Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics

Phospholamban inhibits the cardiac calcium pump by interrupting an allosteric activation pathway

Phospholamban (PLB) is a transmembrane micropeptide that regulates the sarcoplasmic reticulum Ca2+-ATPase (SERCA) in cardiac muscle, but the physical mechanism of this regulation remains poorly understood. PLB reduces the Ca2+ sensitivity of active SERCA, increasing the Ca2+ concentration required for pump cycling. However, PLB does not decrease Ca2+ binding to SERCA when ATP is absent, suggesting PLB does not inhibit SERCA Ca2+ affinity. The prevailing explanation for these seemingly conflicting results is that PLB slows transitions in the SERCA enzymatic cycle associated with Ca2+ binding, altering transport Ca2+ dependence without actually affecting the equilibrium binding affinity of the Ca2+-coordinating sites. Here, we consider another hypothesis, that measurements of Ca2+ binding in the absence of ATP overlook important allosteric effects of nucleotide binding that increase SERCA Ca2+ binding affinity. We speculated that PLB inhibits SERCA by reversing this allostery. To test this, we used a fluorescent SERCA biosensor to quantify the Ca2+ affinity of non-cycling SERCA in the presence and absence of a non-hydrolyzable ATP-analog, AMPPCP. Nucleotide activation increased SERCA Ca2+ affinity, and this effect was reversed by co-expression of PLB. Interestingly, PLB had no effect on Ca2+ affinity in the absence of nucleotide. These results reconcile the previous conflicting observations from ATPase assays versus Ca2+ binding assays. Moreover, structural analysis of SERCA revealed a novel allosteric pathway connecting the ATP- and Ca2+-binding sites. We propose this pathway is disrupted by PLB binding. Thus, PLB reduces the equilibrium Ca2+ affinity of SERCA by interrupting allosteric activation of the pump by ATP.

Oliveira AS, Mulholland AJ, Serapian SA, Colombo G. Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Activation mechanism of the human Smoothened receptor

Smoothened (SMO) is a membrane protein of the class F subfamily of G protein-coupled receptors (GPCRs) and maintains homeostasis of cellular differentiation. SMO undergoes conformational change during activation, transmitting the signal across the membrane, making it amenable to bind to its intracellular signaling partner. Receptor activation has been studied at length for class A receptors, but the mechanism of class F receptor activation remains unknown. Agonists and antagonists bound to SMO at sites in the transmembrane domain (TMD) and the cysteine-rich domain have been characterized, giving a static view of the various conformations SMO adopts. Although the structures of the inactive and active SMO outline the residue-level transitions, a kinetic view of the overall activation process remains unexplored for class F receptors. We describe SMO's activation process in atomistic detail by performing 300 μs of molecular dynamics simulations and combining it with Markov state model theory. A molecular switch, conserved across class F and analogous to the activation-mediating D-R-Y motif in class A receptors, is observed to break during activation. We also show that this transition occurs in a stage-wise movement of the transmembrane helices: TM6 first, followed by TM5. To see how modulators affect SMO activity, we simulated agonist and antagonist-bound SMO. We observed that agonist-bound SMO has an expanded hydrophobic tunnel in SMO's core TMD, whereas antagonist-bound SMO shrinks this tunnel, further supporting the hypothesis that cholesterol travels through a tunnel inside Smoothened to activate it. In summary, this study elucidates the distinct activation mechanism of class F GPCRs and shows that SMO's activation process rearranges the core TMD to open a hydrophobic conduit for cholesterol transport.

psnGPCRdb: The Structure-network Database of G Protein Coupled Receptors

G protein coupled receptors (GPCRs) are critical eukaryotic signal transduction gatekeepers and represent the largest protein superfamily in the human proteome, with more than 800 members. They share seven transmembrane helices organized in an up-down bundle architecture. GPCR-mediated signaling pathways have been linked to numerous human diseases, and GPCRs are the targets of approximately 35% of all drugs currently on the market. Structure network analysis, a graph theory-based approach, represents a cutting-edge tool to deeply understand GPCR function, which strongly relies on communication between the extracellular and intracellular poles of their structure. psnGPCRdb stores the structure networks (i.e., linked nodes, hubs, communities and communication pathways) computed on all updated GPCR structures in the Protein Data Bank, in their isolated states or in complex with extracellular and/or intracellular molecules. The structure communication signatures of a sub-family or family of GPCRs as well as of their small-molecule activators or inhibitors are stored as consensus networks. The database stores also all meaningful structure network-based comparisons (i.e., difference networks) of functionally different states (i.e., inactive or active) of a given receptor sub-type, or of consensus networks representative of a receptor sub-type, type, sub-family or family. Single or consensus GPCR networks hold also information on amino acid conservation. The database allows to graphically analyze 3D structure networks together with interactive data-tables. Ligand-centric networks can be analyzed as well. psnGPCRdb is unique and represents a powerful resource to unravel GPCR function with important implications in cell signaling and drug design. psnGPCRdb is freely available at: http://webpsn.hpc.unimo.it/psngpcr.php.

Conformational spread drives the evolution of the calcium-calmodulin protein kinase II

The calcium calmodulin (Ca²⁺/CaM) dependent protein kinase II (CaMKII) decodes Ca²⁺ frequency oscillations. The CaMKIIα isoform is predominantly expressed in the brain and has a central role in learning. I matched residue and organismal evolution with collective motions deduced from the atomic structure of the human CaMKIIα holoenzyme to learn how its ring architecture abets function. Protein dynamic simulations showed its peripheral kinase domains (KDs) are conformationally coupled via lateral spread along the central hub. The underlying β-sheet motions in the hub or association domain (AD) were deconvolved into dynamic couplings based on mutual information. They mapped onto a coevolved residue network to partition the AD into two distinct sectors. A second, energetically stressed sector was added to ancient bacterial enzyme dimers for assembly of the ringed hub. The continued evolution of the holoenzyme after AD–KD fusion targeted the sector’s ring contacts coupled to the KD. Among isoforms, the α isoform emerged last and, it alone, mutated rapidly after the poikilotherm–homeotherm jump to match the evolution of memory. The correlation between dynamics and evolution of the CaMKII AD argues single residue substitutions fine-tune hub conformational spread. The fine-tuning could increase CaMKIIα Ca²⁺ frequency response range for complex learning functions.

