Energy Propagation and Network Energetic Coupling in Proteins

Allosteric communication and signal transduction in proteins

Allostery is one of the cornerstones of biological function, as it plays a fundamental role in regulating protein activity. The modelling of allostery has gradually moved from a conformation-based framework, linked to structural changes, to dynamics-based allostery, whereby the effects of ligand binding propagate via signal transduction from the allosteric site to other regions of the protein via inter-residue interactions. Characterising such allosteric signalling pathways, which do not necessarily lead to conformational changes, has been pursued experimentally and complemented by computational analysis of protein networks to detect subtle dynamic propagation paths. Considering allostery from the perspective of signal transduction broadens the understanding of allosteric mechanisms, underscores the importance of protein topology, and can provide insights into allosteric drug design.

Emergence of allostery through reorganization of protein residue network architecture

Despite more than a century of study, consensus on the molecular basis of allostery remains elusive. A comparison of allosteric and non-allosteric members of a protein family can shed light on this important regulatory mechanism, and the bacterial biotin protein ligases, which catalyze post-translational biotin addition, provide an ideal system for such comparison. While the Class I bacterial ligases only function as enzymes, the bifunctional Class II ligases use the same structural architecture for an additional transcription repression function. This additional function depends on allosterically activated homodimerization followed by DNA binding. In this work, we used experimental, computational network, and bioinformatics analyses to uncover distinguishing features that enable allostery in the Class II biotin protein ligases. Experimental studies of the Class II Escherichia coli protein indicate that catalytic site residues are critical for both catalysis and allostery. However, allostery also depends on amino acids that are more broadly distributed throughout the protein structure. Energy-based community network analysis of representative Class I and Class II proteins reveals distinct residue community architectures, interactions among the communities, and responses of the network to allosteric effector binding. Bioinformatics mutual information analyses of multiple sequence alignments indicate distinct networks of coevolving residues in the two protein families. The results support the role of divergent local residue community network structures both inside and outside of the conserved enzyme active site combined with distinct inter-community interactions as keys to the emergence of allostery in the Class II biotin protein ligases.

Time-resolved spectroscopic mapping of vibrational energy flow in proteins: Understanding thermal diffusion at the nanoscale

Vibrational energy exchange between various degrees of freedom is critical to barrier-crossing processes in proteins. Hemeproteins are well suited for studying vibrational energy exchange in proteins because the heme group is an efficient photothermal converter. The released energy by heme following photoexcitation shows migration in a protein moiety on a picosecond timescale, which is observed using time-resolved ultraviolet resonance Raman spectroscopy. The anti-Stokes ultraviolet resonance Raman intensity of a tryptophan residue is an excellent probe for the vibrational energy in proteins, allowing the mapping of energy flow with the spatial resolution of a single amino acid residue. This Perspective provides an overview of studies on vibrational energy flow in proteins, including future perspectives for both methodologies and applications.

Energy Transport and Its Function in Heptahelical Transmembrane Proteins

Photoproteins such as bacteriorhodopsin (bR) and rhodopsin (Rho) need to effectively dissipate photoinduced excess energy to prevent themselves from damage. Another well-studied seven transmembrane (TM) helices protein is the β₂ adrenergic receptor (β₂AR), a G protein-coupled receptor for which energy dissipation paths have been linked with allosteric communication. To study the vibrational energy transport in the active and inactive states of these proteins, a master equation approach [J. Chem. Phys.2020, 152, 045103] is employed, which uses scaling rules that allow us to calculate energy transport rates solely based on the protein structure. Despite their overall structural similarity, the three 7TM proteins reveal quite different strategies to redistribute excess energy. While bR quickly removes the energy using the TM7 helix as a "lightning rod", Rho exhibits a rather poor energy dissipation, which might eventually require the hydrolysis of the Schiff base between the protein and the retinal chromophore to prevent overheating. Heating the ligand adrenaline of β₂AR, the resulting energy transport network of the protein is found to change significantly upon switching from the active state to the inactive state. While the energy flow may highlight aspects of the inter-residue couplings of β₂AR, it seems not particularly suited to explain allosteric phenomena.

