Structural changes involved in protein binding correlate with intrinsic motions of proteins in the unbound state

On the conservation of the slow conformational dynamics within the amino acid kinase family: NAGK the paradigm

N-Acetyl-L-Glutamate Kinase (NAGK) is the structural paradigm for examining the catalytic mechanisms and dynamics of amino acid kinase family members. Given that the slow conformational dynamics of the NAGK (at the microseconds time scale or slower) may be rate-limiting, it is of importance to assess the mechanisms of the most cooperative modes of motion intrinsically accessible to this enzyme. Here, we present the results from normal mode analysis using an elastic network model representation, which shows that the conformational mechanisms for substrate binding by NAGK strongly correlate with the intrinsic dynamics of the enzyme in the unbound form. We further analyzed the potential mechanisms of allosteric signalling within NAGK using a Markov model for network communication. Comparative analysis of the dynamics of family members strongly suggests that the low-frequency modes of motion and the associated intramolecular couplings that establish signal transduction are highly conserved among family members, in support of the paradigm sequence→structure→dynamics→function.

During the last 20 years both the experimental and computational communities have provided strong evidence that proteins cannot be regarded as static entities, but as intrinsically flexible molecules that exploit their fluctuation dynamics for catalytic and ligand-binding events, as well as for allosteric regulation. This intrinsic dynamics is encoded in the protein structure and, therefore, those proteins with similar folding should share dynamic features essential to their biological function. In this work, we have applied an Elastic Network Model to predict the large-amplitude dynamics of different enzymes belonging to the same protein family (Amino Acid Kinase family). Subsequent comparison of the dynamics of these proteins reveals that this protein family follows the same dynamic pattern. The present results are strongly supported by experimental data and provide new insights into the performance of biological function by these enzymes. The investigation presented here provides us with a useful framework to identify dynamic fingerprints among proteins with structural similarities.

A perturbative view of protein structural variation

It was recently found that the lowest-energy collective normal modes dominate the evolutionary divergence of protein structures. This was attributed to a presumed functional importance of such motions, i.e., to natural selection. In contrast to this selectionist explanation, we proposed that the observed behavior could be just the expected physical response of proteins to random mutations. This proposal was based on the success of a linearly forced elastic network model (LFENM) of mutational effects on structure to account for the observed pattern of structural divergence. Here, to further test the mutational explanation and the LFENM, we analyze the structural differences observed not only in homologous (globin-like) proteins but also in unselected experimentally engineered myoglobin mutants and in wild-type variants subject to other perturbations such as ligand-binding and pH changes. We show that the lowest normal modes dominate structural change in all the cases considered and that the LFENM reproduces this behavior quantitatively. The collective nature of the lowest normal modes results in global conformational changes that depend little on the exact nature or location of the perturbation. Significantly, the evolutionarily conserved structural core matches the regions observed to be more robust with respect to mutations, so that the core would be more conserved even under unselected random mutations. In a word, the observed patterns of structural variation can be seen as the natural response of proteins to perturbations and can be adequately modeled using the LFENM, which serves as a common framework to relate a priori different phenomena.

Multiscale network model for large protein dynamics

Protein dynamics is essential for gaining insight into biological functions of proteins. Although protein dynamics is well delineated by molecular model, the molecular model is computationally prohibited for simulating large protein structures. In this work, we provide a multiscale network model (MNM) that allows the efficient computation on low-frequency normal modes related to structural deformation of proteins as well as dynamic behavior of functional sites. Specifically, MNM consists of two regions, one of which is described as a low-resolution structure, while the other is dictated by a high-resolution structure. The high-resolution regions using all alpha carbons of the protein are mainly binding site parts, which play a critical function in molecules, while the low-resolution parts are constructed from a further coarse-grained model (not using all alpha carbons). The feasibility of MNM to observe the cooperative motion of a protein structure was validated. It was shown that the MNM enables us to understand functional motion of proteins with computational efficiency.

Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales

An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of 1/2 a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented.

Solvent-induced backbone fluctuations and the collective librational dynamics of lysozyme studied by terahertz spectroscopy

THz spectroscopy is used to investigate the dynamics of the globular protein hen egg white lysozyme under varying hydration and temperature conditions. An analysis of the experimental spectra has revealed that the amount of solvent in the hydration shell has a strong influence on the low-frequency protein conformational dynamics and also the arrangement of hydrogen bonds in the protein secondary structure. Furthermore at a hydration level >0.2 we identify collective backbone fluctuations in the protein secondary structure that are not present at low hydration. It is possible that these solvent induced modes are important for the biological function of the protein.

