The crystal structure of glutamine-binding protein from Escherichia coli

Conformation-Dependent Hydrogen-Bonding Interactions in a Switchable Artificial Metalloprotein

Hydrogen-bonding (H-bonding) interactions in metalloprotein active sites can critically regulate enzyme function. Changes in the protein structure triggered by interplay with substrates, products, and partner proteins are often translated to the metallocofactor by way of specific changes in H-bond networks connected to the active site. However, the complexities of metalloprotein architecture and mechanism often preclude our ability to define the precise molecular interactions giving rise to these intricate regulatory pathways. To address this shortcoming, we have developed conformationally switchable artificial metalloproteins (swArMs) in which allosteric Gln-binding triggers protein conformational changes that impact the microenvironment surrounding an installed metallocofactor. Herein, we report a combined structural, spectroscopic, and computational approach to enhance the conformation-dependent changes in H-bond interactions surrounding the metallocofactor site of a swArM. Structure-informed molecular dynamics simulations were employed to predict point mutations that could enhance active site H-bond interactions preferentially in the Gln-bound holo-conformation of the swArM. Testing our predictions via the unique infrared spectral signals associated with the metallocofactor site, we have identified three key residues capable of imparting conformational control over the metallocofactor microenvironment. The resultant swArMs not only model biologically relevant structural regulation but also provide an enhanced Gln-responsive biological probe to be leveraged in future biosensing applications.

Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.

Modeling Flexible Protein Structure With AlphaFold2 and Crosslinking Mass Spectrometry

We propose a pipeline that combines AlphaFold2 (AF2) and crosslinking mass spectrometry (XL-MS) to model the structure of proteins with multiple conformations. The pipeline consists of two main steps: ensemble generation using AF2 and conformer selection using XL-MS data. For conformer selection, we developed two scores-the monolink probability score (MP) and the crosslink probability score (XLP)-both of which are based on residue depth from the protein surface. We benchmarked MP and XLP on a large dataset of decoy protein structures and showed that our scores outperform previously developed scores. We then tested our methodology on three proteins having an open and closed conformation in the Protein Data Bank: Complement component 3 (C3), luciferase, and glutamine-binding periplasmic protein, first generating ensembles using AF2, which were then screened for the open and closed conformations using experimental XL-MS data. In five out of six cases, the most accurate model within the AF2 ensembles-or a conformation within 1 Å of this model-was identified using crosslinks, as assessed through the XLP score. In the remaining case, only the monolinks (assessed through the MP score) successfully identified the open conformation of glutamine-binding periplasmic protein, and these results were further improved by including the "occupancy" of the monolinks. This serves as a compelling proof-of-concept for the effectiveness of monolinks. In contrast, the AF2 assessment score was only able to identify the most accurate conformation in two out of six cases. Our results highlight the complementarity of AF2 with experimental methods like XL-MS, with the MP and XLP scores providing reliable metrics to assess the quality of the predicted models. The MP and XLP scoring functions mentioned above are available at https://gitlab.com/topf-lab/xlms-tools.

Unravelling molecular dynamics in living cells: Fluorescent protein biosensors for cell biology

Genetically encoded, fluorescent protein (FP)-based Förster resonance energy transfer (FRET) biosensors are microscopy imaging tools tailored for the precise monitoring and detection of molecular dynamics within subcellular microenvironments. They are characterised by their ability to provide an outstanding combination of spatial and temporal resolutions in live-cell microscopy. In this review, we begin by tracing back on the historical development of genetically encoded FP labelling for detection in live cells, which lead us to the development of early biosensors and finally to the engineering of single-chain FRET-based biosensors that have become the state-of-the-art today. Ultimately, this review delves into the fundamental principles of FRET and the design strategies underpinning FRET-based biosensors, discusses their diverse applications and addresses the distinct challenges associated with their implementation. We place particular emphasis on single-chain FRET biosensors for the Rho family of guanosine triphosphate hydrolases (GTPases), pointing to their historical role in driving our understanding of the molecular dynamics of this important class of signalling proteins and revealing the intricate relationships and regulatory mechanisms that comprise Rho GTPase biology in living cells.

Revealing Allosteric Mechanism of Amino Acid Binding Proteins from Open to Closed State

Amino acid binding proteins (AABPs) undergo significant conformational closure in the periplasmic space of Gram-negative bacteria, tightly binding specific amino acid substrates and then initiating transmembrane transport of nutrients. Nevertheless, the possible closure mechanisms after substrate binding, especially long-range signaling, remain unknown. Taking three typical AABPs-glutamine binding protein (GlnBP), histidine binding protein (HisJ) and lysine/arginine/ornithine binding protein (LAOBP) in Escherichia coli (E. coli)-as research subjects, a series of theoretical studies including sequence alignment, Gaussian network model (GNM), anisotropic network model (ANM), conventional molecular dynamics (cMD) and neural relational inference molecular dynamics (NRI-MD) simulations were carried out. Sequence alignment showed that GlnBP, HisJ and LAOBP have high structural similarity. According to the results of the GNM and ANM, AABPs' Index Finger and Thumb domains exhibit closed motion tendencies that contribute to substrate capture and stable binding. Based on cMD trajectories, the Index Finger domain, especially the I-Loop region, exhibits high molecular flexibility, with residues 11 and 117 both being potentially key residues for receptor-ligand recognition and initiation of receptor allostery. Finally, the signaling pathway of AABPs' conformational closure was revealed by NRI-MD training and trajectory reconstruction. This work not only provides a complete picture of AABPs' recognition mechanism and possible conformational closure, but also aids subsequent structure-based design of small-molecule oncology drugs.