Dynamical nonequilibrium molecular dynamics reveals the structural basis for allostery and signal propagation in biomolecular systems

ABSTRACT

A dynamical approach to nonequilibrium molecular dynamics (D-NEMD), proposed in the 1970s by Ciccotti et al., is undergoing a renaissance and is having increasing impact in the study of biological macromolecules. This D-NEMD approach, combining MD simulations in stationary (in particular, equilibrium) and nonequilibrium conditions, allows for the determination of the time-dependent structural response of a system using the Kubo-Onsager relation. Besides providing a detailed picture of the system's dynamic structural response to an external perturbation, this approach also has the advantage that the statistical significance of the response can be assessed. The D-NEMD approach has been used recently to identify a general mechanism of inter-domain signal propagation in nicotinic acetylcholine receptors, and allosteric effects in β -lactamase enzymes, for example. It complements equilibrium MD and is a very promising approach to identifying and analysing allosteric effects. Here, we review the D-NEMD approach and its application to biomolecular systems, including transporters, receptors, and enzymes.

Investigating Conformational Dynamics and Allostery in the p53 DNA-Binding Domain Using Molecular Simulations

The p53 tumor suppressor is a multifaceted context-dependent protein, which is involved in multiple cellular pathways, with the ability to either keep the cells alive or to kill them through mechanisms such as apoptosis. To complicate this picture, cancer cells that express mutant p53 becomes addicted to the mutant activity, so that the mutant variant features a myriad of gain-of-function activities, opening different venues for therapy. This makes essential to think outside the box and apply new approaches to the study of p53 structure-(mis)function relationship to find new critical components of its pathway or to understand how known parts are interconnected, compete, or cooperate. In this context, I will here illustrate how to integrate different computational methods to the identification of possible allosteric effects transmitted from the DNA binding interface of p53 to regions for cofactor recruitment. The protocol can be extended to any other cases of study. Indeed, it does not necessarily apply only to the study of DNA-induced effects, but more broadly to the investigation of long-range effects induced by a biological partner that binds to a biomolecule of interest.

Allosteric Response of DNA Recognition Helices of Catabolite Activator Protein to cAMP and DNA Binding

The homodimeric catabolite activator protein (CAP) regulates the transcription of several bacterial genes based on the cellular concentration of cyclic adenosine monophosphate (cAMP). The binding of cAMP to CAP triggers allosteric communication between the cAMP binding domains (CBD) and DNA binding domains (DBD) of CAP, which entails repositioning of DNA recognition helices (F-helices) in the DBD to dock favorably to the target DNA. Despite considerable progress, much remains to be understood about the mechanistic details of DNA recognition by CAP and about the map of allosteric pathways involved in CAP-mediated gene transcription. The present study uses molecular dynamics and umbrella sampling simulations to investigate the mechanism of cAMP- and DNA-induced changes in the conformation and energetics of F-helices observed during the allosteric regulation of CAP by cAMP and the subsequent binding to the DNA promoter region. Using novel collective variables, the free energy profiles associated with the orientation and dynamics of F-helices in the unliganded, cAMP-bound, and cAMP-DNA-bound states of CAP are calculated and compared. The binding-induced alterations in the resultant free energy profiles reveal important flexibility constraints imposed on DBD upon cAMP and DNA binding. A comprehensive analysis of residue-wise interaction maps reveals potential allosteric pathways between CBD and DBD that facilitate the allosteric transduction of regulatory signals in CAP. The revelation that the predicted allosteric pathways crisscross the intersubunit interface offers important clues on the microscopic origin of the intersubunit cooperativity and dimer stability of CAP.

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

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

Role of atomic contacts in vibrational energy transfer in myoglobin

Heme proteins are ideal systems to investigate vibrational energy flow at the atomic level. Upon photoexcitation, a large amount of excess vibrational energy is selectively deposited on heme due to extremely fast internal conversion. This excess energy is redistributed to the surrounding protein moiety and then to water. Vibrational energy flow in myoglobin (Mb) was examined using picosecond time-resolved anti-Stokes ultraviolet resonance Raman (UVRR) spectroscopy. We used the Trp residue directly contacting the heme group as a selective probe for vibrationally excited populations. Trp residues were placed at different position close to the heme by site-directed mutagenesis. This technique allows us to monitor the excess energy on residue-to-residue basis. Anti-Stokes UVRR measurements for Mb mutants suggest that the dominant channel for energy transfer in Mb is the pathway through atomic contacts between heme and nearby amino acid residues as well as that between the protein and solvent water. It is found that energy flow through proteins is analogous to collisional exchange processes in solutions.

