Allosteric communication in cysteinyl tRNA synthetase: a network of direct and indirect readout

Elucidating the Ionic Liquid-Induced Mixed Inhibition of GH1 β-Glucosidase H0HC94

Deciphering the ionic liquid (IL) tolerance of glycoside hydrolases (GHs) to improve their hydrolysis efficiency for fermentable sugar synthesis in the "one-pot" process has long been a hurdle for researchers. In this work, we employed experimental and theoretical approaches to investigate the 1-ethyl-3-methylimidazolium acetate ([C2C1im][MeCO2])-induced inhibition of GH1 β-glucosidase (H0HC94) from Agrobacterium tumefaciens 5A. At 10-15% [C2C1im][MeCO2] concentration, H0HC94 experiences competitive inhibition (R2 = 0.97, alpha = 2.8). As the IL content increased to 20-25%, the inhibition pattern shifted to mixed-type inhibition (R2 = 0.98, alpha = 3.4). These findings were further confirmed through characteristic inhibition plots using Lineweaver-Burk plots. Atomistic molecular dynamics simulations conducted with 0% [C2C1im][MeCO2], 10% [C2C1im][MeCO2], and 25% [C2C1im][MeCO2] revealed the accumulation of [C2C1im]+ at the negatively charged active site of H0HC94 in 10% [C2C1im][MeCO2], supporting the occurrence of competitive inhibition at lower IL concentrations. At higher IL concentrations, the cations and anions bound to the secondary binding sites (SBSs) of H0HC94, leading to a tertiary conformational change, as captured by the principal component analysis based on the free-energy landscape and protein structure networks. The altered conformation of H0HC94 affected the interaction with [C2C1im][MeCO2], which could possibly shift the inhibition from competitive to more mixed-type (competitive + noncompetitive) inhibition, as observed in the experiments. For the first time, we report a combined experimental and theoretical insight behind the mixed inhibition of a GH1 β-glucosidase. Our findings indicated the role of SBS in IL-induced inhibition, which could aid in developing more IL-tolerant β-glucosidases for biorefinery applications.

Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase

Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.

The tRNA identity landscape for aminoacylation and beyond

tRNAs are key partners in ribosome-dependent protein synthesis. This process is highly dependent on the fidelity of tRNA aminoacylation by aminoacyl-tRNA synthetases and relies primarily on sets of identities within tRNA molecules composed of determinants and antideterminants preventing mischarging by non-cognate synthetases. Such identity sets were discovered in the tRNAs of a few model organisms, and their properties were generalized as universal identity rules. Since then, the panel of identity elements governing the accuracy of tRNA aminoacylation has expanded considerably, but the increasing number of reported functional idiosyncrasies has led to some confusion. In parallel, the description of other processes involving tRNAs, often well beyond aminoacylation, has progressed considerably, greatly expanding their interactome and uncovering multiple novel identities on the same tRNA molecule. This review highlights key findings on the mechanistics and evolution of tRNA and tRNA-like identities. In addition, new methods and their results for searching sets of multiple identities on a single tRNA are discussed. Taken together, this knowledge shows that a comprehensive understanding of the functional role of individual and collective nucleotide identity sets in tRNA molecules is needed for medical, biotechnological and other applications.

Role of salt-bridging interactions in recognition of viral RNA by arginine-rich peptides

Interactions between RNA molecules and proteins are critical to many cellular processes and are implicated in various diseases. The RNA-peptide complexes are good model systems to probe the recognition mechanism of RNA by proteins. In this work, we report studies on the binding-unbinding process of a helical peptide from a viral RNA element using nonequilibrium molecular dynamics simulations. We explored the existence of various dissociation pathways with distinct free-energy profiles that reveal metastable states and distinct barriers to peptide dissociation. We also report the free-energy differences for each of the four pathways to be 96.47 ± 12.63, 96.1 ± 10.95, 91.83 ± 9.81, and 92 ± 11.32 kcal/mol. Based on the free-energy analysis, we further propose the preferred pathway and the mechanism of peptide dissociation. The preferred pathway is characterized by the formation of sequential hydrogen-bonding and salt-bridging interactions between several key arginine amino acids and the viral RNA nucleotides. Specifically, we identified one arginine amino acid (R8) of the peptide to play a significant role in the recognition mechanism of the peptide by the viral RNA molecule.