T cell receptor cross-reactivity directed by antigen-dependent tuning of peptide-MHC molecular flexibility

T cell-mediated immunity requires T cell receptor (TCR) cross-reactivity, the mechanisms behind which remain incompletely elucidated. The alphabeta TCR A6 recognizes both the Tax (LLFGYPVYV) and Tel1p (MLWGYLQYV) peptides presented by the human class I MHC molecule HLA-A2. Here we found that although the two ligands are ideal structural mimics, they form substantially different interfaces with A6, with conformational differences in the peptide, the TCR, and unexpectedly, the MHC molecule. The differences between the Tax and Tel1p ternary complexes could not be predicted from the free peptide-MHC structures and are inconsistent with a traditional induced-fit mechanism. Instead, the differences were attributable to peptide and MHC molecular motion present in Tel1p-HLA-A2 but absent in Tax-HLA-A2. Differential "tuning" of the dynamic properties of HLA-A2 by the Tax and Tel1p peptides thus facilitates cross-recognition and impacts how structural diversity can be presented to and accommodated by receptors of the immune system.

Identification of specificity and promiscuity of PDZ domain interactions through their dynamic behavior

PDZ domains (PDZs), the most common interaction domain proteins, play critical roles in many cellular processes. PDZs perform their job by binding specific protein partners. However, they are very promiscuous, binding to more than one protein, yet selective at the same time. We examined the binding related dynamics of various PDZs to have insight about their specificity and promiscuity. We used full atomic normal mode analysis and a modified coarse-grained elastic network model to compute the binding related dynamics. In the latter model, we introduced specificity for each single parameter constant and included the solvation effect implicitly. The modified model, referred to as specific-Gaussian Network Model (s-GNM), highlights some interesting differences in the conformational changes of PDZs upon binding to Class I or Class II type peptides. By clustering the residue fluctuation profiles of PDZs, we have shown: (i) binding selectivities can be discriminated from their dynamics, and (ii) the dynamics of different structural regions play critical roles for Class I and Class II specificity. s-GNM is further tested on a dual-specific PDZ which showed only Class I specificity when a point mutation exists on the betaA-betaB loop. We observe that the binding dynamics change consistently in the mutated and wild type structures. In addition, we found that the binding induced fluctuation profiles can be used to discriminate the binding selectivity of homolog structures. These results indicate that s-GNM can be a powerful method to study the changes in binding selectivities for mutant or homolog PDZs.

The role of dynamic conformational ensembles in biomolecular recognition

Molecular recognition is central to all biological processes. For the past 50 years, Koshland's 'induced fit' hypothesis has been the textbook explanation for molecular recognition events. However, recent experimental evidence supports an alternative mechanism. 'Conformational selection' postulates that all protein conformations pre-exist, and the ligand selects the most favored conformation. Following binding the ensemble undergoes a population shift, redistributing the conformational states. Both conformational selection and induced fit appear to play roles. Following binding by a primary conformational selection event, optimization of side chain and backbone interactions is likely to proceed by an induced fit mechanism. Conformational selection has been observed for protein-ligand, protein-protein, protein-DNA, protein-RNA and RNA-ligand interactions. These data support a new molecular recognition paradigm for processes as diverse as signaling, catalysis, gene regulation and protein aggregation in disease, which has the potential to significantly impact our views and strategies in drug design, biomolecular engineering and molecular evolution.

Allosteric Conformational Transition in Adenylate Kinase: Dynamic Correlations and Implication for Allostery

An essential aspect of protein science is to determine the deductive relationship between structure, dynamics, and various sets of functions. The role of dynamics is currently challenging our understanding of protein functions, both experimentally and theoretically. To verify the internal fluctuations and dynamics correlations in an enzyme protein undergoing conformational transitions, we have applied a coarse-grained dynamics algorithm using the elastic network model for adenylate kinase. Normal mode analysis reveals possible dynamical and allosteric pathways for the transition between the open and the closed states of adenylate kinase. As the ligands binding induces significant flexibility changes of the nucleotides monophosphate (NMP) domain and adenosine triphosphate (ATP) domain, the diagonalized correlation between different structural transition states shows that most correlated motions occur between the NMP domain and the helices surrounding the ATP domain. The simultaneous existence of positive and negative correlations indicates that the conformational changes of adenylate kinase take place in an allosteric manner. Analyses of the cumulated normal mode overlap coefficients and long-range correlated motion provide new insights of operating mechanisms and dynamics of adenylate kinase. They also suggest a quantitative dynamics criterion for determining the allosteric cooperativity, which may be applicable to other proteins.

Improving structure-based function prediction using molecular dynamics

The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca(2+) binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods.

Conformational selection and induced fit mechanism underlie specificity in noncovalent interactions with ubiquitin

Noncovalent binding interactions between proteins are the central physicochemical phenomenon underlying biological signaling and functional control on the molecular level. Here, we perform an extensive structural analysis of a large set of bound and unbound ubiquitin conformers and study the level of residual induced fit after conformational selection in the binding process. We show that the region surrounding the binding site in ubiquitin undergoes conformational changes that are significantly more pronounced compared with the whole molecule on average. We demonstrate that these induced-fit structural adjustments are comparable in magnitude to conformational selection. Our final model of ubiquitin binding blends conformational selection with the subsequent induced fit and provides a quantitative measure of their respective contributions.