Tuning Allostery through Integration of Disorder to Order with a Residue Network

In allostery, a signal from one site in a protein is transmitted to a second site to alter its function. Due to its ubiquity in biology and the potential for its exploitation in drug and protein design, the molecular basis of allosteric communication continues to be the subject of intense research. Although allosterically coupled sites are frequently characterized by disorder, how communication between disordered segments occurs remains obscure. Allosteric activation of Escherichia coli BirA dimerization occurs via coupled distant disorder-to-order transitions. In this work, combined structural and computational studies reveal an extensive residue network in BirA. Substitution of several network residues yields large perturbations to allostery. Force distribution analysis reveals that disruptions to the disorder-to-order transitions through amino acid substitution are manifested in shifts in the energy experienced by network residues as well as alterations in packing of an α-helix that plays a critical role in allostery. The combined results reveal a highly distributed allosteric mechanism that is robust to sequence change.

gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations

Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid residues and the role played by each in the context of MD simulations, we present a stand-alone software called gRINN (get Residue Interaction eNergies and Networks). gRINN features graphical user interfaces (GUIs) and a command-line interface for generating and analyzing pairwise residue interaction energies and energy correlations from protein MD simulation trajectories. gRINN utilizes the features of NAMD or GROMACS MD simulation packages and automatizes the steps necessary to extract residue-residue interaction energies from user-supplied simulation trajectories, greatly simplifying the analysis for the end-user. A GUI, including an embedded molecular viewer, is provided for visualization of interaction energy time-series, distributions, an interaction energy matrix, interaction energy correlations and a residue correlation matrix. gRINN additionally offers construction and analysis of Protein Energy Networks, providing residue-based metrics such as degrees, betweenness-centralities, closeness centralities as well as shortest path analysis. gRINN is free and open to all users without login requirement at http://grinn.readthedocs.io.

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.

Site-Resolved Observation of Vibrational Energy Transfer Using a Genetically Encoded Ultrafast Heater

Allosteric information transfer in proteins has been linked to distinct vibrational energy transfer (VET) pathways in a number of theoretical studies. Experimental evidence for such pathways, however, is sparse because site-selective injection of vibrational energy into a protein, that is, localized heating, is required for their investigation. Here, we solved this problem by the site-specific incorporation of the non-canonical amino acid β-(1-azulenyl)-l-alanine (AzAla) through genetic code expansion. As an exception to Kasha's rule, AzAla undergoes ultrafast internal conversion and heating after S₁ excitation while upon S₂ excitation, it serves as a fluorescent label. We equipped PDZ3, a protein interaction domain of postsynaptic density protein 95, with this ultrafast heater at two distinct positions. We indeed observed VET from the incorporation sites in the protein to a bound peptide ligand on the picosecond timescale by ultrafast IR spectroscopy. This approach based on genetically encoded AzAla paves the way for detailed studies of VET and its role in a wide range of proteins.

Dissecting a novel allosteric mechanism of cruzain: A computer-aided approach

Trypanosoma cruzi is the causative agent of Chagas disease, a neglected infection affecting millions of people in tropical regions. There are several chemotherapeutic agents for the treatment of this disease, but most of them are highly toxic and generate resistance. Currently, the development of allosteric inhibitors constitutes a promising research field, since it can improve the accessibility to more selective and less toxic medicines. To date, the allosteric drugs prediction is a state-of-the-art topic in rational structure-based computational design. In this work, a simulation strategy was developed for computational discovery of allosteric inhibitors, and it was applied to cruzain, a promising target and the major cysteine protease of T. cruzi. Molecular dynamics simulations, binding free energy calculations and network-based modelling of residue interactions were combined to characterize and compare molecular distinctive features of the apo form and the cruzain-allosteric inhibitor complexes. By using geometry-based criteria on trajectory snapshots, we predicted two main allosteric sites suitable for drug targeting. The results suggest dissimilar mechanisms exerted by the same allosteric site when binding different potential allosteric inhibitors. Finally, we identified the residues involved in suboptimal paths linking the identified site and the orthosteric site. The present study constitutes the first approximation to the design of cruzain allosteric inhibitors and may serve for future pharmacological intervention. Here, no major effects on active site structure were observed due to compound binding (modification of distance and angles between catalytic residues), which indicates that allosteric regulation in cruzain might be mediated via alterations of its dynamical properties similarly to allosteric inhibition of human cathepsin K (HCatK). The current findings are particularly relevant for the design of allosteric modulators of papain-like cysteine proteases.