Role of Conformational Change and Glucose Binding Sites in the Enhanced Glucose Tolerance of Agrobacterium tumefaciens 5A GH1 β-Glucosidase Mutants

β-Glucosidases are often inhibited by their reaction product glucose and a barrier to the efficient lignocellulosic biomass hydrolysis to glucose. We had previously reported the mutants, C174V, and H229S, with a nearly 2-fold increased glucose tolerance over the wild type (WT), H0HC94, encoded in Agrobacterium tumefaciens 5A (apparent K_i,_Glc = 686 mM). We report our steady-state and time-resolved intrinsic fluorescence spectroscopy, circular dichroism, and isothermal titration calorimetry (ITC) studies to further understand increased glucose tolerance. Changes in the mutants' emission intensity and the differential change in quenching rate in the absence and presence of glucose reflect changes in protein conformation by glucose. Time-resolved lifetime and anisotropy measurements further indicated the microenvironment differences across solvent-exposed tryptophan residues and a higher hydrodynamic radius due to glucose binding, respectively. ITC measurements confirmed the increase of glucose binding sites in the mutants. The experiment results were supported by molecular dynamics simulations, which revealed significant variations in the glucose-protein hydrogen-bonding profiles. Protein structure network analysis of the simulated structures further indicates the mutants' conformation change than the WT. Computational studies also indicated additional glucose binding sites in mutants. Our results indicate the role of glucose binding in modulating the enzyme response to glucose.

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.

Electrostatic Switching Controls Channel Dynamics of the Sensor Protein VirB10 in A. tumefaciens Type IV Secretion System

Type IV secretion systems are large nanomachines assembled across the bacterial cell envelope for effector translocation and conjugation. VirB10 traverses the inner and outer membranes, sensing cellular signals for coordinating the conformational switch for pilus biogenesis and/or secretion. Mutations uncoupling secretion from pilus biogenesis were identified in Agrobacterium tumefaciens VirB10 including a gating defect mutation G272R that made VirB10 unresponsive to intracellular ATP, causing unregulated secretion of VirE2 in a contact-independent manner. Comparative long-timescale molecular dynamics of the wild type and G272R mutant of the A. tumefaciens VirB10_CTD tetradecamer reveals how the G272R mutation locks the oligomer in a rigid conformation by swapping the ionic interactions between the loops from the β-barrel close to the inner leaflet of the outer membrane. This electrostatic switching changes the allosteric communication pathway from the extracellular loop to the base of the barrel, suggesting that the local conformational dynamics in the loops can gate information across VirB10.

Anticodon-binding domain swapping in a nondiscriminating aspartyl-tRNA synthetase reveals contributions to tRNA specificity and catalytic activity

The nondiscriminating aspartyl-tRNA synthetase (ND-AspRS), found in many archaea and bacteria, covalently attaches aspartic acid to tRNA^Asp and tRNA^Asn generating a correctly charged Asp-tRNA^Asp and an erroneous Asp-tRNA^Asn . This relaxed tRNA specificity is governed by interactions between the tRNA and the enzyme. In an effort to assess the contributions of the anticodon-binding domain to tRNA specificity, we constructed two chimeric enzymes, Chimera-D and Chimera-N, by replacing the native anticodon-binding domain in the Helicobacter pylori ND-AspRS with that of a discriminating AspRS (Chimera-D) and an asparaginyl-tRNA synthetase (AsnRS, Chimera-N), both from Escherichia coli. Both chimeric enzymes showed similar secondary structure compared to wild-type (WT) ND-AspRS and maintained the ability to form dimeric complexes in solution. Although less catalytically active than WT, Chimera-D was more discriminating as it aspartylated tRNA^Asp over tRNA^Asn with a specificity ratio of 7.0 compared to 2.9 for the WT enzyme. In contrast, Chimera-N exhibited low catalytic activity toward tRNA^Asp and was unable to aspartylate tRNA^Asn . The observed catalytic activities for the two chimeras correlate with their heterologous toxicity when expressed in E. coli. Molecular dynamics simulations show a reduced hydrogen bond network at the interface between the anticodon-binding domain and the catalytic domain in Chimera-N compared to Chimera-D or WT, explaining its lower stability and catalytic activity.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.

Data-driven computational analysis of allosteric proteins by exploring protein dynamics, residue coevolution and residue interaction networks

BACKGROUND

Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks.