REACH coarse-grained normal mode analysis of protein dimer interaction dynamics

The REACH (realistic extension algorithm via covariance Hessian) coarse-grained biomolecular simulation method is a self-consistent multiscale approach directly mapping atomistic molecular dynamics simulation results onto a residue-scale model. Here, REACH is applied to calculate the dynamics of protein-protein interactions. The intra- and intermolecular fluctuations and the intermolecular vibrational densities of states derived from atomistic molecular dynamics are well reproduced by the REACH normal modes. The phonon dispersion relations derived from the REACH lattice dynamics model of crystalline ribonuclease A are also in satisfactory agreement with the corresponding all-atom results. The REACH model demonstrates that increasing dimer interaction strength decreases the translational and rotational intermolecular vibrational amplitudes, while their vibrational frequencies are relatively unaffected. A comparative study of functionally interacting biological dimers with crystal dimers, which are formed artificially via crystallization, reveals a relation between their static structures and the interprotein dynamics: i.e., the consequence of the extensive interfaces of biological dimers is reduction of the intermonomer translational and rotational amplitudes, but not the frequencies.

Nicotinic receptors: allosteric transitions and therapeutic targets in the nervous system

Nicotinic receptors - a family of ligand-gated ion channels that mediate the effects of the neurotransmitter acetylcholine - are among the most well understood allosteric membrane proteins from a structural and functional perspective. There is also considerable interest in modulating nicotinic receptors to treat nervous-system disorders such as Alzheimer's disease, schizophrenia, depression, attention deficit hyperactivity disorder and tobacco addiction. This article describes both recent advances in our understanding of the assembly, activity and conformational transitions of nicotinic receptors, as well as developments in the therapeutic application of nicotinic receptor ligands, with the aim of aiding novel drug discovery by bridging the gap between these two rapidly developing fields.

The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding

The conformational flexibility of target proteins continues to be a major challenge in accurate modeling of protein-inhibitor interactions. A fundamental issue, yet to be clarified, is whether the observed conformational changes are controlled by the protein or induced by the inhibitor. Although the concept of induced fit has been widely adopted for describing the structural changes that accompany ligand binding, there is growing evidence in support of the dominance of proteins' intrinsic dynamics which has been evolutionarily optimized to accommodate its functional interactions. The wealth of structural data for target proteins in the presence of different ligands now permits us to make a critical assessment of the balance between these two effects in selecting the bound forms. We focused on three widely studied drug targets, HIV-1 reverse transcriptase, p38 MAP kinase, and cyclin-dependent kinase 2. A total of 292 structures determined for these enzymes in the presence of different inhibitors and unbound form permitted us to perform an extensive comparative analysis of the conformational space accessed upon ligand binding, and its relation to the intrinsic dynamics before ligand binding as predicted by elastic network model analysis. Our results show that the ligand selects the conformer that best matches its structural and dynamic properties among the conformers intrinsically accessible to the protein in the unliganded form. The results suggest that simple but robust rules encoded in the protein structure play a dominant role in predefining the mechanisms of ligand binding, which may be advantageously exploited in designing inhibitors.

Large Protein Dynamics Described by Hierarchical-Component Mode Synthesis

Protein dynamics has played a pivotal role in understanding the biological function of protein. For investigation of such dynamics, normal-mode analysis (NMA) has been broadly employed with atomistic model and/or coarse-grained models such as elastic network model (ENM). For large protein complexes, NMA with even ENM encounters the expensive computational process such as diagonalization of Hessian (stiffness) matrix. Here, we suggest the hierarchical-component mode synthesis (hCMS), which allows the fast computation of low-frequency normal modes related to conformational change. Specifically, a large protein structure is regarded as a combination of several structural units, for which the eigen-value problem is utilized for obtaining the frequencies and their normal modes for each structural unit, and consequently, such frequencies and normal modes are assembled with geometrical constraint for interface between structural units in order to find the low-frequency normal modes of a large protein complex. It is shown that hCMS is able to provide the normal modes with accuracy, quantitatively comparable to those of original NMA. This implies that hCMS may enable the computationally efficient analysis of large protein dynamics.

