site sequences are not absolutely conserved. The ability of HpNikR to discriminate specific DNA sites resides partly in its nine-amino acid N-terminal arm. Previously, indirect evidence indicated that the arm exists in different conformations when HpNikR is bound to the nixA and ureA promoters. Here, we directly examined HpNikR conformation when it was bound to nixA and ureA DNA fragments by tethering (S)-1{[bis(carboxymethyl)amino]methyl}-2-{4-[(2-bromoacetyl)amino]phenylethyl}(carboxymethyl)amino]acetic acid, iron(III) to different positions in the N-terminal arm and RHH DNA binding domain. Different cleavage patterns at each promoter directly demonstrated that both the RHH domain and the arm adopt different conformations on the nixA and ureA promoters. Additionally, the two RHH domain dimers of the HpNikR tetramer are in distinct conformations at ureA. Site-directed mutagenesis identified an interchain salt bridge (Lys(48)-Glu(47')) in the RHH domain remote from the DNA binding interface that is required for high affinity binding to ureA but not nixA. Finally, DNA affinity measurements of wild-type HpNikR and a salt bridge mutant (K48A) to hybrid nixA-ureA promoters demonstrated that inverted repeat half-sites, spacers, and flanking DNA are all required for sequence-specific DNA binding by HpNikR. Notably, the spacer region made the largest contribution to DNA affinity. HpNikR exhibits a substantially expanded regulon compared with other NikR proteins. The results presented here provide a molecular basis for understanding regulatory network expansion by NikR as well as other prokaryotic regulatory proteins.

Investigating dynamic and energetic determinants of protein nucleic acid recognition: analysis of the zinc finger zif268-DNA complexes

BACKGROUND

Protein-DNA recognition underlies fundamental biological processes ranging from transcription to replication and modification. Herein, we present a computational study of the sequence modulation of internal dynamic properties and of intraprotein networks of aminoacid interactions that determine the stability and specificity of protein-DNA complexes.

RESULTS

To this aim, we apply novel theoretical approaches to analyze the dynamics and energetics of biological systems starting from MD trajectories. As model system, we chose different sequences of Zinc Fingers (ZF) of the Zif268 family bound with different sequences of DNA. The complexes differ for their experimental stability properties, but share the same overall 3 D structure and do not undergo structural modifications during the simulations. The results of our analysis suggest that the energy landscape for DNA binding may be populated by dynamically different states, even in the absence of major conformational changes. Energetic couplings between residues change in response to protein and/or DNA sequence variations thus modulating the selectivity of recognition and the relative importance of different regions for binding.

CONCLUSIONS

The results show differences in the organization of the intra-protein energy-networks responsible for the stabilization of the protein conformations recognizing and binding DNA. These, in turn, are reflected into different modulation of the ZF's internal dynamics. The results also show a correlation between energetic and dynamic properties of the different proteins and their specificity/selectivity for DNA sequences. Finally, a dynamic and energetic model for the recognition of DNA by Zinc Fingers is proposed.

Role of altered sialylation of the I-like domain of beta1 integrin in the binding of fibronectin to beta1 integrin: thermodynamics and conformational analyses

N-glycosylation of the I-like domain of beta1 integrin plays an essential role in integrin structure and function, and the altered sialylation of beta1 integrin regulates beta1 integrin binding to fibronectin. However, the structural basis underlying the effect of altered sialylation of the beta1 I-like domain on beta1 integrin binding to fibronectin remains largely unknown. In this study, we used a combination of molecular dynamics simulations and binding free energy analyses to investigate changes in binding thermodynamics and in conformation of the glycosylated beta1 I-like domain-FN-III(9-10) complex caused by altered sialylation of the beta1 I-like domain. Binding free energy analyses showed that desialylation of beta1 I-like domain increased beta1 integrin binding to fibronectin, consistent with experimental results. Interaction analyses showed that altered sialylation of the beta1 I-like domain resulted in significant changes in the interaction of the N-glycans of the I-like domain with both the I-like domain and fibronectin, and these changes could directly affect the allosteric regulation of the interaction between the I-like domain and fibronectin. Altered sialylation of the beta1 I-like domain caused significant conformational changes in key functional sites of both the beta1 I-like domain and fibronectin. In addition, altered sialylation of the beta1 I-like domain resulted in changes in the degree of correlated motions between residues in the I-like domain and residues in fibronectin, and in the degree of motion changes in fibronectin, which could affect beta1 integrin binding to fibronectin. We believe results from this study provide thermodynamic and structural evidence for a role of altered sialylation of beta1 integrin in regulating beta1 integrin binding to fibronectin and it's induced cellular activities.

