On the functional significance of soft modes predicted by coarse-grained models for membrane proteins

Activation and Speciation Mechanisms in Class A GPCRs

Accurate development of allosteric modulators of GPCRs require a thorough assessment of their sequence, structure, and dynamics, toward gaining insights into their mechanisms of actions shared by family members, as well as dynamic features that distinguish subfamilies. Building on recent progress in the characterization of the signature dynamics of proteins, we analyzed here a dataset of 160 Class A GPCRs to determine their sequence similarities, structural landscape, and dynamic features across different species (human, bovine, mouse, squid, and rat), different activation states (active/inactive), and different subfamilies. The two dominant directions of variability across experimentally resolved structures, identified by principal component analysis of the dataset, shed light to cooperative mechanisms of activation, subfamily differentiation, and speciation of Class A GPCRs. The analysis reveals the functional significance of the conformational flexibilities of specific structural elements, including: the dominant role of the intracellular loop 3 (ICL3) together with the cytoplasmic ends of the adjoining helices TM5 and TM6 in enabling allosteric activation; the role of particular structural motifs at the extracellular loop 2 (ECL2) connecting TM4 and TM5 in binding ligands specific to different subfamilies; or even the differentiation of the N-terminal conformation across different species. Detailed analyses of the modes of motions accessible to the members of the dataset and their variations across members demonstrate how the active and inactive states of GPCRs obey distinct conformational dynamics. The collective fluctuations of the GPCRs are robustly defined in the active state, while the inactive conformers exhibit broad variance among members.

Mechanisms of influence of the microtubule over-stabilizing ligands on the structure and intrinsic dynamics of α,β-Tubulin

The intervention into the cell cycle progression by administering microtubule over-stabilizing ligands that arrest the mitotic cell division by preventing spindle dissociation, is a promising strategy to fight against cancers. The building blocks of the microtubules and the spindles, i.e. the α,β-tubulin dimer, upon binding of such ligands, stay more comfortably in the microtubular multimeric form; the phenomenon of which is the key to the said over-stabilization. Using two such over-stabilizing ligands, Taxol and Taxotere, the present work reports the collective changes that these ligands induce on the structure and dynamics of the α,β-tubulin dimer which could be reconciled as the molecular basis of the over-stabilization of the microtubules; the trends have been found to be statistically significant across all independent calculations on them. The ligand binding increases the coherence between the residue communities of the two opposite faces of the β-subunit, which in a periodic arrangement in microtubule are knwon to form intermolecular contact with each other. This is likely to create an indirect cooperativity between those structural regions and this is a consequence of the reshuffling of the internal network of interactions upon ligand binding. Such reorganizations are also complemented by the increased contributions of the softer modes of the intrinsic dynamics more, which is likely to increase the plasticity of the system favourable for making structural adjustments in a multimer. Further, the ligands are able to compensate the drawback of lacking one phosphate group in protein-GDP interactions compared to the same for protein-GTP and this is in agreement with the hints form the earlier reports. The findings form a mechanistic basis of the enhanced capacity of the α,β-tubulin dimer to get more favourably accommodated into the microtubule superstructure upon binding either of Taxol and Taxotere.

Inferring functional units in ion channel pores via relative entropy

Coarse-grained protein models approximate the first-principle physical potentials. Among those modeling approaches, the relative entropy framework yields promising and physically sound results, in which a mapping from the target protein structure and dynamics to a model is defined and subsequently adjusted by an entropy minimization of the model parameters. Minimization of the relative entropy is equivalent to maximization of the likelihood of reproduction of (configurational ensemble) observations by the model. In this study, we extend the relative entropy minimization procedure beyond parameter fitting by a second optimization level, which identifies the optimal mapping to a (dimension-reduced) topology. We consider anisotropic network models of a diverse set of ion channels and assess our findings by comparison to experimental results.