Evidences of xenon-induced structural changes in the active site of cyano-metmyoglobins: a 1H NMR study

Using xenon atoms as a biomolecular probe raises the concern of whether they may influence in some way the molecular and electronic structure of the system under study. In this paper, the relevance of guest-host interactions in xenon complexes with paramagnetic myoglobins (Mbs) is thoroughly analyzed, and the issue about the use of xenon to detect and characterize voids within flexible biomolecules is critically discussed. A detailed 1H NMR study useful for describing the hydrophobic cavities close to the active site of low-spin ferric myoglobins with respect to their interaction with the xenon atom is presented. The method is subsequently validated by the analysis of Xe-Mb with two different myoglobins, extracted from horse and pig. These myoglobins differ by 14 amino acids. One of these, Ile142 in horse Mb, is located in the proximal cavity, which is the main xenon binding site in horse Mb, and is replaced by Met142 in pig Mb. We demonstrated specific behaviors associated with the capacity of each of the two myoglobins to bind xenon and provided site-specific information on the host-guest interaction. Moreover, 1H NMR measurements produce a picture of xenon-related local distortions of the protein, associated with a functionally relevant residue located right at the active site, the proximal hystidine E7(His93). According to the 1H NMR data, xenon induces the tilt of the residue His93 relative to the heme plane and consequently causes an alteration of the magnetic axes. Similar conclusions are obtained both for pig cyano-myoglobin and for horse cyano-myoglobin, the structural deformation being in the former of minor entity.

Intrinsic dynamics of restriction endonuclease EcoO109I studied by molecular dynamics simulations and X-ray scattering data analysis

EcoO109I is a type II restriction endonuclease that functions as a dimer in solution. Upon DNA binding to the enzyme, the two subunits rotate counterclockwise relative to each other, as the two catalytic domains undergo structural changes to capture the cognate DNA. Using a 150-ns molecular dynamics simulation, we investigated the intrinsic dynamics of the DNA-free enzyme in solution to elucidate the relationship between enzyme dynamics and structural changes. The simulation revealed that the enzyme is considerably flexible, and thus exhibits large fluctuations in the radius of gyration. The small-angle x-ray scattering profile calculated from the simulation, including scattering from explicit hydration water, was in agreement with the experimentally observed profile. Principal component analysis revealed that the major dynamics were represented by the open-close and counterclockwise motions: the former is required for the enzyme to access DNA, whereas the latter corresponds to structural changes upon DNA binding. Furthermore, the intrinsic dynamics in the catalytic domains were consistent with motions capturing the cognate DNA. These results indicate that the structure of EcoO109I is intrinsically flexible in the direction of its functional movement, to facilitate effective structural changes for sequence-specific DNA recognition and processing.

Dynamics and energetics: a consensus analysis of the impact of calcium on EF-CaM protein complex

We have studied the relationship between dynamical correlations and energetic contributions in an attempt to model the transmission of information inside protein-protein complexes. The complex formed between the edema factor (EF) of Bacillus anthracis and calmodulin (CaM) was taken as an example, as the formation and stability of the complex depend on the calcium complexation level. The effect of calcium through EF-CaM residue network has been investigated with various approaches: 1), the elastic network model; 2), the local feature analysis; 3), the generalized correlations; and 4), the energetic dependency maps (EDMs), on 15-ns molecular dynamics simulations of the complex loaded with 0, 2, or 4 Ca2+ ions. The elastic network model correctly describes the basic architecture of the complex but is poorly sensitive to the level of calcium compared to the other methods. The local feature analysis allows us to characterize the local dynamics of the complex and the propagation of the calcium signal through CaM. The analyses of global dynamics and energetics--through generalized correlations and EDMs--provide a comprehensive picture of EF-CaM architecture and can be unified by using the concept of residue network connectedness. A medium connectedness, defined as the ability of each residue to communicate with all remaining parts of the complex, is observed for the 2Ca2+ level, which was experimentally identified as the most stable form of EF-CaM. The hierarchy of relative stabilities given by the EDMs sheds a new light on the EF-CaM interaction mechanism described experimentally and supports an organization of the complex architecture centered around nucleation points.

Rapid sampling of molecular motions with prior information constraints

Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion.

Allosteric communication occurs via networks of tertiary and quaternary motions in proteins

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that allosteric communication in proteins relies upon networks of quaternary (collective, rigid-body) and tertiary (residue-residue contact) motions. We argue that cyclic topology of these networks is necessary for allosteric communication. An automated algorithm identifies rigid bodies from the displacement between the inactive and the active structures and constructs "quaternary networks" from these rigid bodies and the substrate and effector ligands. We then integrate quaternary networks with a coarse-grained representation of contact rearrangements to form "global communication networks" (GCNs). The GCN reveals allosteric communication among all substrate and effector sites in 15 of 18 multidomain and multimeric proteins, while tertiary and quaternary networks exhibit such communication in only 4 and 3 of these proteins, respectively. Furthermore, in 7 of the 15 proteins connected by the GCN, 50% or more of the substrate-effector paths via the GCN are "interdependent" paths that do not exist via either the tertiary or the quaternary network. Substrate-effector "pathways" typically are not linear but rather consist of polycyclic networks of rigid bodies and clusters of rearranging residue contacts. These results argue for broad applicability of allosteric communication based on structural changes and demonstrate the utility of the GCN. Global communication networks may inform a variety of experiments on allosteric proteins as well as the design of allostery into non-allosteric proteins.