METHODS

In this work, we performed a large scale comprehensive and multi-faceted analysis of >300 diverse allosteric proteins and complexes with allosteric modulators. By modeling and exploring coarse-grained dynamics, residue coevolution, and residue interaction networks for allosteric proteins, we have determined unifying molecular signatures shared by allosteric systems.

RESULTS

The results of this study have suggested that allosteric inhibitors and allosteric activators may differentially affect global dynamics and network organization of protein systems, leading to diverse allosteric mechanisms. By using structural and functional data on protein kinases, we present a detailed case study that that included atomic-level analysis of coevolutionary networks in kinases bound with allosteric inhibitors and activators.

CONCLUSIONS

We have found that coevolutionary networks can form direct communication pathways connecting functional regions and can recapitulate key regulatory sites and interactions responsible for allosteric signaling in the studied protein systems. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of known regulatory hotspots in protein kinases.

GENERAL SIGNIFICANCE

This study has shown that allosteric inhibitors and allosteric activators can have a different effect on residue interaction networks and can exploit distinct regulatory mechanisms, which could open up opportunities for probing allostery and new drug combinations with broad range of activities.

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.

Atomistic Modeling of the ABL Kinase Regulation by Allosteric Modulators Using Structural Perturbation Analysis and Community-Based Network Reconstruction of Allosteric Communications

In this work, we have examined the molecular mechanisms of allosteric regulation of the ABL tyrosine kinase at the atomic level. Atomistic modeling of the ABL complexes with a panel of allosteric modulators has been performed using a combination of molecular dynamics simulations, structural residue perturbation scanning, and a novel community analysis of the residue interaction networks. Our results have indicated that allosteric inhibitors and activators may exert a differential control on allosteric signaling between the kinase binding sites and functional regions. While the inhibitor binding can strengthen the closed ABL state and induce allosteric communications directed from the allosteric pocket to the ATP binding site, the DPH activator may induce a more dynamic open form and activate allosteric couplings between the ATP and substrate binding sites. By leveraging a network-centric theoretical framework, we have introduced a novel community analysis method and global topological parameters that have unveiled the hierarchical modularity and the intercommunity bridging sites in the residue interaction network. We have found that allosteric functional hotspots responsible for the kinase regulation may serve the intermodular bridges in the global interaction network. The central conclusion from this analysis is that the regulatory switch centers play a fundamental role in the modular network organization of ABL as the unique intercommunity bridges that connect the SH2 and SH3 domains with the catalytic core into a functional kinase assembly. The hierarchy of network organization in the ABL regulatory complexes may allow for the synergistic action of dense intercommunity links required for the robust signal transfer in the catalytic core and sparse network bridges acting as the regulatory control points that orchestrate allosteric transitions between the inhibited and active kinase forms.

Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications

Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein–DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.

Structure-function studies of the asparaginyl-tRNA synthetase from Fasciola gigantica: understanding the role of catalytic and non-catalytic domains

The asparaginyl-tRNA synthetase (NRS) catalyzes the attachment of asparagine to its cognate tRNA during translation. NRS first catalyzes the binding of Asn and ATP to form the NRS-asparaginyl adenylate complex, followed by the esterification of Asn to its tRNA. We investigated the role of constituent domains in regulating the structure and activity of Fasciola gigantica NRS (FgNRS). We cloned the full-length FgNRS, along with its various truncated forms, expressed, and purified the corresponding proteins. Size exclusion chromatography indicated a role of the anticodon-binding domain (ABD) of FgNRS in protein dimerization. The N-terminal domain (NTD) was not essential for cognate tRNA binding, and the hinge region between the ABD and the C-terminal domain (CTD) was crucial for regulating the enzymatic activity. Molecular docking and fluorescence quenching experiments elucidated the binding affinities of the substrates to various domains. The molecular dynamics simulation of the modeled protein showed the presence of an unstructured region between the NTD and ABD that exhibited a large number of conformations over time, and further analysis indicated this region to be intrinsically disordered. The present study provides information on the structural and functional regulation, protein-substrate(s) interactions and dynamics, and the role of non-catalytic domains in regulating the activity of FgNRS.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Aminoacyl-tRNA synthetases: Structure, function, and drug discovery

Aminoacyl-tRNA synthetases (AARSs) are the enzymes that catalyze the aminoacylation reaction by covalently linking an amino acid to its cognate tRNA in the first step of protein translation. Beyond this classical function, these enzymes are also known to have a role in several metabolic and signaling pathways that are important for cell viability. Study of these enzymes is of great interest to the researchers due to its pivotal role in the growth and survival of an organism. Further, unfolding the interesting structural and functional aspects of these enzymes in the last few years has qualified them as a potential drug target against various diseases. Here we review the classification, function, and the conserved as well the appended structural architecture of these enzymes in detail, including its association with multi-synthetase complexes. We also considered their role in human diseases in terms of mutations and autoantibodies against AARSs. Finally, we have discussed the available inhibitors against AARSs. This review offers comprehensive information on AARSs under a single canopy that would be a good inventory for researchers working in this area.