Advances in the Computational Identification of Allosteric Sites and Pathways in Proteins

With the increasing difficulty to develop new drugs and the emergence of resistance to traditional orthosteric-site inhibitors, the search for alternatives is finally approaching the focus on allosteric sites. Allosteric sites offer opportunities to regulate many pharmacologically targeted pathways by inhibition or activation. In addition, allosteric sites tend to be less conserved than the functional site, which may facilitate the design of specific effectors in the protein families for which specific orthosteric inhibitors have proved difficult to design. Furthermore, recent evidence suggests that all proteins might be susceptible of allosteric regulation, increasing the space of druggable targets. Computational identification of allosteric sites has therefore become an active field of research. The problem can be approached from two sides: (1) the identification of allosteric-communication pathways between the functional site and potential allosteric sites and (2) the functional-site-independent identification of allosteric sites. While the first approach tends to be more laborious and thus restricted to a single protein, the second tends to be more amenable to larger-scale analysis, thus providing tools for the two drug discovery scenarios: the analysis of known targets and the screening for new potential targets. Here, I show some basic concepts and methods useful to the identification of allosteric sites and pathways, in line with these two approaches. I describe them in some detail to build a clear framework, at the risk of losing the interest of experts. Examples of recent studies involving these methods are also illustrated, focusing on the techniques rather than on their findings on allosterism.

Significance of triple torsional correlations in proteins

The free energy landscape (FEL) of a given complex molecular system is fundamentally the joint probability density of its many comprising degrees of freedom (DOFs). Computation of a complete FEL at atomistic scale is unfortunately intractable for a typical biomolecular system. The challenge of entropy calculation comes from various correlations among different DOFs. The common strategy to treat such complexity is expansion of the full correlation into various orders of local correlations. In reality, expansion is usually cut off at the second order (i.e. pairwise interactions) for protein torsional correlations without reliable estimation of the resulting error. Here, we estimated the mutual information of different torsion sets and found that triple correlations were significant for both local/distant residue pairs and consecutive backbone torsional segments. As expected, the third order approximations were found to be consistently better than the second order approximations. These findings were true for all analyzed proteins with different folds, were independent of the two different force fields utilized to generate trajectory sets, and were therefore likely to be of general importance for proteins. Additionally, binning strategies are of universal importance for numerical computation of correlations, we here provided a detailed comparison between equal-width and equal-sample binning for different bin numbers and demonstrated the impact of binning strategies on variances and biases of calculated mutual information. Our observation suggested that caution should be taken when quantitative comparison of correlations were intended between different studies with different binning strategies.

Torsional mutual information for 10 typical residue pairs calculated with full joint distributions (MI), second order expansion (MI₂), third order expansions (MI₃), and their linear recombinations (MI_LR).

Allostery and cooperativity in multimeric proteins: bond-to-bond propensities in ATCase