Characterization of the RND family of multidrug efflux pumps: in silico to in vivo confirmation of four functionally distinct subgroups

We have developed a generalized profile that identifies members of the root-nodulation-cell-division (RND) family of efflux pumps and classifies them into four functional subfamilies. According to Z-score values, efflux pumps can be grouped by their metabolic function, thus making it possible to distinguish pumps involved in antibiotic resistance (group 1) from those involved in metal resistance (group 3). In silico data regarding efflux pumps in group 1 were validated after identification of RND efflux pumps in a number of environmental microbes that were isolated as resistant to ethidium bromide. Analysis of the Pseudomonas putida KT2440 genome identified efflux pumps in all groups. A collection of mutants in efflux pumps and a screening platform consisting of 50 drugs were created to assign a function to the efflux pumps. We validated in silico data regarding efflux pumps in groups 1 and 3 using 9 different mutants. Four mutants belonging to group 2 were found to be more sensitive than the wild-type to oxidative stress-inducing agents such as bipyridyl and methyl viologen. The two remaining mutants belonging to group 4 were found to be more sensitive than the parental to tetracycline and one of them was particularly sensitive to rubidium and chromate. By effectively combining in vivo data with generalized profiles and gene annotation data, this approach allowed the assignment, according to metabolic function, of both known and uncharacterized RND efflux pumps into subgroups, thereby providing important new insight into the functions of proteins within this family.

Conserved tertiary couplings stabilize elements in the PDZ fold, leading to characteristic patterns of domain conformational flexibility

Single-domain allostery has been postulated to occur through intramolecular pathways of signaling within a protein structure. We had previously investigated these pathways by introducing a local thermal perturbation and analyzed the anisotropic propagation of structural changes throughout the protein. Here, we develop an improved approach, the Rotamerically Induced Perturbation (RIP), that identifies strong couplings between residues by analyzing the pathways of heat-flow resulting from thermal excitation of rotameric rotations at individual residues. To explore the nature of these couplings, we calculate the complete coupling maps of 5 different PDZ domains. Although the PDZ domain is a well conserved structural fold that serves as a scaffold in many protein-protein complexes, different PDZ domains display unique patterns of conformational flexibility in response to ligand binding: some show a significant shift in a set of alpha-helices, while others do not. Analysis of the coupling maps suggests a simple relationship between the computed couplings and observed conformational flexibility. In domains where the alpha-helices are rigid, we find couplings of the alpha-helices to the body of the protein, whereas in domains having ligand-responsive alpha-helices, no couplings are found. This leads to a model where the alpha-helices are intrinsically dynamic but can be damped if sidechains interact at key tertiary contacts. These tertiary contacts correlate to high covariation contacts as identified by the statistical coupling analysis method. As these dynamic modules are exploited by various allosteric mechanisms, these tertiary contacts have been conserved by evolution.

Cooperative nature of gating transitions in K(+) channels as seen from dynamic importance sampling calculations

The growing dataset of K(+) channel x-ray structures provides an excellent opportunity to begin a detailed molecular understanding of voltage-dependent gating. These structures, while differing in sequence, represent either a stable open or closed state. However, an understanding of the molecular details of gating will require models for the transitions and experimentally testable predictions for the gating transition. To explore these ideas, we apply dynamic importance sampling to a set of homology models for the molecular conformations of K(+) channels for four different sets of sequences and eight different states. In our results, we highlight the importance of particular residues upstream from the Pro-Val-Pro (PVP) region to the gating transition. This supports growing evidence that the PVP region is important for influencing the flexibility of the S6 helix and thus the opening of the gating domain. The results further suggest how gating on the molecular level depends on intra-subunit motions to influence the cooperative behavior of all four subunits of the K(+) channel. We hypothesize that the gating process occurs in steps: first sidechain movement, then inter-S5-S6 subunit motions, and lastly the large-scale domain rearrangements.