Domain-wise dissection of thermal stability enhancement in multidomain proteins

Stability is critical for the proper functioning of all proteins. Optimization of protein thermostability is a key step in the development of industrial enzymes and biologics. Herein, we demonstrate that multidomain proteins can be stabilized significantly using domain-based engineering followed by the recombination of the optimized domains. Domain-level analysis of designed protein variants with similar structures but different thermal profiles showed that the independent enhancement of the thermostability of a constituent domain improves the overall stability of the whole multidomain protein. The crystal structure and AlphaFold-predicted model of the designed proteins via domain-recombination provided a molecular explanation for domain-based stepwise stabilization. Our study suggests that domain-based modular engineering can minimize the sequence space for calculations in computational design and experimental errors, thereby offering useful guidance for multidomain protein engineering.

Fluorescent proteins and genetically encoded biosensors

The genetically encoded fluorescent sensors convert chemical and physical signals into light. They are powerful tools for the visualisation of physiological processes in living cells and freely moving animals. The fluorescent protein is the reporter module of a genetically encoded biosensor. In this study, we first review the history of the fluorescent protein in full emission spectra on a structural basis. Then, we discuss the design of the genetically encoded biosensor. Finally, we briefly review several major types of genetically encoded biosensors that are currently widely used based on their design and molecular targets, which may be useful for the future design of fluorescent biosensors.

Protein Function Analysis through Machine Learning

Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function. The applications discussed are protein structure prediction, protein engineering using sequence modifications to achieve stability and druggability characteristics, molecular docking in terms of protein-ligand binding, including allosteric effects, protein-protein interactions and protein-centric drug discovery. To quantify the mechanisms underlying protein function, a holistic approach that takes structure, flexibility, stability, and dynamics into account is required, as these aspects become inseparable through their interdependence. Another key component of protein function is conformational dynamics, which often manifest as protein kinetics. Computational methods that use ML to generate representative conformational ensembles and quantify differences in conformational ensembles important for function are included in this review. Future opportunities are highlighted for each of these topics.

Modeling of protein conformational changes with Rosetta guided by limited experimental data

Conformational changes are an essential component of functional cycles of many proteins, but their characterization often requires an integrative structural biology approach. Here, we introduce and benchmark ConfChangeMover (CCM), a new method built into the widely used macromolecular modeling suite Rosetta that is tailored to model conformational changes in proteins using sparse experimental data. CCM can rotate and translate secondary structural elements and modify their backbone dihedral angles in regions of interest. We benchmarked CCM on soluble and membrane proteins with simulated Cα-Cα distance restraints and sparse experimental double electron-electron resonance (DEER) restraints, respectively. In both benchmarks, CCM outperformed state-of-the-art Rosetta methods, showing that it can model a diverse array of conformational changes. In addition, the Rosetta framework allows a wide variety of experimental data to be integrated with CCM, thus extending its capability beyond DEER restraints. This method will contribute to the biophysical characterization of protein dynamics.

Reversible domain closure modulates GlnBP ligand binding affinity

Glutamine binding protein (GlnBP) is an Escherichia Coli periplasmic binding protein, which binds and carries glutamine to the inner membrane ATP-binding cassette (ABC) transporter. GlnBP binds the ligand with affinity around 0.1μM measured by isothermal titration calorimetry (ITC) and ligand binding stabilizes protein structure shown by its increase in thermodynamic stability. However, the molecular determinant of GlnBP ligand binding is not known. Electrostatic and hydrophobic interaction between GlnBP and glutamine are critical factors. We propose that the freedome of closure movement is also vital for ligand binding. In order to approve this hypothesis, we generate a series of mutants with different linker length that has different magnitude of domain closure. Mutants show different ligand binding affinity, which indicates that the propensity of domain closure determines the ligand binding affinity. Ligand binding triggers gradual ensemble conformational change. Structural changes upon ligand binding are monitored by combination of small angle x-ray scattering (SAXS) and NMR spectroscopy. Detailed structure characterization of GlnBP contributes to a better understanding of ligand binding and provides the structural basis for biosensor design.