Aspartate carbamoyltransferase (ATCase) is a large dodecameric enzyme with six active sites that exhibits allostery: its catalytic rate is modulated by the binding of various substrates at distal points from the active sites. A recently developed method, bond-to-bond propensity analysis, has proven capable of predicting allosteric sites in a wide range of proteins using an energy-weighted atomistic graph obtained from the protein structure and given knowledge only of the location of the active site. Bond-to-bond propensity establishes if energy fluctuations at given bonds have significant effects on any other bond in the protein, by considering their propagation through the protein graph. In this work, we use bond-to-bond propensity analysis to study different aspects of ATCase activity using three different protein structures and sources of fluctuations. First, we predict key residues and bonds involved in the transition between inactive (T) and active (R) states of ATCase by analysing allosteric substrate binding as a source of energy perturbations in the protein graph. Our computational results also indicate that the effect of multiple allosteric binding is non linear: a switching effect is observed after a particular number and arrangement of substrates is bound suggesting a form of long range communication between the distantly arranged allosteric sites. Second, cooperativity is explored by considering a bisubstrate analogue as the source of energy fluctuations at the active site, also leading to the identification of highly significant residues to the T ↔ R transition that enhance cooperativity across active sites. Finally, the inactive (T) structure is shown to exhibit a strong, non linear communication between the allosteric sites and the interface between catalytic subunits, rather than the active site. Bond-to-bond propensity thus offers an alternative route to explain allosteric and cooperative effects in terms of detailed atomistic changes to individual bonds within the protein, rather than through phenomenological, global thermodynamic arguments.

Multiscale modeling of keratin, collagen, elastin and related human diseases: Perspectives from atomistic to coarse-grained molecular dynamics simulations

Scleroproteins are an important category of proteins within the human body that adopt filamentous, elongated conformations in contrast with typical globular proteins. These include keratin, collagen, and elastin, which often serve a common mechanical function in structural support of cells and tissues. Genetic mutations alter these proteins, disrupting their functions and causing diseases. Computational characterization of these mutations has proven to be extremely valuable in identifying the intricate structure-function relationships of scleroproteins from the molecular scale up, especially if combined with multiscale experimental analysis and the synthesis of model proteins to test specific structure-function relationships. In this work, we review numerous critical diseases that are related to keratin, collagen, and elastin, and through several case studies, we propose ways of extensively utilizing multiscale modeling, from atomistic to coarse-grained molecular dynamics simulations, to uncover the molecular origins for some of these diseases and to aid in the development of novel cures and therapies. As case studies, we examine the effects of the genetic disease Epidermolytic Hyperkeratosis (EHK) on the structure and aggregation of keratins 1 and 10; we propose models to understand the diseases of Osteogenesis Imperfecta (OI) and Alport syndrome (AS) that affect the mechanical and aggregation properties of collagen; and we develop atomistic molecular dynamics and elastic network models of elastin to determine the role of mutations in diseases such as Cutis Laxa and Supravalvular Aortic Stenosis on elastin's structure and molecular conformational motions and implications for assembly.

Computational study to understand the energy transfer pathways within amicyanin

Vibrational energy diffusivities between the residues present in Amicyanin copper protein are calculated and presented in form of communication map. From those results energy flow pathways from the copper metal ion to the inter protein residue Glu31 are identified. Our finding suggests many different pathways are possible and copper metal ion in oxidized and reduced state switches the pathways. Our finding also suggests the cooperative nature of surrounding residues and water molecules towards selecting the pathways. The major transport channels in the oxidised state are, Cu²⁺---> MET28---> LYS29---> TYR30---> GLU31 and Cu²⁺---> MET98---> TYR30--- > GLU31. And in the reduced state Cu⁺---> CYS9---> TYR30---> GLU31 and Cu⁺---> MET28---> LYS2---> TYR30---> GLU31. We studied further the interaction energies between the copper ion and neighbouring residues using B3LYP/QZVP method. Both the methods complement each other in predicting the energy flow pathways and the cooperative nature of residues.

Long Distance Modulation of Disorder-to-Order Transitions in Protein Allostery

Elucidation of the molecular details of allosteric communication between distant sites in a protein is key to understanding and manipulating many biological regulatory processes. Although protein disorder is acknowledged to play an important thermodynamic role in allostery, the molecular mechanisms by which this disorder is harnessed for long distance communication are known for a limited number of systems. Transcription repression by the Escherichia coli biotin repressor, BirA, is allosterically activated by binding of the small molecule effector biotinoyl-5'-AMP. The effector acts by promoting BirA dimerization, which is a prerequisite for sequence-specific binding to the biotin biosynthetic operon operator sequence. A 30 Å distance separates the effector binding and dimerization surfaces in BirA, and previous studies indicate that allostery is mediated, in part, by disorder-to-order transitions on the two coupled sites. In this work, combined experimental and computational methods have been applied to investigate the molecular basis of allosteric communication in BirA. Double-mutant cycle analysis coupled with thermodynamic measurements indicates functional coupling between residues in disordered loops on the two distant surfaces. All atom molecular dynamics simulations reveal that this coupling occurs through long distance reciprocal modulation of the structure and dynamics of disorder-to-order transitions on the two surfaces.