PSNtools for standalone and web-based structure network analyses of conformational ensembles

Structure graphs, in which interacting amino acids/nucleotides correspond to linked nodes, represent cutting-edge tools to investigate macromolecular function.

The graph-based approach defined as Protein Structure Network (PSN) was initially implemented in the Wordom software and subsequently in the webPSN server. PSNs are computed either on a molecular dynamics (MD) trajectory (PSN-MD) or on a single structure. In the latter case, information on atomic fluctuations is inferred from the Elastic Network Model-Normal Mode Analysis (ENM-NMA) (PSN-ENM). While Wordom performs both PSN-ENM and PSN-MD analyses but without output post-processing, the webPSN server performs only single-structure PSN-EMN but assisting the user in input setup and output analysis.

Here we release for the first time the standalone software PSNtools, which allows calculation and post-processing of PSN analyses carried out either on single structures or on conformational ensembles. Relevant unique and novel features of PSNtools are either comparisons of two networks or computations of consensus networks on sets of homologous/analogous macromolecular structures or conformational ensembles. Network comparisons and consensus serve to infer differences in functionally different states of the same system or network-based signatures in groups of bio-macromolecules sharing either the same functionality or the same fold.

In addition to the new software, here we release also an updated version of the webPSN server, which allows performing an interactive graphical analysis of PSN-MD, following the upload of the PSNtools output.

PSNtools, the auxiliary binary version of Wordom software, and the WebPSN server are freely available at http://webpsn.hpc.unimo.it/wpsn3.php.

Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action

Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the membrane protein rod opsin. While the mechanisms underlying the noxious effects of the mutated protein are not completely understood, a common feature is the functional protein conformational loss. Here, the wild type and 39 adRP rod opsin mutants were subjected to mechanical unfolding simulations coupled to the graph theory-based protein structure network analysis.

A robust computational model was inferred and in vitro validated in its ability to predict endoplasmic reticulum retention of adRP mutants, a feature linked to the mutation-caused misfolding. The structure-based approach could also infer the structural determinants of small chaperone action on misfolded protein mutants with therapeutic implications.

The approach is exportable to conformational diseases linked to missense mutations in any membrane protein.

Autoencoder-based detection of the residues involved in G protein-coupled receptor signaling

Regulator binding and mutations alter protein dynamics. The transmission of the signal of these alterations to distant sites through protein motion results in changes in protein expression and cell function. The detection of residues involved in signal transmission contributes to an elucidation of the mechanisms underlying processes as vast as cellular function and disease pathogenesis. We developed an autoencoder (AE) based method that detects residues essential for signaling by comparing the fluctuation data, particularly the time fluctuation of the side-chain distances between residues, during molecular dynamics simulations between the ligand-bound and -unbound forms or wild-type and mutant forms of proteins. Here, the AE-based method was applied to the G protein-coupled receptor (GPCR) system, particularly a class A-type GPCR, CXCR4, to detect the essential residues involved in signaling. Among the residues involved in the signaling of the homolog CXCR2, which were extracted from the literature based on the complex structures of the ligand and G protein, our method could detect more than half of the essential residues involved in G protein signaling, including those spanning the fifth and sixth transmembrane helices in the intracellular region, despite the lack of information regarding the interaction with G protein in our CXCR4 models.

Mutual information analysis of the dynamic correlation between side chains in proteins

Protein dynamics play an essential role in function regulation. In recent years, many experimental and theoretical studies have shown that changes in protein fluctuations in the backbone and side chains fulfill a pivotal role associated with amino acid mutations, chemical modifications, and ligand binding. The dynamic correlations between protein side chains have not been sufficiently studied, and no reliable analysis method has been available so far. Therefore, we developed a method to evaluate the dynamic correlation between protein side chains using mutual information and molecular dynamics simulations. To eliminate the structural superposition errors dealing with conventional analysis methods, and to accurately extract the intrinsic fluctuation properties of the side chains, we employed distance principal component analysis (distPCA). The motion of the side chain was then projected onto the eigenvector space obtained by distPCA, and the mutual information between the projected motions was calculated. The proposed method was then applied to a small protein "eglin c" and the mutants. The results show that even a single mutation significantly changed the dynamic correlations and also suggest that the dynamic change is deeply related to the stability. Those results indicate that our developed method could be useful for analyzing the molecular mechanism of allosteric communication in proteins.

Activation mechanism of Drosophila cryptochrome through an allosteric switch

Cryptochromes are signaling proteins activated by photoexcitation of the flavin adenine dinucleotide (FAD) cofactor. Although extensive research has been performed, the mechanism for this allosteric process is still unknown. We constructed three computational models, corresponding to different redox states of the FAD cofactor in Drosophila cryptochrome (dCRY). Analyses of the dynamics trajectories reveal that the activation process occurs in the semiquinone state FAD^-●, resulting from excited-state electron transfer. The Arg³⁸¹-Asp⁴¹⁰ salt bridge acts as an allosteric switch, regulated by the change in the redox state of FAD. In turn, Asp⁴¹⁰ forms new hydrogen bonds, connecting allosteric networks of the amino-terminal and carboxyl-terminal domains initially separated in the resting state. The expansion to a global dynamic network leads to enhanced protein fluctuations, an increase in the radius of gyration, and the expulsion of the carboxyl-terminal tail. These structural features are in accord with mutations and spectroscopic experiments.

Molecular Simulations Guidelines for Biological Nanomaterials: From Peptides to Membranes

In studying biological processes and focusing on the molecular mechanisms at the basis of these, molecular dynamics (MD) simulations have demonstrated to be a very useful tool for the past 50 years. This suite of computational methods calculates the time-dependent evolution of a molecular system using physics-based first principles. In this chapter, we give a brief introduction to the theory and practical use of molecular dynamics simulations, highlighting the different models and algorithms that have been developed to tackle specific problems, with a special focus on classical force fields. Some examples of how simulations have been used in the past will help the reader in discerning their power, limitations, and significance.

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.