Dissecting the Protein Dynamics Coupled Ligand Binding with Kinetic Models and Single-Molecule FRET

Protein-ligand interactions are crucial to many biological processes. Ligand binding and dissociation are the basic steps that allow proteins to function. Protein conformational dynamics have been shown to play important roles in ligand binding and dissociation. However, it is challenging to determine the ligand binding kinetics of dynamic proteins. Here, we undertook comprehensive single-molecule FRET (smFRET) measurements and kinetic model analysis to characterize the conformational dynamics coupled ligand binding of glutamine-binding protein (GlnBP). We showed that hinge and T118A mutations of GlnBP affect its conformational dynamics as well as the ligand binding affinity. Based on smFRET measurements, the kinetic model of ligand-GlnBP interactions was constructed. Using experimentally measured parameters, we solved the rate equations of the model and obtained the undetectable parameters of the model which allowed us to understand the ligand binding kinetics fully. Our results demonstrate that modulation of the conformational dynamics of GlnBP affects the ligand binding and dissociation rates. This study provides insights into the binding kinetics of ligands, which are related to the protein function itself.

Sensory perception in bacterial cyclic diguanylate signal transduction

Cyclic diguanylate (c-di-GMP) signal transduction systems provide bacteria with the ability to sense changing cell status or environmental conditions and then execute suitable physiological and social behaviors in response. In this review, we provide a comprehensive census of the stimuli and receptors that are linked to the modulation of intracellular c-di-GMP. Emerging evidence indicates that c-di-GMP networks sense light, surfaces, energy, redox potential, respiratory electron acceptors, temperature, and structurally diverse biotic and abiotic chemicals. Bioinformatic analysis of sensory domains in diguanylate cyclases and c-di-GMP-specific phosphodiesterases as well as the receptor complexes associated with them reveals that these functions are linked to a diverse repertoire of protein domain families. We describe the principles of stimulus perception learned from studying these modular sensory devices, illustrate how they are assembled in varied combinations with output domains, and summarize a system for classifying these sensor proteins based on their complexity. Biological information processing via c-di-GMP signal transduction not only is fundamental to bacterial survival in dynamic environments but also is being used to engineer gene expression circuitry and synthetic proteins with à la carte biochemical functionalities.

Titratable transmembrane residues and a hydrophobic plug are essential for manganese import via the Bacillus anthracis ABC transporter MntBC-A

All extant life forms require trace transition metals (e.g., Fe^2/3+, Cu^1/2+, and Mn²⁺) to survive. However, as these are environmentally scarce, organisms have evolved sophisticated metal uptake machineries. In bacteria, high-affinity import of transition metals is predominantly mediated by ABC transporters. During bacterial infection, sequestration of metal by the host further limits the availability of these ions, and accordingly, bacterial ABC transporters (importers) of metals are key virulence determinants. However, the structure–function relationships of these metal transporters have not been fully elucidated. Here, we used metal-sensitivity assays, advanced structural modeling, and enzymatic assays to study the ABC transporter MntBC-A, a virulence determinant of the bacterial human pathogen Bacillus anthracis. We find that despite its broad metal-recognition profile, MntBC-A imports only manganese, whereas zinc can function as a high-affinity inhibitor of MntBC-A. Computational analysis shows that the transmembrane metal permeation pathway is lined with six titratable residues that can coordinate the positively charged metal, and mutagenesis studies show that they are essential for manganese transport. Modeling suggests that access to these titratable residues is blocked by a ladder of hydrophobic residues, and ATP-driven conformational changes open and close this hydrophobic seal to permit metal binding and release. The conservation of this arrangement of titratable and hydrophobic residues among ABC transporters of transition metals suggests a common mechanism. These findings advance our understanding of transmembrane metal recognition and permeation and may aid the design and development of novel antibacterial agents.

A methodology for carbamate post-translational modification discovery and its application in Escherichia coli

Carbon dioxide can influence cell phenotypes through the modulation of signalling pathways. CO₂ regulates cellular processes as diverse as metabolism, cellular homeostasis, chemosensing and pathogenesis. This diversity of regulated processes suggests a broadly conserved mechanism for CO₂ interactions with diverse cellular targets. CO₂ is generally unreactive but can interact with neutral amines on protein under normal intracellular conditions to form a carbamate post-translational modification (PTM). We have previously demonstrated the presence of this PTM in a subset of protein produced by the model plant species Arabidopsis thaliana. Here, we describe a detailed methodology for identifying new carbamate PTMs in an extracted soluble proteome under biologically relevant conditions. We apply this methodology to the soluble proteome of the model prokaryote Escherichia coli and identify new carbamate PTMs. The application of this methodology, therefore, supports the hypothesis that the carbamate PTM is both more widespread in biology than previously suspected and may represent a broadly relevant mechanism for CO₂-protein interactions.

Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins

We propose edge expansion parallel cascade selection molecular dynamics (eePaCS-MD) as an efficient adaptive conformational sampling method to investigate the large-amplitude motions of proteins without prior knowledge of the conformational transitions. In this method, multiple independent MD simulations are iteratively conducted from initial structures randomly selected from the vertices of a multi-dimensional principal component subspace. This subspace is defined by an ensemble of protein conformations sampled during previous cycles of eePaCS-MD. The edges and vertices of the conformational subspace are determined by solving the "convex hull problem." The sampling efficiency of eePaCS-MD is achieved by intensively repeating MD simulations from the vertex structures, which increases the probability of rare event occurrence to explore new large-amplitude collective motions. The conformational sampling efficiency of eePaCS-MD was assessed by investigating the open-close transitions of glutamine binding protein, maltose/maltodextrin binding protein, and adenylate kinase and comparing the results to those obtained using related methods. In all cases, the open-close transitions were simulated in ∼10 ns of simulation time or less, offering 1-3 orders of magnitude shorter simulation time compared to conventional MD. Furthermore, we show that the combination of eePaCS-MD and accelerated MD can further enhance conformational sampling efficiency, which reduced the total computational cost of observing the open-close transitions by at most 36%.