Coarse-grained dynamics of the receiver domain of NtrC: fluctuations, correlations and implications for allosteric cooperativity

Receiver domains are key molecular switches in bacterial signaling. Structural studies have shown that the receiver domain of the nitrogen regulatory protein C (NtrC) exists in a conformational equilibrium encompassing both inactive and active states, with phosphorylation of Asp54 allosterically shifting the equilibrium towards the active state. To analyze dynamical fluctuations and correlations in NtrC as it undergoes activation, we have applied a coarse-grained dynamics algorithm using elastic network models. Normal mode analysis reveals possible dynamical pathways for the transition of NtrC from the inactive state to the active state. The diagonalized correlation between the inactive and the active (phosphorylated) state shows that most correlated motions occur around the active site of Asp54 and in the region Thr82 to Tyr101. This indicates a coupled correlation of dynamics in the "Thr82-Tyr101" motion. With phosphorylation inducing significant flexibility changes around the active site and alpha3 and alpha4 helices, we find that this activation makes the active-site region and the loops of alpha3/beta4 and alpha4/beta5 more stable. This means that phosphorylation entropically favors the receiver domain in its active state, and the induced conformational changes occur in an allosteric manner. Analyses of the local flexibility and long-range correlated motion also suggest a dynamics criterion for determining the allosteric cooperativity of NtrC, and may be applicable to other proteins.

Conformational changes and flexibility in T-cell receptor recognition of peptide-MHC complexes

A necessary feature of the immune system, TCR (T-cell receptor) cross-reactivity has been implicated in numerous autoimmune pathologies and is an underlying cause of transplant rejection. Early studies of the interactions of alphabeta TCRs (T-cell receptors) with their peptide-MHC ligands suggested that conformational plasticity in the TCR CDR (complementarity determining region) loops is a dominant contributor to T-cell cross-reactivity. Since these initial studies, the database of TCRs whose structures have been solved both bound and free is now large enough to permit general conclusions to be drawn about the extent of TCR plasticity and the types and locations of motion that occur. In the present paper, we review the conformational differences between free and bound TCRs, quantifying the structural changes that occur and discussing their possible roles in specificity and cross-reactivity. We show that, rather than undergoing major structural alterations or 'folding' upon binding, the majority of TCR CDR loops shift by relatively small amounts. The structural changes that do occur are dominated by hinge-bending motions, with loop remodelling usually occurring near loop apexes. As predicted from previous studies, the largest changes are in the hypervariable CDR3alpha and CDR3beta loops, although in some cases the germline-encoded CDR1alpha and CDR2alpha loops shift in magnitudes that approximate those of the CDR3 loops. Intriguingly, the smallest shifts are in the germline-encoded loops of the beta-chain, consistent with recent suggestions that the TCR beta domain may drive ligand recognition.

In silico models for the human alpha4beta2 nicotinic acetylcholine receptor

The neuronal alpha4beta2 nicotinic acetylcholine receptor (nAChR) is one of the most widely expressed nAChR subtypes in the brain. Its subunits have high sequence identity (54 and 46% for alpha4 and beta2, respectively) with alpha and beta subunits in Torpedo nAChR. Using the known structure of the Torpedo nAChR as a template, the closed-channel structure of the alpha4beta2 nAChR was constructed through homology modeling. Normal-mode analysis was performed on this closed structure and the resulting lowest frequency mode was applied to it for a "twist-to-open" motion, which increased the minimum pore radius from 2.7 to 3.4 A and generated an open-channel model. Nicotine could bind to the predicted agonist binding sites in the open-channel model but not in the closed one. Both models were subsequently equilibrated in a ternary lipid mixture via extensive molecular dynamics (MD) simulations. Over the course of 11 ns MD simulations, the open channel remained open with filled water, but the closed channel showed a much lower water density at its hydrophobic gate comprised of residues alpha4-V259 and alpha4-L263 and their homologous residues in the beta2 subunits. Brownian dynamics simulations of Na+ permeation through the open channel demonstrated a current-voltage relationship that was consistent with experimental data on the conducting state of alpha4beta2 nAChR. Besides establishment of the well-equilibrated closed- and open-channel alpha4beta2 structural models, the MD simulations on these models provided valuable insights into critical factors that potentially modulate channel gating. Rotation and tilting of TM2 helices led to changes in orientations of pore-lining residue side chains. Without concerted movement, the reorientation of one or two hydrophobic side chains could be enough for channel opening. The closed- and open-channel structures exhibited distinct patterns of electrostatic interactions at the interface of extracellular and transmembrane domains that might regulate the signal propagation of agonist binding to channel opening. A potential prominent role of the beta2 subunit in channel gating was also elucidated in the study.