Cholesterol binding to the sterol-sensing region of Niemann Pick C1 protein confines dynamics of its N-terminal domain

Lysosomal accumulation of cholesterol is a hallmark of Niemann Pick type C (NPC) disease caused by mutations primarily in the lysosomal membrane protein NPC1. NPC1 contains a transmembrane sterol-sensing domain (SSD), which is supposed to regulate protein activity upon cholesterol binding, but the mechanisms underlying this process are poorly understood. Using atomistic simulations, we show that in the absence of cholesterol in the SSD, the luminal domains of NPC1 are highly dynamic, resulting in the disengagement of the NTD from the rest of the protein. The disengaged NPC1 adopts a flexed conformation that approaches the lipid bilayer, and could represent a conformational state primed to receive a sterol molecule from the soluble lysosomal cholesterol carrier NPC2. The binding of cholesterol to the SSD of NPC1 allosterically suppresses the conformational dynamics of the luminal domains resulting in an upright NTD conformation. The presence of an additional 20% cholesterol in the membrane has negligible impact on this process. The additional presence of an NTD-bound cholesterol suppresses the flexing of the NTD. We propose that cholesterol acts as an allosteric effector, and the modulation of NTD dynamics by the SSD-bound cholesterol constitutes an allosteric feedback mechanism in NPC1 that controls cholesterol abundance in the lysosomal membrane.

Cholesterol is absorbed from LDL particles in esterified form, and is broken down to free cholesterol in the lysosomes of cells, from where cholesterol must be transported to other cellular compartments such as the plasma membrane. The Niemann Pick type C (NPC) diseases arise from deficient cholesterol transport and result from mutations in the cholesterol transport protein NPC1. Using computer simulations, we show that cholesterol, when bound to one part of NPC1, can control the structural transitions of an 8-nm distant, different part of NPC1 protein called the N-terminal domain (NTD). Such long-range control of protein conformations (allostery), controls a wide range of cellular functions mediated by proteins. Fundamental molecular insights into the function of the NPC1 protein can potentially lead to better pharmaceutical interventions for the NPC diseases.

webPSN v2.0: a webserver to infer fingerprints of structural communication in biomacromolecules

A mixed Protein Structure Network (PSN) and Elastic Network Model-Normal Mode Analysis (ENM-NMA)-based strategy (i.e. PSN-ENM) was developed to investigate structural communication in bio-macromolecules. Protein Structure Graphs (PSGs) are computed on a single structure, whereas information on system dynamics is supplied by ENM-NMA. The approach was implemented in a webserver (webPSN), which was significantly updated herein. The webserver now handles both proteins and nucleic acids and relies on an internal upgradable database of network parameters for ions and small molecules in all PDB structures. Apart from the radical restyle of the server and some changes in the calculation setup, other major novelties concern the possibility to: a) compute the differences in nodes, links, and communication pathways between two structures (i.e. network difference) and b) infer links, hubs, communities, and metapaths from consensus networks computed on a number of structures. These new features are useful to identify commonalties and differences between two different functional states of the same system or structural-communication signatures in homologous or analogous systems. The output analysis relies on 3D-representations, interactive tables and graphs, also available for download. Speed and accuracy make this server suitable to comparatively investigate structural communication in large sets of bio-macromolecular systems. URL: http://webpsn.hpc.unimore.it.

Allosteric Priming of E. coli CheY by the Flagellar Motor Protein FliM

Phosphorylation of Escherichia coli CheY protein transduces chemoreceptor stimulation to a highly cooperative flagellar motor response. CheY binds to the N-terminal peptide of the FliM motor protein (FliM_N). Constitutively active D13K-Y106W CheY has been an important tool for motor physiology. The crystal structures of CheY and CheY ⋅ FliM_N with and without D13K-Y106W have shown FliM_N-bound CheY contains features of both active and inactive states. We used molecular dynamics (MD) simulations to characterize the CheY conformational landscape accessed by FliM_N and D13K-Y106W. Mutual information measures identified the central features of the long-range CheY allosteric network between D57 phosphorylation site and the FliM_N interface, namely the closure of the α4-β4 hinge and inward rotation of Y- or W106 with W58. We used hydroxy-radical foot printing with mass spectroscopy (XFMS) to track the solvent accessibility of these and other side chains. The solution XFMS oxidation rate correlated with the solvent-accessible area of the crystal structures. The protection of allosteric relay side chains reported by XFMS confirmed the intermediate conformation of the native CheY ⋅ FliM_N complex, the inactive state of free D13K-Y106W CheY, and the MD-based network architecture. We extended the MD analysis to determine temporal coupling and energetics during activation. Coupled aromatic residue rotation was a graded rather than a binary switch, with Y- or W106 side-chain burial correlated with increased FliM_N affinity. Activation entrained CheY fold stabilization to FliM_N affinity. The CheY network could be partitioned into four dynamically coordinated sectors. Residue substitutions mapped to sectors around D57 or the FliM_N interface according to phenotype. FliM_N increased sector size and interactions. These sectors fused between the substituted K13-W106 residues to organize a tightly packed core and novel surfaces that may bind additional sites to explain the cooperative motor response. The community maps provide a more complete description of CheY priming than proposed thus far.

The Architectural Dynamics of the Bacterial Flagellar Motor Switch

The rotary bacterial flagellar motor is remarkable in biochemistry for its highly synchronized operation and amplification during switching of rotation sense. The motor is part of the flagellar basal body, a complex multi-protein assembly. Sensory and energy transduction depends on a core of six proteins that are adapted in different species to adjust torque and produce diverse switches. Motor response to chemotactic and environmental stimuli is driven by interactions of the core with small signal proteins. The initial protein interactions are propagated across a multi-subunit cytoplasmic ring to switch torque. Torque reversal triggers structural transitions in the flagellar filament to change motile behavior. Subtle variations in the core components invert or block switch operation. The mechanics of the flagellar switch have been studied with multiple approaches, from protein dynamics to single molecule and cell biophysics. The architecture, driven by recent advances in electron cryo-microscopy, is available for several species. Computational methods have correlated structure with genetic and biochemical databases. The design principles underlying the basis of switch ultra-sensitivity and its dependence on motor torque remain elusive, but tantalizing clues have emerged. This review aims to consolidate recent knowledge into a unified platform that can inspire new research strategies.