Double-Well Ultra-Coarse-Grained Model to Describe Protein Conformational Transitions

The double-well model is usually used to describe the conformational transition between two states of a protein. Since conformational changes usually occur within a relatively large time scale, coarse-grained models are often used to accelerate the dynamic process due to their inexpensive computational cost. In this work, we develop a double-well ultra-coarse-grained (DW-UCG) model to describe the conformational transitions of the adenylate kinase, glutamine-binding protein, and lactoferrin. The coarse-grained simulation results show that the DW-UCG model of adenylate kinase captures the crucial intermediate states in the LID-closing and NMP-closing pathways, reflecting the key secondary structural changes in the conformational transition. A comparison of the different DW-UCG models of adenylate kinase indicates that an appropriate choice of bead resolution could generate the free energy landscape that is comparable to that from the residue-based model. The coarse-grained simulations for the glutamine-binding protein and lactoferrin also demonstrate that the DW-UCG model is valid in reproducing the correct two-state behavior for their functional study, which indicates the potential application of the DW-UCG model in investigating the mechanism of conformational changes of large proteins.

Ligand-bound glutamine binding protein assumes multiple metastable binding sites with different binding affinities

Protein dynamics plays key roles in ligand binding. However, the microscopic description of conformational dynamics-coupled ligand binding remains a challenge. In this study, we integrate molecular dynamics simulations, Markov state model (MSM) analysis and experimental methods to characterize the conformational dynamics of ligand-bound glutamine binding protein (GlnBP). We show that ligand-bound GlnBP has high conformational flexibility and additional metastable binding sites, presenting a more complex energy landscape than the scenario in the absence of ligand. The diverse conformations of GlnBP demonstrate different binding affinities and entail complex transition kinetics, implicating a concerted ligand binding mechanism. Single molecule fluorescence resonance energy transfer measurements and mutagenesis experiments are performed to validate our MSM-derived structure ensemble as well as the binding mechanism. Collectively, our study provides deeper insights into the protein dynamics-coupled ligand binding, revealing an intricate regulatory network underlying the apparent binding affinity.

Zhang, Wu, Feng et al. show that ligand-bound glutamine binding protein assumes multiple metastable binding sites, presenting a more dynamic energy landscape than its ligand-free form. This study provides insights into the ligand-binding mechanisms coupled with protein dynamics that underly the apparent binding affinity.

Single-molecule transport kinetics of a glutamate transporter homolog shows static disorder

Kinetic properties of membrane transporters are typically poorly defined because high-resolution functional assays analogous to single-channel recordings are lacking. Here, we measure single-molecule transport kinetics of a glutamate transporter homolog from Pyrococcus horikoshii, GltPh, using fluorescently labeled periplasmic amino acid binding protein as a fluorescence resonance energy transfer-based sensor. We show that individual transporters can function at rates varying by at least two orders of magnitude that persist for multiple turnovers. A gain-of-function mutant shows increased population of the fast-acting transporters, leading to a 10-fold increase in the mean transport rate. These findings, which are broadly consistent with earlier single-molecule measurements of GltPh conformational dynamics, suggest that GltPh transport is defined by kinetically distinct populations that exhibit long-lasting "molecular memory."

Substrate recognition and ATPase activity of the E. coli cysteine/cystine ABC transporter YecSC-FliY

Sulfur is essential for biological processes such as amino acid biogenesis, iron-sulfur cluster formation, and redox homeostasis. To acquire sulfur-containing compounds from the environment, bacteria have evolved high-affinity uptake systems, predominant among which is the ABC transporter family. Theses membrane-embedded enzymes use the energy of ATP hydrolysis for transmembrane transport of a wide range of biomolecules against concentration gradients. Three distinct bacterial ABC import systems of sulfur-containing compounds have been identified, but the molecular details of their transport mechanism remain poorly characterized. Here we provide results from a biochemical analysis of the purified Escherichia coli YecSC-FliY cysteine/cystine import system. We found that the substrate-binding protein FliY binds l-cystine, l-cysteine, and d-cysteine with micromolar affinities. However, binding of the l- and d-enantiomers induced different conformational changes of FliY, where the l- enantiomer-substrate-binding protein complex interacted more efficiently with the YecSC transporter. YecSC had low basal ATPase activity that was moderately stimulated by apo FliY, more strongly by d-cysteine-bound FliY, and maximally by l-cysteine- or l-cystine-bound FliY. However, at high FliY concentrations, YecSC reached maximal ATPase rates independent of the presence or nature of the substrate. These results suggest that FliY exists in a conformational equilibrium between an open, unliganded form that does not bind to the YecSC transporter and closed, unliganded and closed, liganded forms that bind this transporter with variable affinities but equally stimulate its ATPase activity. These findings differ from previous observations for similar ABC transporters, highlighting the extent of mechanistic diversity in this large protein family.