Molecular mechanism of allosteric communication in the human PPARalpha-RXRalpha heterodimer

The peroxisome proliferator-activated receptor alpha (PPARalpha) is a nuclear receptor (NR) that forms a heterodimeric transcription factor complex with the retinoid X receptor alpha (RXRalpha). The phenomenon that the heterodimer can be activated by both PPARalpha and RXRalpha ligands, while both ligands have a synergistic effect on its activity suggests that there is an allosteric communication within the heterodimer. In this study, the molecular mechanism of this allosteric signaling was studied by molecular dynamics (MD) simulations and some of the residues involved in this communication were tested experimentally. Multiple MD simulations were done for the PPARalpha-RXRalpha heterodimer ligand-binding domains (LBDs) without ligands, with agonistic ligand bound to RXRalpha or PPARalpha, and ligand bound to both receptors. Fluctuation calculations and structural clustering analysis of the heterodimer MD simulations showed that ligand binding to RXRalpha decreases fluctuations of large parts of PPARalpha, most notably helices 3 and 4 at the coactivator binding site, which presumably stabilizes the coactivator binding to heterodimer complex. The dynamics of helix 8-9 loop and helix 10/11 located at the heterodimeric interface were affected by RXRalpha ligand binding, suggesting that these parts of the dimer are involved in allosteric communication. Experimental data complemented this view by showing that a large set of residues at the heterodimerization surface has a role in the communication. These results provided evidence that RXRalpha ligand binding-induced stabilization of PPARalpha coactivator binding site has a role in the permissive and synergistic activation of the PPARalpha-RXRalpha heterodimer. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Coordinating intracellular nickel-metal-site structure-function relationships and the NikR and RcnR repressors

Metalloregulator function requires both sensitivity and selectivity to ensure metal-specific activity without interfering with intracellular metal trafficking pathways. Here, we examine the role of metal coordination geometry in the function of NikR and RcnR, two widely conserved nickel-responsive regulators that are both present in E. coli. The available data suggest an emerging trend in which coordination number is linked to metal-binding affinity, and thus regulatory function. The differences in coordination geometry also suggest that the kinetic mechanisms of metal-association and dissociation will contribute to metalloregulator function. We also discuss ways in which the ligand binding properties of metalloregulators may be tuned to alter the regulatory response.

Apo and nickel-bound forms of the Pyrococcus horikoshii species of the metalloregulatory protein: NikR characterized by molecular dynamics simulations

NikR is a homotetrameric nickel regulatory protein whose binding to free Ni(2+) increases its binding affinity for a gene that codes for a nickel transporter protein. It is comprised of a tetrameric nickel-binding domain, flanked by two dimeric DNA-binding domains. Though X-ray crystallography data for various species (Escherichia coli, Heliobacter pylori, and Pyrococcus horikoshii) of NikR reveal large conformational differences between nickel-bound, DNA-bound, and unbound forms, transitions between them have never been observed. We have run all-atom molecular dynamics simulations of three forms of the Pyrococcus horikoshii species of NikR including two apo-forms and one nickel-bound form. Though all 552 residues of this species occur naturally, quantum-mechanics-based force-field parametrization was required to accurately represent the four nickel-centers in the nickel-bound form. Global conformational analysis of the three 100-ns-long simulations indicates slow conformational kinetics and independent DNA binding domain motion. Correlation and flexibility analysis revealed regions of high structural and dynamical importance. A striking relationship was observed between regions with high levels of structural importance and regions with known biological importance. Mutation of key regions of P. horikoshii and analogous regions in both E. coli and H. pylori are suggested that might inhibit DNA-binding activity while not affecting nickel-binding.

Structural and mechanistic insights into Helicobacter pylori NikR activation

NikR is a transcriptional metalloregulator central in the mandatory response to acidity of Helicobacter pylori that controls the expression of numerous genes by binding to specific promoter regions. NikR/DNA interactions were proposed to rely on protein activation by Ni(II) binding to high-affinity (HA) and possibly secondary external (X) sites. We describe a biochemical characterization of HpNikR mutants that shows that the HA sites are essential but not sufficient for DNA binding, while the secondary external (X) sites and residues from the HpNikR dimer–dimer interface are important for DNA binding. We show that a second metal is necessary for HpNikR/DNA binding, but only to some promoters. Small-angle X-ray scattering shows that HpNikR adopts a defined conformation in solution, resembling the cis-conformation and suggests that nickel does not trigger large conformational changes in HpNikR. The crystal structures of selected mutants identify the effects of each mutation on HpNikR structure. This study unravels key structural features from which we derive a model for HpNikR activation where: (i) HA sites and an hydrogen bond network are required for DNA binding and (ii) metallation of a unique secondary external site (X) modulates HpNikR DNA binding to low-affinity promoters by disruption of a salt bridge.