Autoencoder-Based Detection of Dynamic Allostery Triggered by Ligand Binding Based on Molecular Dynamics

Dynamic allostery on proteins, triggered by regulator binding or chemical modifications, transmits information from the binding site to distant regions, dramatically altering protein function. It is accompanied by subtle changes in side-chain conformations of the protein, indicating that the changes in dynamics, and not rigid or large conformational changes, are essential to understand regulation of protein function. Although a lot of experimental and theoretical studies have been dedicated to investigate this issue, the regulation mechanism of protein function is still being debated. Here, we propose an autoencoder-based method that can detect dynamic allostery. The method is based on the comparison of time fluctuations of protein structures, in the form of distance matrices, obtained from molecular dynamics simulations in ligand-bound and -unbound forms. Our method detected that the changes in dynamics by ligand binding in the PDZ2 domain led to the reorganization of correlative fluctuation motions among residue pairs, which revealed a different view of the correlated motions from the PCA and DCCM. In addition, other correlative motions were also found as a result of the dynamic perturbation from the ligand binding, which may lead to dynamic allostery. This autoencoder-based method would be usefully applied to the signal transduction and mutagenesis systems involved in protein functions and severe diseases.

The allosteric mechanism of substrate-specific transport in SLC6 is mediated by a volumetric sensor

Neurotransmitter:sodium symporters (NSSs) in the SLC6 family terminate neurotransmission by coupling the thermodynamically favorable transport of ions to the thermodynamically unfavorable transport of neurotransmitter back into presynaptic neurons. Results from many structural, functional, and computational studies on LeuT, a bacterial NSS homolog, have provided critical insight into the mechanism of sodium-coupled transport, but the mechanism underlying substrate-specific transport rates is still not understood. We present a combination of molecular dynamics simulations, single-molecule fluorescence resonance energy transfer (smFRET) imaging, and measurements of Na+ binding and substrate transport that reveals an allosteric substrate specificity mechanism. In this mechanism, residues F259 and I359 in the substrate binding pocket couple the binding of substrate to Na+ release from the Na2 site by allosterically modulating the stability of a partially open, inward-facing state. We propose a model for transport selectivity in which residues F259 and I359 act as a volumetric sensor that inhibits the transport of bulky amino acids.

Functional cross-talk between allosteric effects of activating and inhibiting ligands underlies PKM2 regulation

Several enzymes can simultaneously interact with multiple intracellular metabolites, however, how the allosteric effects of distinct ligands are integrated to coordinately control enzymatic activity remains poorly understood. We addressed this question using, as a model system, the glycolytic enzyme pyruvate kinase M2 (PKM2). We show that the PKM2 activator fructose 1,6-bisphosphate (FBP) alone promotes tetramerisation and increases PKM2 activity, but addition of the inhibitor L-phenylalanine (Phe) prevents maximal activation of FBP-bound PKM2 tetramers. We developed a method, AlloHubMat, that uses eigenvalue decomposition of mutual information derived from molecular dynamics trajectories to identify residues that mediate FBP-induced allostery. Experimental mutagenesis of these residues identified PKM2 variants in which activation by FBP remains intact but cannot be attenuated by Phe. Our findings reveal residues involved in FBP-induced allostery that enable the integration of allosteric input from Phe and provide a paradigm for the coordinate regulation of enzymatic activity by simultaneous allosteric inputs.

Conformational coupling by trans-phosphorylation in calcium calmodulin dependent kinase II

The calcium calmodulin-dependent protein kinase II (CaMKII) is a dodecameric holoenzyme important for encoding memory. Its activation, triggered by binding of calcium-calmodulin, persists autonomously after calmodulin dissociation. One (receiver) kinase captures and subsequently phosphorylates the regulatory domain peptide of a donor kinase forming a chained dimer as the first stage of autonomous activation. Protein dynamics simulations examined the conformational changes triggered by dimer formation and phosphorylation, aimed to provide a molecular rationale for human mutations that result in learning disabilities. Ensembles generated from X-ray crystal structures were characterized by network centrality and community analysis. Mutual information related collective motions to local fragment dynamics encoded with a structural alphabet. Implicit solvent tCONCOORD conformational ensembles revealed the dynamic architecture of inactive kinase domains was co-opted in the activated dimer but the network hub shifted from the nucleotide binding cleft to the captured peptide. Explicit solvent molecular dynamics (MD) showed nucleotide and substrate binding determinants formed coupled nodes in long-range signal relays between regulatory peptides in the dimer. Strain in the extended captured peptide was balanced by reduced flexibility of the receiver kinase C-lobe core. The relays were organized around a hydrophobic patch between the captured peptide and a key binding helix. The human mutations aligned along the relays. Thus, these mutations could disrupt the allosteric network alternatively, or in addition, to altered binding affinities. Non-binding protein sectors distant from the binding sites mediated the allosteric signalling; providing possible targets for inhibitor design. Phosphorylation of the peptide modulated the dielectric of its binding pocket to strengthen the patch, non-binding sectors, domain interface and temporal correlations between parallel relays. These results provide the molecular details underlying the reported positive kinase cooperativity to enrich the discussion on how autonomous activation by phosphorylation leads to long-term behavioural effects.

Protein kinases play central roles in intracellular signalling. Auto-phosphorylation by bound nucleotide typically precedes phosphate transfer to multiple substrates. Protein conformational changes are central to kinase function, altering binding affinities to change cellular location and shunt from one signal pathway to another. In the brain, the multi-subunit kinase, CaMKII is activated by calcium-calmodulin upon calcium jumps produced by synaptic stimulation. Auto-transphosphorylation of a regulatory peptide enables the kinase to remain activated and mediate long-term behavioural effects after return to basal calcium levels. A database of mutated residues responsible for these effects is difficult to reconcile solely with impaired nucleotide or substrate binding. Therefore, we have computationally generated interaction networks to map the conformational plasticity of the kinase domains where most mutations localize. The network generated from the atomic structure of a phosphorylated dimer resolves protein sectors based on their collective motions. The sectors link nucleotide and substrate binding sites in self-reinforcing relays between regulatory peptides. The self-reinforcement is strengthened by phosphorylation consistent with the reported positive cooperativity of kinase activity with calcium-calmodulin concentration. The network gives a better match with the mutations and, in addition, reveals target sites for drug development.