Thermodynamics of T-cell receptor-peptide/MHC interactions: progress and opportunities

alphabeta T-cell receptors (TCRs) recognize peptide antigens presented by class I or class II major histocompatibility complex molecules (pMHC). Here we review the use of thermodynamic measurements in the study of TCR-pMHC interactions, with attention to the diversity in binding thermodynamics and how this is related to the variation in TCR-pMHC interfaces. We show that there is no enthalpic or entropic signature for TCR binding; rather, enthalpy and entropy changes vary in a compensatory manner that reflects a narrow free energy window for the interactions that have been characterized. Binding enthalpy and entropy changes do not correlate with structural features such as buried surface area or the number of hydrogen bonds within TCR-pMHC interfaces, possibly reflecting the myriad of contributors to binding thermodynamics, but likely also reflecting a reliance on van't Hoff over calorimetric measurements and the unaccounted influence of equilibria linked to binding. TCR-pMHC binding heat capacity changes likewise vary considerably. In some cases, the heat capacity changes are consistent with conformational differences between bound and free receptors, but there is little data indicating these conformational differences represent the need to organize disordered CDR loops. In this regard, we discuss how thermodynamics may provide additional insight into conformational changes occurring upon TCR binding. Finally, we highlight opportunities for the further use of thermodynamic measurements in the study of TCR-pMHC interactions, not only for understanding TCR binding in general, but also for understanding specifics of individual interactions and the engineering of TCRs with desired molecular recognition properties.

Cooperative transition between open and closed conformations in potassium channels

Potassium (K+) ion channels switch between open and closed conformations. The nature of this important transition was revealed by comparing the X-ray crystal structures of the MthK channel from Methanobacterium thermoautotrophicum, obtained in its open conformation, and the KcsA channel from Streptomyces lividans, obtained in its closed conformation. We analyzed the dynamic characteristics and energetics of these homotetrameric structures in order to study the role of the intersubunit cooperativity in this transition. For this, elastic models and in silico alanine-scanning mutagenesis were used, respectively. Reassuringly, the calculations manifested motion from the open (closed) towards the closed (open) conformation. The calculations also revealed a network of dynamically and energetically coupled residues. Interestingly, the network suggests coupling between the selectivity filter and the gate, which are located at the two ends of the channel pore. Coupling between these two regions was not observed in calculations that were conducted with the monomer, which emphasizes the importance of the intersubunit interactions within the tetrameric structure for the cooperative gating behavior of the channel.

Time-resolved mechanism of extracellular gate opening and substrate binding in a glutamate transporter

Glutamate transporters, also referred to as excitatory amino acid transporters (EAATs), are membrane proteins that regulate glutamatergic signal transmission by clearing excess glutamate after its release at synapses. A structure-based understanding of their molecular mechanisms of function has been elusive until the recent determination of the x-ray structure of an archaeal transporter, Glt_Ph. Glt_Ph exists as a trimer, with each subunit containing a core region that mediates substrate translocation. In the present study a series of molecular dynamics simulations have been conducted and analyzed in light of new experimental data on substrate binding properties of EAATs. The simulations provide for the first time a full atomic description of the time-resolved events that drive the recognition and binding of substrate. The core region of each subunit exhibits an intrinsic tendency to open the helical hairpin HP2 loop, the extracellular gate, within tens of nanoseconds exposing conserved polar residues that serve as attractors for substrate binding. The NMDGT motif on the partially unwound part of the transmembrane helix TM7 and the residues Asp-390 and Asp-394 on TM8 are also distinguished by their important role in substrate binding and close interaction with mediating water molecules and/or sodium ions. The simulations reveal a Na⁺ binding site comprised in part of Leu-303 on TM7 and Asp-405 on TM8 and support a role for sodium ions in stabilizing substrate-bound conformers. The functional importance of Leu-303 or its counterpart Leu-391 in human EAAT1 (hEAAT1) is confirmed by site-directed mutagenesis and Na⁺ dependence assays conducted with hEAAT1 mutants L391C and L391A.

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein-protein docking

Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 A Calpha RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.

The molecular mechanism of toxin-induced conformational changes in a potassium channel: relation to C-type inactivation

Recently, a solid-state NMR study revealed that scorpion toxin binding leads to conformational changes in the selectivity filter of potassium channels. The exact nature of the conformational changes, however, remained elusive. We carried out all-atom molecular dynamics simulations that enabled us to cover the complete pathway of toxin approach and binding, and we validated our simulation results by using solid-state NMR data and electrophysiological measurements. Our structural model revealed a mechanism of cooperative toxin-induced conformational changes that accounts both for the signal changes observed in solid-state NMR and for the tight interaction between KcsA-Kv1.3 and Kaliotoxin. We show that this mechanism is structurally and functionally closely related to recovery from C-type inactivation. Furthermore, our simulations indicate heterogeneity in the binding modes of Kaliotoxin, which might serve to enhance its affinity for KcsA-Kv1.3 further by entropic stabilization.