From the gating charge response to pore domain movement: initial motions of Kv1.2 dynamics under physiological voltage changes

Recent structures of the potassium channel provide an essential beginning point for explaining how the pore is gated between open and closed conformations by changes in membrane voltage. Yet, the molecular details of this process and the connections to transmembrane gradients are not understood. To begin addressing how changes within a membrane environment lead to the channel's ability to sense shifts in membrane voltage and to gate, we performed double-bilayer simulations of the Kv1.2 channel. These double-bilayer simulations enable us to simulate realistic voltage drops from resting potential conditions to depolarized conditions by changes in the bath conditions on each side of the bilayer. Our results show how the voltage sensor domain movement responds to differences in transmembrane potential. The initial voltage sensor domain movement, S4 in particular, is modulated by the gating charge response to changes in voltage and is initially stabilized by the lipid headgroups. We show this response is directly coupled to the initial stages of pore domain motion. Results presented here provide a molecular model for how the pre-gating process occurs in sequential steps: Gating charge response, movement and stabilization of the S4 voltage sensor domain, and movement near the base of the S5 region to close the pore domain.

A general profile for the MerR family of transcriptional regulators constructed using the semi-automated Provalidator tool

Provalidator is a web-based tool that facilitates the design and validation of generalized profiles of protein families in prokaryotes. This tool combines the nearly full automation of profile building with a search for family members in all available databases. The tool is useful for assigning a given protein to a specific family, and is also useful for genome mining in annotated prokaryotic genomes. The tool is freely available at http://www.bactregulators.org. As proof of concept we constructed a profile that best defines the MerR family of transcriptional regulators. The profile created includes functional residues that are part of the helix-turn-helix DNA binding domain and accessory elements defined as wings 1 and 2, suggesting that members of the MerR family of regulators may exhibit conserved 3D structure in the region that defines the family profile. The profile defined for MerR was used to search for members of this family in the Swiss-Prot and TrEMBL databases, and also to identify members of the family in the genome of Pseudomonas putida. One of these identified regulators was found to be involved in zinc tolerance, showing the usefulness of identifying family members and assigning phenotypes.

Unifying mechanical and thermodynamic descriptions across the thioredoxin protein family

We compare various predicted mechanical and thermodynamic properties of nine oxidized thioredoxins (TRX) using a Distance Constraint Model (DCM). The DCM is based on a nonadditive free energy decomposition scheme, where entropic contributions are determined from rigidity and flexibility of structure based on distance constraints. We perform averages over an ensemble of constraint topologies to calculate several thermodynamic and mechanical response functions that together yield quantitative stability/flexibility relationships (QSFR). Applied to the TRX protein family, QSFR metrics display a rich variety of similarities and differences. In particular, backbone flexibility is well conserved across the family, whereas cooperativity correlation describing mechanical and thermodynamic couplings between the residue pairs exhibit distinctive features that readily standout. The diversity in predicted QSFR metrics that describe cooperativity correlation between pairs of residues is largely explained by a global flexibility order parameter describing the amount of intrinsic flexibility within the protein. A free energy landscape is calculated as a function of the flexibility order parameter, and key values are determined where the native-state, transition-state, and unfolded-state are located. Another key value identifies a mechanical transition where the global nature of the protein changes from flexible to rigid. The key values of the flexibility order parameter help characterize how mechanical and thermodynamic response is linked. Variation in QSFR metrics and key characteristics of global flexibility are related to the native state X-ray crystal structure primarily through the hydrogen bond network. Furthermore, comparison of three TRX redox pairs reveals differences in thermodynamic response (i.e., relative melting point) and mechanical properties (i.e., backbone flexibility and cooperativity correlation) that are consistent with experimental data on thermal stabilities and NMR dynamical profiles. The results taken together demonstrate that small-scale structural variations are amplified into discernible global differences by propagating mechanical couplings through the H-bond network.