Use of Computational Biochemistry for Elucidating Molecular Mechanisms of Nitric Oxide Synthase

Nitric oxide (NO) is an essential signaling molecule in the regulation of multiple cellular processes. It is endogenously synthesized by NO synthase (NOS) as the product of L-arginine oxidation to L-citrulline, requiring NADPH, molecular oxygen, and a pterin cofactor. Two NOS isoforms are constitutively present in cells, nNOS and eNOS, and a third is inducible (iNOS). Despite their biological relevance, the details of their complex structural features and reactivity mechanisms are still unclear. In this review, we summarized the contribution of computational biochemistry to research on NOS molecular mechanisms. We described in detail its use in studying aspects of structure, dynamics and reactivity. We also focus on the numerous outstanding questions in the field that could benefit from more extensive computational investigations.

Peeking at G-protein-coupled receptors through the molecular dynamics keyhole

Molecular dynamics is a state of the art computational tool for the investigation of biophysics phenomenon at a molecular scale, as it enables the modeling of dynamic processes, such as conformational motions, molecular solvation and ligand binding. The recent advances in structural biology have led to a bloom in published G-protein-coupled receptor structures, representing a solid and valuable resource for molecular dynamics studies. During the last decade, indeed, a plethora of physiological and pharmacological facets of this membrane protein superfamily have been addressed by means of molecular dynamics simulations, including the activation mechanism, allosterism and, very recently, biased signaling. Here, we try to recapitulate some of the main contributions that molecular dynamics has recently produced in the field.

Dynamic Role of the G Protein in Stabilizing the Active State of the Adenosine A2A Receptor

Agonist binding in the extracellular region of the G protein-coupled adenosine A2A receptor increases its affinity to the G proteins in the intracellular region, and vice versa. The structural basis for this effect is not evident from the crystal structures of A_2AR in various conformational states since it stems from the receptor dynamics. Using atomistic molecular dynamics simulations on four different conformational states of the adenosine A_2A receptor, we observed that the agonists show decreased ligand mobility, lower entropy of the extracellular loops in the active-intermediate state compared with the inactive state. In contrast, the entropy of the intracellular region increases to prime the receptor for coupling the G protein. Coupling of the G protein to A_2AR shrinks the agonist binding site, making tighter receptor agonist contacts with an increase in the strength of allosteric communication compared with the active-intermediate state. These insights provide a strong basis for structure-based ligand design studies.

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GPCR conformation dynamics reveals the forward and backward allosteric mechanism

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Agonist binding increases the entropy in the intracellular region of the GPCR

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G protein binding shrinks the receptor-ligand contacts in the extracellular region

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Increased allostery between G protein and agonist in the GPCR-G protein complex

Dynamics of Dystrophin's Actin-Binding Domain

We have used pulsed electron paramagnetic resonance, calorimetry, and molecular dynamics simulations to examine the structural mechanism of binding for dystrophin's N-terminal actin-binding domain (ABD1) and compare it to utrophin's ABD1. Like other members of the spectrin superfamily, dystrophin's ABD1 consists of two calponin-homology (CH) domains, CH1 and CH2. Several mutations within dystrophin's ABD1 are associated with the development of severe degenerative muscle disorders Duchenne and Becker muscular dystrophies, highlighting the importance of understanding its structural biology. To investigate structural changes within dystrophin ABD1 upon binding to actin, we labeled the protein with spin probes and measured changes in inter-CH domain distance using double-electron electron resonance. Previous studies on the homologous protein utrophin showed that actin binding induces a complete structural opening of the CH domains, resulting in a highly ordered ABD1-actin complex. In this study, double-electron electron resonance shows that dystrophin ABD1 also undergoes a conformational opening upon binding F-actin, but this change is less complete and significantly more structurally disordered than observed for utrophin. Using molecular dynamics simulations, we identified a hinge in the linker region between the two CH domains that grants conformational flexibility to ABD1. The conformational dynamics of both dystrophin's and utrophin's ABD1 showed that compact conformations driven by hydrophobic interactions are preferred and that extended conformations are energetically accessible through a flat free-energy surface. Considering that the binding free energy of ABD1 to actin is on the order of 6-7 kcal/mole, our data are compatible with a mechanism in which binding to actin is largely dictated by specific interactions with CH1, but fine tuning of the binding affinity is achieved by the overlap between conformational ensembles of ABD1 free and bound to actin.

Nanosecond Dynamics Regulate the MIF-Induced Activity of CD74

Macrophage migration inhibitory factor (MIF) activates CD74, which leads to severe disorders including inflammation, autoimmune diseases and cancer under pathological conditions. Molecular dynamics (MD) simulations up to one microsecond revealed dynamical correlation between a residue located at the opening of one end of the MIF solvent channel, previously thought to be a consequence of homotrimerization, and residues in a distal region responsible for CD74 activation. Experiments verified the allosteric regulatory site and identified a pathway to this site via the MIF β-strands. The reported findings provide fundamental insights on a dynamic mechanism that controls the MIF-induced activation of CD74.

Decomposing Dynamical Couplings in Mutated scFv Antibody Fragments into Stabilizing and Destabilizing Effects

Conformational fluctuations within scFv antibodies are characterized by a novel perturbation-response decomposition of molecular dynamics trajectories. Both perturbation and response profiles are stratified into stabilizing and destabilizing conditions. The linker between the VH and VL domains exhibits the dominant dynamical response by being coupled to nearly the entire protein, responding to both stabilizing and destabilizing perturbations. Perturbations within complementarity-determining regions (CDR) induce rich behavior in dynamic response. Among many effects, stabilizing any CDR loop in the VH domain triggers a destabilizing response in all CDR loops in the VL domain and vice versa. Destabilizing residues within the VL domain are likely to stabilize all CDR loops in the VH domain, and, when these residues are not buried, the CDR loops in the VL domain are also likely to be stabilized. These effects, described by shifts in normal mode characteristics, initiate a propensity for dynamic allostery with possible functional implications in bispecific antibodies.

Uncovering GPCR and G Protein Function by Protein Structure Network Analysis

Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used for investigating structural communication in biomolecular systems. Information on the system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). This chapter reports on selected applications of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs) and G proteins. Strategies to highlight changes in structural communication caused by mutations, ligand and protein binding are described. Conserved amino acids, sites of misfolding mutations, or ligands acting as functional switches tend to behave as hubs in the native structure networks. Densely linked regions in the protein structure graphs could be identified as playing central roles in protein stability and function. Changes in the communication pathway fingerprints depending on the bound ligand or following amino acid mutation could be highlighted as well. A bridge between misfolding and misrouting could be established in rhodopsin mutants linked to inherited blindness. The analysis of native network perturbations by misfolding mutations served to infer key structural elements of protein responsiveness to small chaperones with implications for drug discovery.