Systematic multiscale parameterization of heterogeneous elastic network models of proteins

We present a method to parameterize heterogeneous elastic network models (heteroENMs) of proteins to reproduce the fluctuations observed in atomistic simulations. Because it is based on atomistic simulation, our method allows the development of elastic coarse-grained models of proteins under different conditions or in different environments. The method is simple and applicable to models at any level of coarse-graining. We validated the method in three systems. First, we computed the persistence length of ADP-bound F-actin, using a heteroENM model. The value of 6.1 +/- 1.6 microm is consistent with the experimentally measured value of 9.0 +/- 0.5 microm. We then compared our method to a uniform elastic network model and a realistic extension algorithm via covariance Hessian (REACH) model of carboxy myoglobin, and found that the heteroENM method more accurately predicted mean-square fluctuations of alpha-carbon atoms. Finally, we showed that the method captures critical differences in effective harmonic interactions for coarse-grained models of the N-terminal Bin/amphiphysin/Rvs (N-BAR) domain of amphiphysin, by building models of N-BAR both bound to a membrane and free in solution.

Evolutionary conservation of protein vibrational dynamics

The aim of the present work is to study the evolutionary divergence of vibrational protein dynamics. To this end, we used the Gaussian Network Model to perform a systematic analysis of normal mode conservation on a large dataset of proteins classified into homologous sets of family pairs and superfamily pairs. We found that the lowest most collective normal modes are the most conserved ones. More precisely, there is, on average, a linear correlation between normal mode conservation and mode collectivity. These results imply that the previously observed conservation of backbone flexibility (B-factor) profiles is due to the conservation of the most collective modes, which contribute the most to such profiles. We discuss the possible roles of normal mode robustness and natural selection in the determination of the observed behavior. Finally, we draw some practical implications for dynamics-based protein alignment and classification and discuss possible caveats of the present approach.

Conformer selection and induced fit in flexible backbone protein-protein docking using computational and NMR ensembles

Accommodating backbone flexibility continues to be the most difficult challenge in computational docking of protein-protein complexes. Towards that end, we simulate four distinct biophysical models of protein binding in RosettaDock, a multiscale Monte-Carlo-based algorithm that uses a quasi-kinetic search process to emulate the diffusional encounter of two proteins and to identify low-energy complexes. The four binding models are as follows: (1) key-lock (KL) model, using rigid-backbone docking; (2) conformer selection (CS) model, using a novel ensemble docking algorithm; (3) induced fit (IF) model, using energy-gradient-based backbone minimization; and (4) combined conformer selection/induced fit (CS/IF) model. Backbone flexibility was limited to the smaller partner of the complex, structural ensembles were generated using Rosetta refinement methods, and docking consisted of local perturbations around the complexed conformation using unbound component crystal structures for a set of 21 target complexes. The lowest-energy structure contained >30% of the native residue-residue contacts for 9, 13, 13, and 14 targets for KL, CS, IF, and CS/IF docking, respectively. When applied to 15 targets using nuclear magnetic resonance ensembles of the smaller protein, the lowest-energy structure recovered at least 30% native residue contacts in 3, 8, 4, and 8 targets for KL, CS, IF, and CS/IF docking, respectively. CS/IF docking of the nuclear magnetic resonance ensemble performed equally well or better than KL docking with the unbound crystal structure in 10 of 15 cases. The marked success of CS and CS/IF docking shows that ensemble docking can be a versatile and effective method for accommodating conformational plasticity in docking and serves as a demonstration for the CS theory--that binding-competent conformers exist in the unbound ensemble and can be selected based on their favorable binding energies.

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

Escherichia coli NikR is a homotetrameric Ni(2+)- and DNA-binding protein that functions as a transcriptional repressor of the NikABCDE nickel permease. The protein is composed of two distinct domains. The N-terminal 50 amino acids of each chain forms part of the dimeric ribbon-helix-helix (RHH) domains, a well-studied DNA-binding fold. The 83-residue C-terminal nickel-binding domain forms an ACT (aspartokinase, chorismate mutase, and TyrA) fold and contains the tetrameric interface. In this study, we have utilized an equilibrium molecular dynamics simulation in order to explore the conformational dynamics of the NikR tetramer and determine important residue interactions within and between the RHH and ACT domains to gain insight into the effects of Ni(2+) on DNA-binding activity. The molecular simulation data were analyzed using two different correlation measures based on fluctuations in atomic position and noncovalent contacts together with a clustering algorithm to define groups of residues with similar correlation patterns for both types of correlation measure. Based on these analyses, we have defined a series of residue interrelationships that describe an allosteric communication pathway between the Ni(2+)- and DNA-binding sites, which are separated by 40 A. Several of the residues identified by our analyses have been previously shown experimentally to be important for NikR function. An additional subset of the identified residues structurally connects the experimentally implicated residues and may help coordinate the allosteric communication between the ACT and RHH domains.