Soluble expression and purification of a full-length asparaginyl tRNA synthetase from Fasciola gigantica

We report the molecular cloning, expression, and single-step homogeneous purification of a full-length asparaginyl tRNA synthetase (NRS) from Fasciola gigantica (FgNRS). Fasciola gigantica is a parasitic liver fluke of the class Trematoda. It causes fascioliasis that infects the liver of various mammals, including humans. Aminoacyl tRNA synthetases (AARS) catalyze the first step of protein synthesis. They attach an amino acid to its cognate tRNA, forming an amino acid-tRNA complex. The gene that codes for FgNRS was generated by amplification by polymerase chain reaction. It was then inserted in the expression vector pQE30 under the transcriptional control of the bacteriophage T5 promoter and lac operator. M15 Escherichia coli strain transformed with the FgNRS expression vector pQE30-NRS accumulates large amounts of a soluble protein of about 61 kDa. The protein was purified to homogeneity using immobilized metal affinity chromatography. The recombinant protein was further confirmed by immunoblotting with anti-His antibody. Following size exclusion chromatography, the FgNRS was stable and observed to be a dimeric protein. In this study, the expression and purification procedures have provided a simple and efficient method to obtain full-length FgNRS in large quantities. This will provide an opportunity to study the structure, dynamics and function of NRS.

Specific DNA sequences allosterically enhance protein-protein interaction in a transcription factor through modulation of protein dynamics: implications for specificity of gene regulation

Most genes are regulated by multiple transcription factors, often assembling into multi-protein complexes in the gene regulatory region. Understanding of the molecular origin of specificity of gene regulatory complex formation in the context of the whole genome is currently inadequate. A phage transcription factor λ-CI forms repressive multi-protein complexes by binding to multiple binding sites in the genome to regulate the lifecycle of the phage. The protein-protein interaction between two DNA-bound λ-CI molecules is stronger when they are bound to the correct pair of binding sites, suggesting allosteric transmission of recognition of correct DNA sequences to the protein-protein interaction interface. Exploration of conformation and dynamics by time-resolved fluorescence anisotropy decay and molecular dynamics suggests a change in protein dynamics to be a crucial factor in mediating allostery. A lattice-based model suggests that DNA-sequence induced allosteric effects could be crucial underlying factors in differentially stabilizing the correct site-specific gene regulatory complexes. We conclude that transcription factors have evolved multiple mechanisms to augment the specificity of DNA-protein interactions in order to achieve an extraordinarily high degree of spatial and temporal specificities of gene regulatory complexes, and DNA-sequence induced allostery plays an important role in the formation of sequence-specific gene regulatory complexes.

Competition for amino acid flux among translation, growth and detoxification in bacteria

Transfer-tRNAs (tRNAs) are central entities for translation that deliver amino acids to the ribosome to translate genetic information in an mRNA-template dependent manner. Recent discoveries from our laboratory show that in E. coli and B. licheniformis, some tRNAs are poorly charged despite the plentiful intracellular cognate amino acid. Specifically, tRNAs carrying amino acids that exert toxicity and inhibit bacterial growth when added separately to the growth medium are poorly charged. Here, we discuss various evolutionary strategies different bacterial cells have adopted to precisely hone the competition between amino acid utilization for translation and proliferation and combat the inhibitory effect toward maximizing bacterial fitness. These data add a new twist to the amino acid flux models and to our understanding of the complex intimate link between dynamics of translation and bacterial growth.

Uncoupling of an ammonia channel as a mechanism of allosteric inhibition in anthranilate synthase of Serratia marcescens: dynamic and graph theoretical analysis

Network modeling and molecular dynamic studies reveal the perturbation in communication pathways as a mechanism of allosteric inhibition in anthranilate synthase.