NMR Analysis of Apo Glutamine-Binding Protein Exposes Challenges in the Study of Interdomain Dynamics

Glutamine-binding protein (GlnBP) displays an apo, "open" and a holo, "closed" crystal form, mutually related by a rigid-body reorientation of its domains. A fundamental question about such large-scale conformational transitions, whether the closed state exists in the absence of ligand, is controversial in the case of GlnBP. NMR observations have indicated no evidence of the closed form, whereas experimentally validated computations have suggested a remarkable ca. 40 % population. Herein, a paramagnetic NMR strategy designed to detect the putative apo-closed species shows that a major population of the latter is highly improbable. Further, NMR residual dipolar couplings collected under three anisotropic conditions do not reveal differential domain alignment and establish that the average solution conformation is satisfied by the apo-open crystal structure. Our results indicate that the computational prediction of large-scale interdomain motions is not trivial and may lead to erroneous conclusions without proper experimental validation.

Structures of the substrate-binding protein YfeA in apo and zinc-reconstituted holo forms

In the structural biology of bacterial substrate-binding proteins (SBPs), a growing number of comparisons between substrate-bound and substrate-free forms of metal atom-binding (cluster A-I) SBPs have revealed minimal structural differences between forms. These observations contrast with SBPs that bind substrates such as amino acids or nucleic acids and may undergo >60° rigid-body rotations. Substrate transfer in these SBPs is described by a Venus flytrap model, although this model may not apply to all SBPs. In this report, structures are presented of substrate-free (apo) and reconstituted substrate-bound (holo) YfeA, a polyspecific cluster A-I SBP from Yersinia pestis. It is demonstrated that an apo cluster A-I SBP can be purified by fractionation when co-expressed with its cognate transporter, adding an alternative strategy to the mutagenesis or biochemical treatment used to generate other apo cluster A-I SBPs. The apo YfeA structure contains 111 disordered protein atoms in a mobile helix located in the flexible carboxy-terminal lobe. Metal binding triggers a 15-fold reduction in the solvent-accessible surface area of the metal-binding site and reordering of the 111 protein atoms in the mobile helix. The flexible lobe undergoes a 13.6° rigid-body rotation that is driven by a spring-hammer metal-binding mechanism. This asymmetric rigid-body rotation may be unique to metal atom-binding SBPs (i.e. clusters A-I, A-II and D-IV).

Local structural motifs in proteins: Detection and characterization of fragments inserted in helices

The global/local fold of protein structures is stabilized by a variety of specific interactions. A primary role in this context is played by hydrogen bonds. In order to identify novel motifs in proteins, we searched Protein Data Bank structures looking for backbone H-bonds formed by NH groups of two (or more) consecutive residues with consecutive CO groups of distant residues in the sequence. The present analysis unravels the occurrence of recurrent structural motifs that, to the best of our knowledge, had not been characterized in literature. Indeed, these H-bonding patterns are found (i) in a specific parallel β-sheet capping, (ii) in linking of β-hairpins to α-helices, and (iii) in α-helix insertions. Interestingly, structural analyses of these motifs indicate that Gly residues frequently occupy prominent positions. The formation of these motifs is likely favored by the limited propensity of Gly to be embodied in helices/sheets. Of particular interest is the motif corresponding to insertions in helices that was detected in 1% of analyzed structures. Inserted fragments may assume different structures and aminoacid compositions and usually display diversified evolutionary conservation. Since inserted regions are physically separated from the rest of the protein structure, they represent hot spots for ad-hoc protein functionalization.

Gtr/Ego-independent TORC1 activation is achieved through a glutamine-sensitive interaction with Pib2 on the vacuolar membrane

TORC1 is a central regulator of cell growth in response to amino acids. The role of the evolutionarily conserved Gtr/Rag pathway in the regulation of TORC1 is well-established. Recent genetic studies suggest that an additional regulatory pathway, depending on the activity of Pib2, plays a role in TORC1 activation independently of the Gtr/Rag pathway. However, the interplay between the Pib2 pathway and the Gtr/Rag pathway remains unclear. In this study, we show that Pib2 and Gtr/Ego form distinct complexes with TORC1 in a mutually exclusive manner, implying dedicated functional relationships between TORC1 and Pib2 or Gtr/Rag in response to specific amino acids. Furthermore, simultaneous depletion of Pib2 and the Gtr/Ego system abolishes TORC1 activity and completely compromises the vacuolar localization of TORC1. Thus, the amino acid-dependent activation of TORC1 is achieved through the Pib2 and Gtr/Ego pathways alone. Finally, we show that glutamine induces a dose-dependent increase in Pib2-TORC1 complex formation, and that glutamine binds directly to the Pib2 complex. These data provide strong preliminary evidence for Pib2 functioning as a putative glutamine sensor in the regulation of TORC1.