REACH coarse-grained biomolecular simulation: transferability between different protein structural classes

Coarse graining of protein interactions provides a means of simulating large biological systems. The REACH (Realistic Extension Algorithm via Covariance Hessian) coarse-graining method, in which the force constants of a residue-scale elastic network model are calculated from the variance-covariance matrix obtained from atomistic molecular dynamics (MD) simulation, involves direct mapping between scales without the need for iterative optimization. Here, the transferability of the REACH force field is examined between protein molecules of different structural classes. As test cases, myoglobin (all alpha), plastocyanin (all beta), and dihydrofolate reductase (alpha/beta) are taken. The force constants derived are found to be closely similar in all three proteins. An MD version of REACH is presented, and low-temperature coarse-grained (CG) REACH MD simulations of the three proteins are compared with atomistic MD results. The mean-square fluctuations of the atomistic MD are well reproduced by the CGMD. Model functions for the CG interactions, derived by averaging over the three proteins, are also shown to produce fluctuations in good agreement with the atomistic MD. The results indicate that, similarly to the use of atomistic force fields, it is now possible to use a single, generic REACH force field for all protein studies, without having first to derive parameters from atomistic MD simulation for each individual system studied. The REACH method is thus likely to be a reliable way of determining spatiotemporal motion of a variety of proteins without the need for expensive computation of long atomistic MD simulations.

Contact rearrangements form coupled networks from local motions in allosteric proteins

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that networks of contacts altered, formed, or broken are a significant contributor to allosteric communication in proteins. In this work, we identify which interactions change significantly between the residue-residue contact networks of two allosteric structures, and then organize these changes into graphs. We perform the analysis on 15 pairs of allosteric structures with effector and substrate each present in at least one of the two structures. Most proteins exhibit large, dense regions of contact rearrangement, and the graphs form connected paths between allosteric effector and substrate sites in five of these proteins. In the remaining 10 proteins, large-scale conformational changes such as rigid-body motions are likely required in addition to contact rearrangement networks to account for substrate-effector communication. On average, clusters which contain at least one substrate or effector molecule comprise 20% of the protein. These allosteric graphs are small worlds; that is, they typically have mean shortest path lengths comparable to those of corresponding random graphs and average clustering coefficients enhanced relative to those of random graphs. The networks capture 60-80% of known allostery-perturbing mutants in three proteins, and the metrics degree and closeness are statistically good discriminators of mutant residues from nonmutant residues within the networks in two of these three proteins. For two proteins, coevolving clusters of residues which have been hypothesized to be allosterically important differ from the regions with the most contact rearrangement. Residues and contacts which modulate normal mode fluctuations also often participate in the contact rearrangement networks. In summary, residue-residue contact rearrangement networks provide useful representations of the portions of allosteric pathways resulting from coupled local motions.

Differential native state ruggedness of the two Ca2+-binding domains in a Ca2+ sensor protein

Characterization of near-native excited states of a protein provides insights into various biological functions such as co-operativity, protein-ligand, and protein-protein interactions. In the present study, we investigated the ruggedness of the native state of EhCaBP using nonlinear temperature dependence of backbone amide-proton chemical shifts. EhCaBP is a two-domain EF-hand calcium sensor protein consisting of two EF-hands in each domain and binds four Ca2+ ions. It has been observed that approximately 30% of the residues in the protein access alternative conformations. Theoretical modeling suggested that these low-energy excited states are within 2-3 kcal/mol from the native state. Further, it is interesting to note that the residues accessing alternative conformations are more dominated in the C-terminal domain compared with its N-terminal counterpart suggesting that the former is more rugged in its native state. These distinct characteristics of N- and C-terminal domains of a calcium sensor protein belonging to the super family of calmodulin would have implications for domain dependent Ca2+ signaling pathways.

HingeProt: automated prediction of hinges in protein structures

Proteins are highly flexible molecules. Prediction of molecular flexibility aids in the comprehension and prediction of protein function and in providing details of functional mechanisms. The ability to predict the locations, directions, and extent of molecular movements can assist in fitting atomic resolution structures to low-resolution EM density maps and in predicting the complex structures of interacting molecules (docking). There are several types of molecular movements. In this work, we focus on the prediction of hinge movements. Given a single protein structure, the method automatically divides it into the rigid parts and the hinge regions connecting them. The method employs the Elastic Network Model, which is very efficient and was validated against a large data set of proteins. The output can be used in applications such as flexible protein-protein and protein-ligand docking, flexible docking of protein structures into cryo-EM maps, and refinement of low-resolution EM structures. The web server of HingeProt provides convenient visualization of the results and is available with two mirror sites at http://www.prc.boun.edu.tr/appserv/prc/HingeProt3 and http://bioinfo3d.cs.tau.ac.il/HingeProt/.