Computational approaches to investigating allostery

Allosteric regulation plays a key role in many biological processes, such as signal transduction, transcriptional regulation, and many more. It is rooted in fundamental thermodynamic and dynamic properties of macromolecular systems that are still poorly understood and are moreover modulated by the cellular context. Here we review the computational approaches used in the investigation of allosteric processes in protein systems. We outline how the models of allostery have evolved from their initial formulation in the sixties to the current views, which more fully account for the roles of the thermodynamic and dynamic properties of the system. We then describe the major classes of computational approaches employed to elucidate the mechanisms of allostery, the insights they have provided, as well as their limitations. We complement this analysis by highlighting the role of computational approaches in promising practical applications, such as the engineering of regulatory modules and identifying allosteric binding sites.

Dynamic Allostery Mediated by a Conserved Tryptophan in the Tec Family Kinases

Bruton’s tyrosine kinase (Btk) is a Tec family non-receptor tyrosine kinase that plays a critical role in immune signaling and is associated with the immunological disorder X-linked agammaglobulinemia (XLA). Our previous findings showed that the Tec kinases are allosterically activated by the adjacent N-terminal linker. A single tryptophan residue in the N-terminal 17-residue linker mediates allosteric activation, and its mutation to alanine leads to the complete loss of activity. Guided by hydrogen/deuterium exchange mass spectrometry results, we have employed Molecular Dynamics simulations, Principal Component Analysis, Community Analysis and measures of node centrality to understand the details of how a single tryptophan mediates allostery in Btk. A specific tryptophan side chain rotamer promotes the functional dynamic allostery by inducing coordinated motions that spread across the kinase domain. Either a shift in the rotamer population, or a loss of the tryptophan side chain by mutation, drastically changes the coordinated motions and dynamically isolates catalytically important regions of the kinase domain. This work also identifies a new set of residues in the Btk kinase domain with high node centrality values indicating their importance in transmission of dynamics essential for kinase activation. Structurally, these node residues appear in both lobes of the kinase domain. In the N-lobe, high centrality residues wrap around the ATP binding pocket connecting previously described Catalytic-spine residues. In the C-lobe, two high centrality node residues connect the base of the R- and C-spines on the αF-helix. We suggest that the bridging residues that connect the catalytic and regulatory architecture within the kinase domain may be a crucial element in transmitting information about regulatory spine assembly to the catalytic machinery of the catalytic spine and active site.

Bruton’s tyrosine kinase (Btk) belongs to the Tec family of protein tyrosine kinases, and plays a crucial role in the signaling pathway in B-cells. Alteration of Btk activity results in the serious immunological disorder, X-linked agammaglobulinemia. Btk is a multi-domain protein and the activity of the kinase domain is regulated by the adjacent non-catalytic domains, which mediate their effect by means of a conserved tryptophan residue. In this work, we have investigated the mechanism of regulation by this tryptophan residue, W395, in the linker preceding the Btk kinase domain. Using hydrogen-deuterium exchange mass spectrometry and molecular dynamics simulations we identify structural elements within the kinase domain that are required for function by transmitting the allosteric effects of W395. Molecular Dynamics simulations further guided us to delineate the kinase domain into dynamically correlated sets of residues using community analysis, thereby identifying the important communication nodes that connect the various elements of the kinase domain required for function. The analyses performed indicate clearly how the W395A mutant changes the communication pathway required for function.

Predicting long term cooperativity and specific modulators of receptor interactions in human transferrin from dynamics within a single microstate

PRS identifies regions contacting rapidly evolving residues that mechanically manipulate dissociation from the pathogen in the human transferrin–bacterial receptor complex.

Molecular dynamics simulations and modelling of the residue interaction networks in the BRAF kinase complexes with small molecule inhibitors: probing the allosteric effects of ligand-induced kinase dimerization and paradoxical activation

The computational analysis of residue interaction networks dissects the allosteric effects of inhibitor-induced BRAF kinase dimerization and paradoxical activation.