TORC1 is a central regulator of cell growth in response to amino acids. The evolutionarily conserved Gtr/Rag pathway is a well-established TORC1 regulatory pathway. In this study, we show that two molecular machineries, Pib2 and Gtr/Ego, form distinct complexes with TORC1 in a mutually exclusive manner, implying an exclusive functional relationship between TORC1 and Pib2 or Gtr/Rag in response to various amino acids. We also show that the amino acid-dependent activation of TORC1 is achieved through the Pib2 and Gtr/Ego pathways by anchoring them to the vacuolar membrane. Finally, we show that glutamine binds directly to the Pib2 complex and that glutamine enhances Pib2-TORC1 complex formation. Collectively we provide evidence supporting a role for Pib2 as an element of a putative glutamine sensor.

Sterically Shielded, Stabilized Nitrile Imine for Rapid Bioorthogonal Protein Labeling in Live Cells

In pursuit of fast bioorthogonal reactions, reactive moieties have been increasingly employed for selective labeling of biomolecules in living systems, posing a challenge in attaining reactivity without sacrificing selectivity. To address this challenge, here we report a bioinspired strategy in which molecular shape controls the selectivity of a transient, highly reactive nitrile imine dipole. By tuning the shape of structural pendants attached to the ortho position of the N-aryl ring of diaryltetrazoles-precursors of nitrile imines, we discovered a sterically shielded nitrile imine that favors the 1,3-dipolar cycloaddition over the competing nucleophilic addition. The photogenerated nitrile imine exhibits an extraordinarily long half-life of 102 s in aqueous medium, owing to its unique molecular shape that hinders the approach of a nucleophile as shown by DFT calculations. The utility of this sterically shielded nitrile imine in rapid (∼1 min) bioorthogonal labeling of glucagon receptor in live mammalian cells was demonstrated.

Modeling Protein Excited-state Structures from "Over-length" Chemical Cross-links

Chemical cross-linking coupled with mass spectroscopy (CXMS) provides proximity information for the cross-linked residues and is used increasingly for modeling protein structures. However, experimentally identified cross-links are sometimes incompatible with the known structure of a protein, as the distance calculated between the cross-linked residues far exceeds the maximum length of the cross-linker. The discrepancies may persist even after eliminating potentially false cross-links and excluding intermolecular ones. Thus the "over-length" cross-links may arise from alternative excited-state conformation of the protein. Here we present a method and associated software DynaXL for visualizing the ensemble structures of multidomain proteins based on intramolecular cross-links identified by mass spectrometry with high confidence. Representing the cross-linkers and cross-linking reactions explicitly, we show that the protein excited-state structure can be modeled with as few as two over-length cross-links. We demonstrate the generality of our method with three systems: calmodulin, enzyme I, and glutamine-binding protein, and we show that these proteins alternate between different conformations for interacting with other proteins and ligands. Taken together, the over-length chemical cross-links contain valuable information about protein dynamics, and our findings here illustrate the relationship between dynamic domain movement and protein function.

Mechanism of Action of ABC Importers: Conservation, Divergence, and Physiological Adaptations

The past decade has seen a remarkable surge in structural characterization of ATP binding cassette (ABC) transporters, which have spurred a more focused functional analysis of these elaborate molecular machines. As a result, it has become increasingly apparent that there is a substantial degree of mechanistic variation between ABC transporters that function as importers, which correlates with their physiological roles. Here, we summarize recent advances in ABC importers' structure-function studies and provide an explanation as to the origin of the different mechanisms of action.

Poly-γ-glutamic acid coupled Pseudomonas putida cells surface-displaying metallothioneins: composited copper(ii) biosorption and inducible flocculation in aqueous solution

Schematic illustration of the preparation, biosorption, and induced flocculation of the biocomposite MB546-PGA.

An efficient perturbation method to predict the functionally key sites of glutamine binding protein

Glutamine-Binding Protein (GlnBP) of Escherichia coli, an important member of the periplasmic binding protein family, is responsible for the first step in the active transport of glutamine across the cytoplasmic membrane. In this work, the functionally key regulation sites of GlnBP were identified by utilizing a perturbation method proposed by our group, in which the residues whose perturbations markedly change the binding free energy between GlnBP and glutamine are considered to be functionally key residues. The results show that besides the substrate binding sites, some other residues distant from the binding pocket, including the ones in the hinge regions between the two domains, the front- and back- door channels and the exposed region, are important for the function of glutamine binding and transport. The predicted results are well consistent with the theoretical and experimental data, which indicates that our method is an effective approach to identify the key residues important for both ligand binding and long-range allosteric signal transmission. This work can provide some insights into the function performance of GlnBP and the physical mechanism of its allosteric regulation.