What Mutagenesis Can and Cannot Reveal About Allostery

Allosteric regulation of protein function is recognized to be widespread throughout biology; however, knowledge of allosteric mechanisms, the molecular changes within a protein that couple one binding site to another, is limited. Although mutagenesis is often used to probe allosteric mechanisms, we consider herein what the outcome of a mutagenesis study truly reveals about an allosteric mechanism. Arguably, the best way to evaluate the effects of a mutation on allostery is to monitor the allosteric coupling constant (Qax), a ratio of the substrate binding constants in the absence versus presence of an allosteric effector. A range of substitutions at a given residue position in a protein can reveal when a particular substitution causes gain-of-function, which addresses a key challenge in interpreting mutation-dependent changes in the magnitude of Qax. Thus, whole-protein mutagenesis studies offer an acceptable means of identifying residues that contribute to an allosteric mechanism. With this focus on monitoring Qax, and keeping in mind the equilibrium nature of allostery, we consider alternative possibilities for what an allosteric mechanism might be. We conclude that different possible mechanisms (rotation-of-solid-domains, movement of secondary structure, side-chain repacking, changes in dynamics, etc.) will result in different findings in whole-protein mutagenesis studies.

An optimal distance cutoff for contact-based Protein Structure Networks using side-chain centers of mass

Proteins are highly dynamic entities attaining a myriad of different conformations. Protein side chains change their states during dynamics, causing clashes that are propagated at distal sites. A convenient formalism to analyze protein dynamics is based on network theory using Protein Structure Networks (PSNs). Despite their broad applicability, few efforts have been devoted to benchmarking PSN methods and to provide the community with best practices. In many applications, it is convenient to use the centers of mass of the side chains as nodes. It becomes thus critical to evaluate the minimal distance cutoff between the centers of mass which will provide stable network properties. Moreover, when the PSN is derived from a structural ensemble collected by molecular dynamics (MD), the impact of the MD force field has to be evaluated. We selected a dataset of proteins with different fold and size and assessed the two fundamental properties of the PSN, i.e. hubs and connected components. We identified an optimal cutoff of 5 Å that is robust to changes in the force field and the proteins. Our study builds solid foundations for the harmonization and standardization of the PSN approach.

Molecular Mechanism of Nucleotide-Dependent Allosteric Regulation in AMP-Activated Protein Kinase

The AMP-activated protein kinase (AMPK), a central enzyme in the regulation of energy homeostasis, is an important drug target for type 2 diabetes, obesity, and cancer. Binding of adenosine nucleotides to the regulatory γ-subunit tightly regulates the activity of this enzyme. Though recent crystal structures of AMPK have provided important insights into the allosteric activation of AMPK, molecular details of the regulatory mechanism of AMPK activation is still elusive. Here, we have performed extensive all-atom molecular dynamics (MD) simulations and shown that the kinase domain (KD) and γ-subunit come closer resulting in a more compact heterotrimeric AMPK complex in AMP-bound state compared to the ATP-bound state. The binding of ATP at site 3 of regulatory γ-subunit allosterically inhibits AMPK by destabilizing different regulatory regions of α-subunit: the autoinhibitory domain, the linker region, and the activation loop of the kinase core. The catalytically important residues experience a change in mechanical stress, and major rearrangements in community structure derived from residue-residue interaction energy-based network are observed in KD and α-linker region upon binding of different nucleotides. Our results also highlight the role of conserved charged residues forming an ionic network near the site 3 of γ-subunit in allosteric communications.