Allosteric modulation of cardiac myosin dynamics by omecamtiv mecarbil

New promising avenues for the pharmacological treatment of skeletal and heart muscle diseases rely on direct sarcomeric modulators, which are molecules that can directly bind to sarcomeric proteins and either inhibit or enhance their activity. A recent breakthrough has been the discovery of the myosin activator omecamtiv mecarbil (OM), which has been shown to increase the power output of the cardiac muscle and is currently in clinical trials for the treatment of heart failure. While the overall effect of OM on the mechano-chemical cycle of myosin is to increase the fraction of myosin molecules in the sarcomere that are strongly bound to actin, the molecular basis of its action is still not completely clear. We present here a Molecular Dynamics study of the motor domain of human cardiac myosin bound to OM, where the effects of the drug on the dynamical properties of the protein are investigated for the first time with atomistic resolution. We found that OM has a double effect on myosin dynamics, inducing a) an increased coupling of the motions of the converter and lever arm subdomains to the rest of the protein and b) a rewiring of the network of dynamic correlations, which produces preferential communication pathways between the OM binding site and distant functional regions. The location of the residues responsible for these effects suggests possible strategies for the future development of improved drugs and the targeting of specific cardiomyopathy-related mutations.

Investigating Ebola virus pathogenicity using molecular dynamics

BACKGROUND

Ebolaviruses have been known to cause deadly disease in humans for 40 years and have recently been demonstrated in West Africa to be able to cause large outbreaks. Four Ebolavirus species cause severe disease associated with high mortality in humans. Reston viruses are the only Ebolaviruses that do not cause disease in humans. Conserved amino acid changes in the Reston virus protein VP24 compared to VP24 of other Ebolaviruses have been suggested to alter VP24 binding to host cell karyopherins resulting in impaired inhibition of interferon signalling, which may explain the difference in human pathogenicity. Here we used protein structural analysis and molecular dynamics to further elucidate the interaction between VP24 and KPNA5.

RESULTS

As a control experiment, we compared the interaction of wild-type and R137A-mutant (known to affect KPNA5 binding) Ebola virus VP24 with KPNA5. Results confirmed that the R137A mutation weakens direct VP24-KPNA5 binding and enables water molecules to penetrate at the interface. Similarly, Reston virus VP24 displayed a weaker interaction with KPNA5 than Ebola virus VP24, which is likely to reduce the ability of Reston virus VP24 to prevent host cell interferon signalling.

CONCLUSION

Our results provide novel molecular detail on the interaction of Reston virus VP24 and Ebola virus VP24 with human KPNA5. The results indicate a weaker interaction of Reston virus VP24 with KPNA5 than Ebola virus VP24, which is probably associated with a decreased ability to interfere with the host cell interferon response. Hence, our study provides further evidence that VP24 is a key player in determining Ebolavirus pathogenicity.

Structural modeling of the AhR:ARNT complex in the bHLH-PASA-PASB region elucidates the key determinants of dimerization

Elucidation of the dimerization process of the aryl hydrocarbon receptor (AhR) with the AhR nuclear translocator (ARNT) is crucial for understanding the mechanisms underlying the functional activity of AhR, including mediation of the toxicity of environmental contaminants. In this work, for the first time a structural model of the AhR:ARNT dimer encompassing the entire bHLH-PASA-PASB domain region is proposed. It is developed by using a template-based modeling approach, relying on the recently available crystallographic structures of two dimers of homologous systems in the bHLH-PAS family of proteins: the CLOCK:BMAL1 and the HIF2α:ARNT heterodimers. The structural and energetic characteristics of the modeled AhR:ARNT protein-protein interface are determined by evaluating the variations in solvent accessible surface area, the total binding free energy and the per-residue free energy contributions obtained by the MM-GBSA method and the Energy Decomposition Analysis. The analyses of the intricate network of inter-domain interactions at the dimerization interfaces provide insights into the key determinants of dimerization. These are confirmed by comparison of the computational findings with the available experimental mutagenesis and functional analysis data. The results presented here on the AhR:ARNT dimer structure and interactions provide a framework to start analyzing the mechanism of AhR transformation into its functional DNA binding form.

Allosteric regulation of metabolism in cancer: endogenous mechanisms and considerations for drug design

Alterations in metabolic processes have been linked to various diseases, including cancer. Although gene expression can dictate long-term metabolic adaptation, many metabolic changes found in cancer are associated with altered allosteric properties of the underlying enzymes. Small molecule-protein interactions and intracellular signalling converge to orchestrate these allosteric mechanisms, which, emerging evidence suggests, constitute a promising therapeutic avenue. In this review we focus on glucose and energy metabolism to illustrate the role of allostery in cancer physiology and we discuss approaches to streamline the process of targeting aberrant allosteric pathways with small molecules.

The Allostery Landscape: Quantifying Thermodynamic Couplings in Biomolecular Systems

Allostery plays a fundamental role in most biological processes. However, little theory is available to describe it outside of two-state models. Here we use a statistical mechanical approach to show that the allosteric coupling between two collective variables is not a single number, but instead a two-dimensional thermodynamic coupling function that is directly related to the mutual information from information theory and the copula density function from probability theory. On this basis, we demonstrate how to quantify the contribution of specific energy terms to this thermodynamic coupling function, enabling an approximate decomposition that reveals the mechanism of allostery. We illustrate the thermodynamic coupling function and its use by showing how allosteric coupling in the alanine dipeptide molecule contributes to the overall shape of the Φ/Ψ free energy surface, and by identifying the interactions that are necessary for this coupling.