Simple, yet powerful methodologies for conformational sampling of proteins

Several biological functions, such as molecular recognition, enzyme catalysis, signal transduction, allosteric regulation, and protein folding, are strongly related to conformational transitions of proteins. These conformational transitions are generally induced as slow dynamics upon collective motions, including biologically relevant large-amplitude fluctuations of proteins. Although molecular dynamics (MD) simulation has become a powerful tool for extracting conformational transitions of proteins, it might still be difficult to reach time scales of the biological functions because the accessible time scales of MD simulations are far from biological time scales, even if straightforward conventional MD (CMD) simulations using massively parallel computers are employed. Thus, it is desirable to develop efficient methods to achieve canonical ensembles with low computational costs. From this perspective, we review several enhanced conformational sampling techniques of biomolecules developed by us. In our methods, multiple independent short-time MD simulations are employed instead of single straightforward long-time CMD simulations. Our basic strategy is as follows: (i) selection of initial seeds (initial structures) for the conformational sampling in restarting MD simulations. Here, the seeds should be selected as candidates with high potential to transit. (ii) Resampling from the selected seeds by initializing velocities in restarting short-time MD simulations. A cycle of these simple protocols might drastically promote the conformational transitions of biomolecules. (iii) Once reactive trajectories extracted from the cycles of short-time MD simulations are obtained, a free energy profile is evaluated by means of umbrella sampling (US) techniques with the weighted histogram analysis method (WHAM) as a post-processing technique. For the selection of the initial seeds, we proposed four different choices: (1) Parallel CaScade molecular dynamics (PaCS-MD), (2) Fluctuation Flooding Method (FFM), (3) Outlier FLOODing (OFLOOD) method, and (4) TaBoo SeArch (TBSA) method. We demonstrate applications of our methods to several biological systems, such as domain motions of proteins with large-amplitude fluctuations, conformational transitions upon ligand binding, and protein folding/refolding to native structures of proteins. Finally, we show the conformational sampling efficiencies of our methods compared with those by CMD simulations and other previously developed enhanced conformational sampling methods.

Toward an Enhanced Sampling Molecular Dynamics Method for Studying Ligand-Induced Conformational Changes in Proteins

Current enhanced sampling molecular dynamics methods for studying large conformational changes in proteins suffer from certain limitations. These include, among others, the need for user defined collective variables, the prerequisite of both start and end point structures of the conformational change, and the need for a priori knowledge of the amount by which to boost specific parts of the potential. In this paper, a framework is proposed for a molecular dynamics method for studying ligand-induced conformational changes, in which the nonbonded interactions between the ligand and the protein are used to calculate a biasing force. The method requires only a single input structure, and does not entail the use of collective variables. We provide a proof-of-concept for accelerating conformational changes in three simple test molecules, as well as promising results for two proteins known to undergo domain closure upon ligand binding. For the ribose-binding protein, backbone root-mean-square deviations as low as 0.75 Å compared to the crystal structure of the closed conformation are obtained within 50 ns simulations, whereas no domain closures are observed in unbiased simulations. A skewed closed structure is obtained for the glutamine-binding protein at high bias values, indicating that specific protein-ligand interactions might suppress important protein-protein interactions.

PDB-Explorer: a web-based interactive map of the protein data bank in shape space

Background

The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited.

Methods

A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space.

Results

The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups.

Conclusion

A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.cheminfo.org/pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.

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Graphical abstract

Nontargeted Parallel Cascade Selection Molecular Dynamics for Enhancing the Conformational Sampling of Proteins

Nontargeted parallel cascade selection molecular dynamics (nt-PaCS-MD) is proposed as an efficient conformational sampling method to enhance the conformational transitions of proteins, which is an extension of the original targeted PaCS-MD (t-PaCS-MD). The original PaCS-MD comprises cycles of (i) selection of initial structures for multiple independent MD simulations toward a predetermined target and (ii) conformational sampling by the independent MDs. In nt-PaCS-MD, structures that significantly deviate from an average are regarded as candidates that have high potential to address other metastable states and are chosen as the initial structures in the selection. To select significantly deviated structures, we examine the root-mean-square deviation (RMSD) of snapshots generated from the average structure based on Gram-Schmidt orthogonalization. nt-PaCS-MD was applied to the folding of the mini-protein chignolin in implicit solvent and to the open-closed conformational transitions of T4 lysozyme (T4L) and glutamine binding protein (QBP) in explicit solvent. We show that nt-PaCS-MD can reach chignolin's native state and can also cause the open-closed transition of T4L and QBP on a nanosecond time scale, which are very efficient in terms of conformational sampling and comparable to that with t-PaCS-MD.

Catabolism of Amino Acids and Related Compounds

This review considers the pathways for the degradation of amino acids and a few related compounds (agmatine, putrescine, ornithine, and aminobutyrate), along with their functions and regulation. Nitrogen limitation and an acidic environment are two physiological cues that regulate expression of several amino acid catabolic genes. The review considers Escherichia coli, Salmonella enterica serovar Typhimurium, and Klebsiella species. The latter is included because the pathways in Klebsiella species have often been thoroughly characterized and also because of interesting differences in pathway regulation. These organisms can essentially degrade all the protein amino acids, except for the three branched-chain amino acids. E. coli, Salmonella enterica serovar Typhimurium, and Klebsiella aerogenes can assimilate nitrogen from D- and L-alanine, arginine, asparagine, aspartate, glutamate, glutamine, glycine, proline, and D- and L-serine. There are species differences in the utilization of agmatine, citrulline, cysteine, histidine, the aromatic amino acids, and polyamines (putrescine and spermidine). Regardless of the pathway of glutamate synthesis, nitrogen source catabolism must generate ammonia for glutamine synthesis. Loss of glutamate synthase (glutamineoxoglutarate amidotransferase, or GOGAT) prevents utilization of many organic nitrogen sources. Mutations that create or increase a requirement for ammonia also prevent utilization of most organic nitrogen sources.