Monitoring Conformational Landscape of Ovine Prion Protein Monomer Using Ion Mobility Coupled to Mass Spectrometry

Prion protein is involved in deadly neurodegenerative diseases. Its pathogenicity is linked to its structural conversion (α-helix to β-strand transition). However, recent studies suggest that prion protein can follow a plurality of conversion pathways, which hints towards different conformers that might coexist in solution. To gain insights on the plasticity of the ovine prion protein (PrP) monomer, wild type (A136, R154, Q171), mutants and deletions of ARQ were studied by traveling wave ion mobility experiments coupled to mass spectrometry. In order to perform the analysis of a large body of data sets, we designed and evaluated the performance of a processing pipeline based on Driftscope peak detection and a homemade script for automated peak assignment, annotation, and quantification on specific multiply charged protein data. Using this approach, we showed that in the gas phase, PrPs are represented by at least three conformer families differing in both charge state distribution and collisional cross-section, in agreement with the work of Hilton et al. (2010). We also showed that this plasticity is borne both by the N- and C-terminal domains. Effect of protein concentration, pH and temperature were also assessed, showing that (1) pH does not affect conformer distributions, (2) protein concentration modifies the conformational landscape of one mutant (I208M) only, and (3) heating leads to other unfolded species and to a modification of the conformer intensity ratios. Graphical Abstract ᅟ.

Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites.

Water-Mediated Energy Dynamics in a Homodimeric Hemoglobin

We examine energy dynamics in the unliganded and liganded states of the homodimeric hemoglobin from Scapharca inaequivalvis (HbI), which exhibits cooperativity mediated by the cluster of water molecules at the interface upon ligand binding and dissociation. We construct and analyze a dynamic network in which nodes representing the residues, hemes, and water cluster are connected by edges that represent energy transport times, as well as a nonbonded network (NBN) indicating regions that respond rapidly to local strain within the protein via nonbonded interactions. One of the two largest NBNs includes the Lys30-Asp89 salt bridge critical for stabilizing the dimer. The other includes the hemes and surrounding residues, as well as, in the unliganded state, the cluster of water molecules between the globules. Energy transport in the protein appears to be controlled by the Lys30-Asp89 salt bridge critical for stabilizing the dimer, as well as the interface water cluster in the unliganded state. Possible connections between energy transport dynamics in response to local strain identified here and allosteric transitions in HbI are discussed.

Mapping Mechanical Force Propagation through Biomolecular Complexes

Here we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. The results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.

MDN: A Web Portal for Network Analysis of Molecular Dynamics Simulations

We introduce a web portal that employs network theory for the analysis of trajectories from molecular dynamics simulations. Users can create protein energy networks following methodology previously introduced by our group, and can identify residues that are important for signal propagation, as well as measure the efficiency of signal propagation by calculating the network coupling. This tool, called MDN, was used to characterize signal propagation in Escherichia coli heat-shock protein 70-kDa. Two variants of this protein experimentally shown to be allosterically active exhibit higher network coupling relative to that of two inactive variants. In addition, calculations of partial coupling suggest that this quantity could be used as part of the criteria to determine pocket druggability in drug discovery studies.

Allosteric communication pathways and thermal rectification in PDZ-2 protein: a computational study

Allosteric communication in proteins is a fundamental and yet unresolved problem of structural biochemistry. Previous findings, from computational biology ( Ota, N.; Agard, D. A. J. Mol. Biol. 2005 , 351 , 345 - 354 ), have proposed that heat diffuses in a protein through cognate protein allosteric pathways. This work studied heat diffusion in the well-known PDZ-2 protein, and confirmed that this protein has two cognate allosteric pathways and that heat flows preferentially through these. Also, a new property was also observed for protein structures: heat diffuses asymmetrically through the structures. The underling structure of this asymmetrical heat flow was a normal length hydrogen bond (∼2.85 Å) that acted as a thermal rectifier. In contrast, thermal rectification was compromised in short hydrogen bonds (∼2.60 Å), giving rise to symmetrical thermal diffusion. Asymmetrical heat diffusion was due, on a higher scale, to the local, structural organization of residues that, in turn, was also mediated by hydrogen bonds. This asymmetrical/symmetrical energy flow may be relevant for allosteric signal communication directionality in proteins and for the control of heat flow in materials science.