(Dis)similarity Index To Compare Correlated Motions in Molecular Simulations

Molecular dynamics (MD) simulations are widely used to complement or guide experimental studies in the characterization of protein dynamics, thanks to improvements in force-field accuracy, along with in the software and hardware to sample the conformational landscape of proteins. Among the different applications of MD simulations, the study of correlated motions is largely employed for different purposes. Several metrics have been developed to describe correlated motions in the MD ensemble, such as methods based on Pearson Correlation or Mutual Information. Cross-correlation analysis of MD trajectories is indeed appealing not only to identify residues characterized by coupled fluctuations in protein structures but also since it can be used to extrapolate motions along directions in which major conformational changes should occur, for example on longer time scales than the ones that are actually simulated. Nevertheless, most of the MD studies employ average correlation maps and mostly in a qualitative way, even when different systems or different replicates of the same system are compared. The broad application of correlation metrics in the analysis of MD simulations, especially for comparative purposes, requires a step forward toward more quantitative and accurate comparisons. We thus here employed a simple but effective index, which is based on a normalized Frobenius norm of the differences between protein correlation maps, to compare correlated motions. We applied this index for a quantitative comparison of correlated motions from MD simulations of seven proteins of different size and fold. We also employed the index to assess the robustness of correlation description when multi-replicate MD simulations of a same system are used, and we compared our index to metrics for comparison of structural ensembles such as Root Mean Square Inner Product and the Bhattacharyya Coefficient.

MD Simulations of tRNA and Aminoacyl-tRNA Synthetases: Dynamics, Folding, Binding, and Allostery

While tRNA and aminoacyl-tRNA synthetases are classes of biomolecules that have been extensively studied for decades, the finer details of how they carry out their fundamental biological functions in protein synthesis remain a challenge. Recent molecular dynamics (MD) simulations are verifying experimental observations and providing new insight that cannot be addressed from experiments alone. Throughout the review, we briefly discuss important historical events to provide a context for how far the field has progressed over the past few decades. We then review the background of tRNA molecules, aminoacyl-tRNA synthetases, and current state of the art MD simulation techniques for those who may be unfamiliar with any of those fields. Recent MD simulations of tRNA dynamics and folding and of aminoacyl-tRNA synthetase dynamics and mechanistic characterizations are discussed. We highlight the recent successes and discuss how important questions can be addressed using current MD simulations techniques. We also outline several natural next steps for computational studies of AARS:tRNA complexes.

What RNA World? Why a Peptide/RNA Partnership Merits Renewed Experimental Attention

We review arguments that biology emerged from a reciprocal partnership in which small ancestral oligopeptides and oligonucleotides initially both contributed rudimentary information coding and catalytic rate accelerations, and that the superior information-bearing qualities of RNA and the superior catalytic potential of proteins emerged from such complexes only with the gradual invention of the genetic code. A coherent structural basis for that scenario was articulated nearly a decade before the demonstration of catalytic RNA. Parallel hierarchical catalytic repertoires for increasingly highly conserved sequences from the two synthetase classes now increase the likelihood that they arose as translation products from opposite strands of a single gene. Sense/antisense coding affords a new bioinformatic metric for phylogenetic relationships much more distant than can be reconstructed from multiple sequence alignments of a single superfamily. Evidence for distinct coding properties in tRNA acceptor stems and anticodons, and experimental demonstration that the two synthetase family ATP binding sites can indeed be coded by opposite strands of the same gene supplement these biochemical and bioinformatic data, establishing a solid basis for key intermediates on a path from simple, stereochemically coded, reciprocally catalytic peptide/RNA complexes through the earliest peptide catalysts to contemporary aminoacyl-tRNA synthetases. That scenario documents a path to increasing complexity that obviates the need for a single polymer to act both catalytically and as an informational molecule.

Small-world networks of residue interactions in the Abl kinase complexes with cancer drugs: topology of allosteric communication pathways can determine drug resistance effects

Computational modelling of efficiency and robustness of the residue interaction networks and allosteric pathways in kinase structures can characterize protein kinase sensitivity to drug binding and drug resistance effects.

Structure-based network analysis of activation mechanisms in the ErbB family of receptor tyrosine kinases: the regulatory spine residues are global mediators of structural stability and allosteric interactions

The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced “superacceptor” activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD) motif in the catalytic loop and the Asp-Phe-Gly (DFG) motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not limited to the ATP site, and may enhance allosteric cooperativity with the substrate binding region by increasing communication capabilities of mediating residues.