Structure of a Bacterial ABC Transporter Involved in the Import of an Acidic Polysaccharide Alginate

The acidic polysaccharide alginate represents a promising marine biomass for the microbial production of biofuels, although the molecular and structural characteristics of alginate transporters remain to be clarified. In Sphingomonas sp. A1, the ATP-binding cassette transporter AlgM1M2SS is responsible for the import of alginate across the cytoplasmic membrane. Here, we present the substrate-transport characteristics and quaternary structure of AlgM1M2SS. The addition of poly- or oligoalginate enhanced the ATPase activity of reconstituted AlgM1M2SS coupled with one of the periplasmic solute-binding proteins, AlgQ1 or AlgQ2. External fluorescence-labeled oligoalginates were specifically imported into AlgM1M2SS-containing proteoliposomes in the presence of AlgQ2, ATP, and Mg(2+). The crystal structure of AlgQ2-bound AlgM1M2SS adopts an inward-facing conformation. The interaction between AlgQ2 and AlgM1M2SS induces the formation of an alginate-binding tunnel-like structure accessible to the solvent. The translocation route inside the transmembrane domains contains charged residues suitable for the import of acidic saccharides.

TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits

TEMPy is an object-oriented Python library that provides the means to validate density fits in electron microscopy reconstructions. This article highlights several features of particular interest for this purpose and includes some customized examples.

Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists.

Retour aux sources: defining the structural basis of glutamate receptor activation

Ionotropic glutamate receptors (iGluRs) are the major excitatory neurotransmitter receptor in the vertebrate CNS and, as a result, their activation properties lie at the heart of much of the neuronal network activity observed in the developing and adult brain. iGluRs have also been implicated in many nervous system disorders associated with postnatal development (e.g. autism, schizophrenia), cerebral insult (e.g. stroke, epilepsy), and disorders of the ageing brain (e.g. Alzheimer's disease, Parkinsonism). In view of this, an emphasis has been placed on understanding how iGluRs activate and desensitize in functional and structural terms. Early structural models of iGluRs suggested that the strength of the agonist response was primarily governed by the degree of closure induced in the ligand-binding domain (LBD). However, recent studies have suggested a more nuanced role for the LBD with current evidence identifying the iGluR LBD interface as a "hotspot" regulating agonist behaviour. Such ideas remain to be consolidated with recently solved structures of full-length iGluRs to account for the global changes that underlie channel activation and desensitization.

Exploring multi-dimensional coordinate-dependent diffusion dynamics on the energy landscape of protein conformation change

We explore the multi-dimensional diffusion dynamics of protein conformational change. We found in general that the diffusion is anisotropic and inhomogeneous. The directional and positional dependence of diffusion have significant impacts on the protein conformational kinetics: the dominant kinetic path of conformational change is shifted from the naively expected steepest decent gradient paths. The kinetic transition state is shifted away from the transition state. The effective kinetic free energy barrier height, determining the kinetic rate of the conformational change, is shifted away from the one estimated from the thermodynamic free energy barrier. The shift of the transition state in position and value will modify the phi value analysis for identification of hot residues and interactions responsible for conformational dynamics. Ongoing and future experiments can test the predictions of the model.

Coevolutionary signals across protein lineages help capture multiple protein conformations

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

Nitrogen assimilation in Escherichia coli: putting molecular data into a systems perspective

We present a comprehensive overview of the hierarchical network of intracellular processes revolving around central nitrogen metabolism in Escherichia coli. The hierarchy intertwines transport, metabolism, signaling leading to posttranslational modification, and transcription. The protein components of the network include an ammonium transporter (AmtB), a glutamine transporter (GlnHPQ), two ammonium assimilation pathways (glutamine synthetase [GS]-glutamate synthase [glutamine 2-oxoglutarate amidotransferase {GOGAT}] and glutamate dehydrogenase [GDH]), the two bifunctional enzymes adenylyl transferase/adenylyl-removing enzyme (ATase) and uridylyl transferase/uridylyl-removing enzyme (UTase), the two trimeric signal transduction proteins (GlnB and GlnK), the two-component regulatory system composed of the histidine protein kinase nitrogen regulator II (NRII) and the response nitrogen regulator I (NRI), three global transcriptional regulators called nitrogen assimilation control (Nac) protein, leucine-responsive regulatory protein (Lrp), and cyclic AMP (cAMP) receptor protein (Crp), the glutaminases, and the nitrogen-phosphotransferase system. First, the structural and molecular knowledge on these proteins is reviewed. Thereafter, the activities of the components as they engage together in transport, metabolism, signal transduction, and transcription and their regulation are discussed. Next, old and new molecular data and physiological data are put into a common perspective on integral cellular functioning, especially with the aim of resolving counterintuitive or paradoxical processes featured in nitrogen assimilation. Finally, we articulate what still remains to be discovered and what general lessons can be learned from the vast amounts of data that are available now.