Vibrational resonance, allostery, and activation in rhodopsin-like G protein-coupled receptors

G protein-coupled receptors are a large family of membrane proteins activated by a variety of structurally diverse ligands making them highly adaptable signaling molecules. Despite recent advances in the structural biology of this protein family, the mechanism by which ligands induce allosteric changes in protein structure and dynamics for its signaling function remains a mystery. Here, we propose the use of terahertz spectroscopy combined with molecular dynamics simulation and protein evolutionary network modeling to address the mechanism of activation by directly probing the concerted fluctuations of retinal ligand and transmembrane helices in rhodopsin. This approach allows us to examine the role of conformational heterogeneity in the selection and stabilization of specific signaling pathways in the photo-activation of the receptor. We demonstrate that ligand-induced shifts in the conformational equilibrium prompt vibrational resonances in the protein structure that link the dynamics of conserved interactions with fluctuations of the active-state ligand. The connection of vibrational modes creates an allosteric association of coupled fluctuations that forms a coherent signaling pathway from the receptor ligand-binding pocket to the G-protein activation region. Our evolutionary analysis of rhodopsin-like GPCRs suggest that specific allosteric sites play a pivotal role in activating structural fluctuations that allosterically modulate functional signals.

Mechanisms for allosteric activation of protease DegS by ligand binding and oligomerization as revealed from molecular dynamics simulations

A local perturbation of a protein may lead to functional changes at some distal site, a phenomenon denoted as allostery. Here, we study the allosteric control of a protease using molecular dynamics simulations. The system considered is the bacterial protein DegS which includes a protease domain activated on ligand binding to an adjacent PDZ domain. Starting from crystallographic structures of DegS homo-trimers, we perform simulations of the ligand-free and -bound state of DegS at equilibrium. Considering a single protomer only, the trimeric state was mimicked by applying restraints on the residues in contact with other protomers in the DegS trimer. In addition, the bound state was also simulated without any restraints to mimic the monomer. Our results suggest that not only ligand release but also disassembly of a DegS trimer inhibits proteolytic activity. Considering various observables for structural changes, we infer allosteric pathways from the interface with other protomers to the active site. Moreover, we study how ligand release leads to (i) catalytically relevant changes involving residues 199-201 and (ii) a transition from a stretched to a bent conformation for residues 217-219 (which prohibits proper substrate binding). Finally, based on ligand-induced C_α shifts we identify residues in contact with other protomers in the DegS trimer that likely transduce the perturbation from ligand release from a given protomer to adjacent protomers. These residues likely play a key role in the experimentally known effect of ligand release from a protomer on the proteolytic activity of the other protomers. Proteins 2016; 84:1690-1705. © 2016 Wiley Periodicals, Inc.

Allosteric communication pipelines in G-protein-coupled receptors

The binding of ligands to G-protein-coupled receptors (GPCRs) in the extracellular region transmits the signal to the intracellular region to initiate coupling to effector proteins. The mechanism of this allosteric communication remains largely unexplored. Knowledge of the residues involved in the pipeline of the allosteric communication from the extracellular to the intracellular region will provide means to (a) design ligands with bias in potency towards one signaling pathway over others, and (b) design allosteric modulators that show subtype selectivity in GPCRs. In this review we describe the current state of the computational methods that provide insights into the allosteric communication in GPCRs and elucidate how this information can be used to design allosteric modulators.

Cluster analysis of molecular simulation trajectories for systems where both conformation and orientation of the sampled states are important

Clustering methods have been widely used to group together similar conformational states from molecular simulations of biomolecules in solution. For applications such as the interaction of a protein with a surface, the orientation of the protein relative to the surface is also an important clustering parameter because of its potential effect on adsorbed-state bioactivity. This study presents cluster analysis methods that are specifically designed for systems where both molecular orientation and conformation are important, and the methods are demonstrated using test cases of adsorbed proteins for validation. Additionally, because cluster analysis can be a very subjective process, an objective procedure for identifying both the optimal number of clusters and the best clustering algorithm to be applied to analyze a given dataset is presented. The method is demonstrated for several agglomerative hierarchical clustering algorithms used in conjunction with three cluster validation techniques. © 2016 Wiley Periodicals, Inc.

The Phylogenetic Signature Underlying ATP Synthase c-Ring Compliance

The proton-driven ATP synthase (FOF1) is comprised of two rotary, stepping motors (FO and F1) coupled by an elastic power transmission. The elastic compliance resides in the rotor module that includes the membrane-embedded FO c-ring. Proton transport by FO is firmly coupled to the rotation of the c-ring relative to other FO subunits (ab2). It drives ATP synthesis. We used a computational method to investigate the contribution of the c-ring to the total elastic compliance. We performed principal component analysis of conformational ensembles built using distance constraints from the bovine mitochondrial c-ring x-ray structure. Angular rotary twist, the dominant ring motion, was estimated to show that the c-ring accounted in part for the measured compliance. Ring rotation was entrained to rotation of the external helix within each hairpin-shaped c-subunit in the ring. Ensembles of monomer and dimers extracted from complete c-rings showed that the coupling between collective ring and the individual subunit motions was independent of the size of the c-ring, which varies between organisms. Molecular determinants were identified by covariance analysis of residue coevolution and structural-alphabet-based local dynamics correlations. The residue coevolution gave a readout of subunit architecture. The dynamic couplings revealed that the hinge for both ring and subunit helix rotations was constructed from the proton-binding site and the adjacent glycine motif (IB-GGGG) in the midmembrane plane. IB-GGGG motifs were linked by long-range couplings across the ring, while intrasubunit couplings connected the motif to the conserved cytoplasmic loop and adjacent segments. The correlation with principal collective motions shows that the couplings underlie both ring rotary and bending motions. Noncontact couplings between IB-GGGG motifs matched the coevolution signal as well as contact couplings. The residue coevolution reflects the physiological importance of the dynamics that may link proton transfer to ring compliance.

From Binding-Induced Dynamic Effects in SH3 Structures to Evolutionary Conserved Sectors

Src Homology 3 domains are ubiquitous small interaction modules known to act as docking sites and regulatory elements in a wide range of proteins. Prior experimental NMR work on the SH3 domain of Src showed that ligand binding induces long-range dynamic changes consistent with an induced fit mechanism. The identification of the residues that participate in this mechanism produces a chart that allows for the exploration of the regulatory role of such domains in the activity of the encompassing protein. Here we show that a computational approach focusing on the changes in side chain dynamics through ligand binding identifies equivalent long-range effects in the Src SH3 domain. Mutation of a subset of the predicted residues elicits long-range effects on the binding energetics, emphasizing the relevance of these positions in the definition of intramolecular cooperative networks of signal transduction in this domain. We find further support for this mechanism through the analysis of seven other publically available SH3 domain structures of which the sequences represent diverse SH3 classes. By comparing the eight predictions, we find that, in addition to a dynamic pathway that is relatively conserved throughout all SH3 domains, there are dynamic aspects specific to each domain and homologous subgroups. Our work shows for the first time from a structural perspective, which transduction mechanisms are common between a subset of closely related and distal SH3 domains, while at the same time highlighting the differences in signal transduction that make each family member unique. These results resolve the missing link between structural predictions of dynamic changes and the domain sectors recently identified for SH3 domains through sequence analysis.