Communication routes in ARID domains between distal residues in helix 5 and the DNA-binding loops

ARID is a DNA-binding domain involved in several transcriptional regulatory processes, including cell-cycle regulation and embryonic development. ARID domains are also targets of the Human Cancer Protein Interaction Network. Little is known about the molecular mechanisms related to conformational changes in the family of ARID domains. Thus, we have examined their structural dynamics to enrich the knowledge on this important family of regulatory proteins. In particular, we used an approach that integrates atomistic simulations and methods inspired by graph theory. To relate these properties to protein function we studied both the free and DNA-bound forms. The interaction with DNA not only stabilizes the conformations of the DNA-binding loops, but also strengthens pre-existing paths in the native ARID ensemble for long-range communication to those loops. Residues in helix 5 are identified as critical mediators for intramolecular communication to the DNA-binding regions. In particular, we identified a distal tyrosine that plays a key role in long-range communication to the DNA-binding loops and that is experimentally known to impair DNA-binding. Mutations at this tyrosine and in other residues of helix 5 are also demonstrated, by our approach, to affect the paths of communication to the DNA-binding loops and alter their native dynamics. Overall, our results are in agreement with a scenario in which ARID domains exist as an ensemble of substates, which are shifted by external perturbation, such as the interaction with DNA. Conformational changes at the DNA-binding loops are transmitted long-range by intramolecular paths, which have their heart in helix 5.

Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.

Functional versatility and structural adaptability of the Hsp90 chaperones are regulated by allosteric interactions that allow for diverse functions including modulation of ATP hydrolysis and binding with cochaperones and client proteins. By integrating molecular simulations and network-based approaches we have characterized conformational dynamics and allosteric interactions in different functional forms of Hsp90. The network centrality analysis and structural mapping of allosteric communications have revealed a small-world organization of the interaction network that is mediated by functionally important residues of the Hsp90 activity. We have found that effective allosteric communications in the Hsp90 chaperone may be provided by structurally stable residues that exhibit high centrality properties. Nucleotide-specific rewiring of the network topology and assortative organization of functional residues may protect the active form of the chaperone from random perturbations and detrimental mutations. These results have confirmed that allosteric interactions in the Hsp90 chaperone may be determined by a small-world network of functional residues that can regulate the network efficiency and resiliency by modulating the statistical ensemble of communication pathways in response to functional requirements of the ATPase cycle.

Mechanism-based site-directed mutagenesis to shift the optimum pH of the phenylalanine ammonia-lyase from Rhodotorula glutinis JN-1

Phenylalanine ammonia-lyase (RgPAL) from Rhodotorula glutinis JN-1 stereoselectively catalyzes the conversion of the l-phenylalanine into trans-cinnamic acid and ammonia, and was used in chiral resolution of dl-phenylalanine to produce the d-phenylalanine under acidic condition. However, the optimum pH of RgPAL is 9 and the RgPAL exhibits low catalytic efficiency at acidic side. Therefore, a mutant RgPAL with a lower optimum pH is expected. Based on catalytic mechanism and structure analysis, we constructed a mutant RgPAL-Q137E by site-directed mutagenesis, and found that this mutant had an extended optimum pH 7-9 with activity of 1.8-fold higher than that of the wild type at pH 7. As revealed by Friedel-Crafts-type mechanism of RgPAL, the improvement of the RgPAL-Q137E might be due to the negative charge of Glu137 which could stabilize the intermediate transition states through electrostatic interaction. The RgPAL-Q137E mutant was used to resolve the racemic dl-phenylalanine, and the conversion rate and the ee_D value of d-phenylalanine using RgPAL-Q137E at pH 7 were increased by 29% and 48%, and achieved 93% and 86%, respectively. This work provides an effective strategy to shift the optimum pH which is favorable to further applications of RgPAL.

Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs

Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach - MOdular NETwork Analysis (MONETA) - based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins - a crucial basis to guide the discovery of next-generation allosteric drugs.

Loop-loop interactions govern multiple steps in indole-3-glycerol phosphate synthase catalysis

Substrate binding, product release, and likely chemical catalysis in the tryptophan biosynthetic enzyme indole-3-glycerol phosphate synthase (IGPS) are dependent on the structural dynamics of the β1α1 active-site loop. Statistical coupling analysis and molecular dynamic simulations had previously indicated that covarying residues in the β1α1 and β2α2 loops, corresponding to Arg54 and Asn90, respectively, in the Sulfolobus sulfataricus enzyme (ssIGPS), are likely important for coordinating functional motions of these loops. To test this hypothesis, we characterized site mutants at these positions for changes in catalytic function, protein stability and structural dynamics for the thermophilic ssIGPS enzyme. Although there were only modest changes in the overall steady-state kinetic parameters, solvent viscosity and solvent deuterium kinetic isotope effects indicated that these amino acid substitutions change the identity of the rate-determining step across multiple temperatures. Surprisingly, the N90A substitution had a dramatic effect on the general acid/base catalysis of the dehydration step, as indicated by the loss of the descending limb in the pH rate profile, which we had previously assigned to Lys53 on the β1α1 loop. These changes in enzyme function are accompanied with a quenching of ps-ns and µs-ms timescale motions in the β1α1 loop as measured by nuclear magnetic resonance studies. Altogether, our studies provide structural, dynamic and functional rationales for the coevolution of residues on the β1α1 and β2α2 loops, and highlight the multiple roles that the β1α1 loop plays in IGPS catalysis. Thus, substitution of covarying residues in the active-site β1α1 and β2α2 loops of indole-3-glycerol phosphate synthase results in functional, structural, and dynamic changes, highlighting the multiple roles that the β1α1 loop plays in enzyme catalysis and the importance of regulating the structural dynamics of this loop through noncovalent interactions with nearby structural elements.

Energetic pathway sampling in a protein interaction domain

The affinity and specificity of protein-ligand interactions are influenced by energetic crosstalk within the protein domain. However, the molecular details of such intradomain allostery are still unclear. Here, we have experimentally detected and computationally predicted interaction pathways in the postsynaptic density 95/discs large/zonula occludens 1 (PDZ)-peptide ligand model system using wild-type and circularly permuted PDZ proteins. The circular permutant introduced small perturbations in the tertiary structure and a concomitant rewiring of allosteric pathways, allowing us to describe how subtle changes may reshape energetic signaling. The results were analyzed in the context of other members of the PDZ family, which were found to contain distinct interaction pathways for different peptide ligands. The data reveal a fascinating scenario whereby several energetic pathways are sampled within one single domain and distinct pathways are activated by specific protein ligands.

Allosteric regulation of the Hsp90 dynamics and stability by client recruiter cochaperones: protein structure network modeling

The fundamental role of the Hsp90 chaperone in supporting functional activity of diverse protein clients is anchored by specific cochaperones. A family of immune sensing client proteins is delivered to the Hsp90 system with the aid of cochaperones Sgt1 and Rar1 that act cooperatively with Hsp90 to form allosterically regulated dynamic complexes. In this work, functional dynamics and protein structure network modeling are combined to dissect molecular mechanisms of Hsp90 regulation by the client recruiter cochaperones. Dynamic signatures of the Hsp90-cochaperone complexes are manifested in differential modulation of the conformational mobility in the Hsp90 lid motif. Consistent with the experiments, we have determined that targeted reorganization of the lid dynamics is a unifying characteristic of the client recruiter cochaperones. Protein network analysis of the essential conformational space of the Hsp90-cochaperone motions has identified structurally stable interaction communities, interfacial hubs and key mediating residues of allosteric communication pathways that act concertedly with the shifts in conformational equilibrium. The results have shown that client recruiter cochaperones can orchestrate global changes in the dynamics and stability of the interaction networks that could enhance the ATPase activity and assist in the client recruitment. The network analysis has recapitulated a broad range of structural and mutagenesis experiments, particularly clarifying the elusive role of Rar1 as a regulator of the Hsp90 interactions and a stability enhancer of the Hsp90-cochaperone complexes. Small-world organization of the interaction networks in the Hsp90 regulatory complexes gives rise to a strong correspondence between highly connected local interfacial hubs, global mediator residues of allosteric interactions and key functional hot spots of the Hsp90 activity. We have found that cochaperone-induced conformational changes in Hsp90 may be determined by specific interaction networks that can inhibit or promote progression of the ATPase cycle and thus control the recruitment of client proteins.

Weighted Implementation of Suboptimal Paths (WISP): An Optimized Algorithm and Tool for Dynamical Network Analysis

Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site many ångstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. Aside from providing signal redundancy, suboptimal paths traverse residues that, if disrupted through pharmacological or mutational means, could modulate the allosteric regulation of important drug targets. To demonstrate the utility of our program, we present a case study describing the allostery of HisH-HisF, an amidotransferase from T. maritima thermotiga. WISP and its VMD-based graphical user interface (GUI) can be downloaded from http://nbcr.ucsd.edu/wisp.