Small protein domains as Src Homology 3 often act as docking sites and serve as regulatory elements. To understand their role in the regulation of a protein’s activity, one needs to understand how their backbone and sidechain dynamics are affected when binding to peptides. We have therefore computationally analyzed eight different SH3 domain structures, predicting dynamical effects induced by binding through our MCIT approach that has been shown to correlate well with experimental data. We show first that binding the Src SH3 domain triggers a particular cascade of dynamic effects, which are compatible with an induced fit mechanism reported before. We then combined the predictions for the eight SH3 domains into different consensus models, with the aim of analyzing, for the first time from a structural perspective, commonalities and differences in the transduction mechanisms among these SH3 domains. These consensus results are, on one hand, in agreement with the domain sectors recently identified for the entire family of SH3 domains. On the other hand, they reveal also that differences exist between the different subgroups that were studied here, requiring extensive experimental investigations of the importance of these differences for the proteins wherein these SH3 domains can be found.

Structure network analysis to gain insights into GPCR function

G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM–NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM–NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor.

PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity.

Using Local States To Drive the Sampling of Global Conformations in Proteins

Conformational changes associated with protein function often occur beyond the time scale currently accessible to unbiased molecular dynamics (MD) simulations, so that different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in precalculated libraries known as structural alphabets (SA), can be used to explore the landscape of protein conformations in MD simulations. We find that (a) enhancing the sampling of native local states in both metadynamics and steered MD simulations allows the recovery of global folded states in small proteins; (b) folded states can still be recovered when the amount of information on the native local states is reduced by using a low-resolution version of the SA, where states are clustered into macrostates; and (c) sequences of SA states derived from collections of structural motifs can be used to sample alternative conformations of preselected protein regions. The present findings have potential impact on several applications, ranging from protein model refinement to protein folding and design.

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Long-Range Conformational Response of a PDZ Domain to Ligand Binding and Release: A Molecular Dynamics Study

The binding of a ligand to a protein may induce long-range structural or dynamical changes in the biomacromolecule even at sites physically well separated from the binding pocket. A system for which such behavior has been widely discussed is the PDZ2 domain of human tyrosine phosphatase 1E. Here, we present results from equilibrium trajectories of the PDZ2 domain in the free and ligand-bound state, as well as nonequilibrium simulations of the relaxation of PDZ2 after removal of its peptide ligand. The study reveals changes in inter-residue contacts, backbone dihedral angles, and C(α) positions upon ligand release. Our findings show a long-range conformational response of the PDZ2 domain to ligand release in the form of a collective shift of the secondary structure elements α2, β2, β3, α1-β4, and the C terminal loop relative to the rest of the protein away from the N-terminus, and a shift of the loops β2-β3 and β1-β2 in the opposite direction. The shifts lead to conformational changes in the backbone, especially in the β2-β3 loop but also in the β5-α2 and the α2-β6 loop, and are accompanied by changes of inter-residue contacts mainly within the β2-β3 loop as well as between the α2 helix and other segments. The residues showing substantial changes of inter-residue contacts, backbone conformations, or C(α) positions are considered "key residues" for the long-range conformational response of PDZ2. By comparing these residues with various sets of residues highlighted by previous studies of PDZ2, we investigate the statistical correlation of the various approaches. Interestingly, we find a considerable correlation of our findings with several works considering structural changes but no significant correlations with approaches considering energy flow or networks based on inter-residue energies.

The dynamics of the β-propeller domain in Kelch protein KLHL40 changes upon nemaline myopathy-associated mutation

The nemaline myopathy-associated E528K mutation in the KLHL40 alters the communication between the Kelch propeller blades.

Differences in allosteric communication pipelines in the inactive and active states of a GPCR

G-protein-coupled receptors (GPCRs) are membrane proteins that allosterically transduce the signal of ligand binding in the extracellular (EC) domain to couple to proteins in the intracellular (IC) domain. However, the complete pathway of allosteric communication from the EC to the IC domain, including the role of individual amino acids in the pathway is not known. Using the correlation in torsion angle movements calculated from microseconds-long molecular-dynamics simulations, we elucidated the allosteric pathways in three different conformational states of β2-adrenergic receptor (β2AR): 1), the inverse-agonist-bound inactive state; 2), the agonist-bound intermediate state; and (3), the agonist- and G-protein-bound fully active state. The inactive state is less dynamic compared with the intermediate and active states, showing dense clusters of allosteric pathways (allosteric pipelines) connecting the EC with the IC domain. The allosteric pipelines from the EC domain to the IC domain are weakened in the intermediate state, thus decoupling the EC domain from the IC domain and making the receptor more dynamic compared with the other states. Also, the orthosteric ligand-binding site becomes the initiator region for allosteric communication in the intermediate state. This finding agrees with the paradigm that the nature of the agonist governs the specific signaling state of the receptor. These results provide an understanding of the mechanism of allosteric communication in class A GPCRs. In addition, our analysis shows that mutations that affect the ligand efficacy, but not the binding affinity, are located in the allosteric pipelines. This clarifies the role of such mutations, which has hitherto been unexplained.

Anatomy of protein disorder, flexibility and disease-related mutations

Integration of protein structural information with human genetic variation and pathogenic mutations is essential to understand molecular mechanisms associated with the effects of polymorphisms on protein interactions and cellular processes. We investigate occurrences of non-synonymous SNPs in ordered and disordered protein regions by systematic mapping of common variants and disease-related SNPs onto these regions. We show that common variants accumulate in disordered regions; conversely pathogenic variants are significantly depleted in disordered regions. These different occurrences of pathogenic and common SNPs can be attributed to a negative selection on random mutations in structurally highly constrained regions. New approaches in the study of quantitative effects of pathogenic-related mutations should effectively account for all the possible contexts and relative functional constraints in which the sequence variation occurs.