Characterizing and Predicting Protein Hinges for Mechanistic Insight

The functioning of proteins requires highly specific dynamics, which depend critically on the details of how amino acids are packed. Hinge motions are the most common type of large motion, typified by the opening and closing of enzymes around their substrates. The packing and geometries of residues are characterized here by graph theory. This characterization is sufficient to enable reliable hinge predictions from a single static structure, and notably, this can be from either the open or the closed form of a structure. This new method to identify hinges within protein structures is called PACKMAN. The predicted hinges are validated by using permutation tests on B-factors. Hinge prediction results are compared against lists of manually curated hinge residues, and the results suggest that PACKMAN is robust enough to reproduce the known conformational changes and is able to predict hinge regions equally well from either the open or the closed forms of a protein. A group of 167 protein pairs with open and closed structures has been investigated Examples are shown for several additional proteins, including Zika virus nonstructured (NS) proteins where there are 6 hinge regions in the NS5 protein, 5 hinge regions in the NS2B bound in the NS3 protease complex and 5 hinges in the NS3- helicase protein. Results obtained from this method can be important for generating conformational ensembles of protein targets for drug design. PACKMAN is freely accessible at (https://PACKMAN.bb.iastate.edu/).

Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science

Organic anion and cation transporting proteins (OATs, OATPs, and OCTs), as well as the Multidrug and Toxin Extrusion (MATE) transporters of the Solute Carrier (SLC) family are playing a pivotal role in the discovery and development of new drugs due to their involvement in drug disposition, drug-drug interactions, adverse drug effects and related toxicity. Computational methods to understand and predict clinically relevant transporter interactions can provide useful guidance at early stages in drug discovery and design, especially if they include contemporary data science approaches. In this review, we summarize the current state-of-the-art of computational approaches for exploring ligand interactions and selectivity for these drug (uptake) transporters. The computational methods discussed here by highlighting interesting examples from the current literature are ranging from semiautomatic data mining and integration, to ligand-based methods (such as quantitative structure-activity relationships, and combinatorial pharmacophore modeling), and finally structure-based methods (such as comparative modeling, molecular docking, and molecular dynamics simulations). We are focusing on promising computational techniques such as fold-recognition methods, proteochemometric modeling or techniques for enhanced sampling of protein conformations used in the context of these ADMET-relevant SLC transporters with a special focus on methods useful for studying ligand selectivity.

Characterization of Differential Dynamics, Specificity, and Allostery of Lipoxygenase Family Members

Accurate modeling of structural dynamics of proteins and their differentiation across different species can help us understand generic mechanisms of function shared by family members and the molecular basis of the specificity of individual members. We focused here on the family of lipoxygenases, enzymes that catalyze lipid oxidation, the mammalian and bacterial structures of which have been elucidated. We present a systematic method of approach for characterizing the sequence, structure, dynamics, and allosteric signaling properties of these enzymes using a combination of structure-based models and methods and bioinformatics tools applied to a data set of 88 structures. The analysis elucidates the signature dynamics of the lipoxygenase family and its differentiation among members, as well as key sites that enable its adaptation to specific substrate binding and allosteric activity.

Green function of correlated genes in a minimal mechanical model of protein evolution

The function of proteins arises from cooperative interactions and rearrangements of their amino acids, which exhibit large-scale dynamical modes. Long-range correlations have also been revealed in protein sequences, and this has motivated the search for physical links between the observed genetic and dynamic cooperativity. We outline here a simplified theory of protein, which relates sequence correlations to physical interactions and to the emergence of mechanical function. Our protein is modeled as a strongly coupled amino acid network with interactions and motions that are captured by the mechanical propagator, the Green function. The propagator describes how the gene determines the connectivity of the amino acids and thereby, the transmission of forces. Mutations introduce localized perturbations to the propagator that scatter the force field. The emergence of function is manifested by a topological transition when a band of such perturbations divides the protein into subdomains. We find that epistasis-the interaction among mutations in the gene-is related to the nonlinearity of the Green function, which can be interpreted as a sum over multiple scattering paths. We apply this mechanical framework to simulations of protein evolution and observe long-range epistasis, which facilitates collective functional modes.

Allosteric Modulation of Intact γ-Secretase Structural Dynamics

As a protease complex involved in the cleavage of amyloid precursor proteins that lead to the formation of amyloid β fibrils implicated in Alzheimer's disease, γ-secretase is an important target for developing therapeutics against Alzheimer's disease. γ-secretase is composed of four subunits: nicastrin (NCT) in the extracellular (EC) domain, presenilin-1 (PS1), anterior pharynx defective 1, and presenilin enhancer 2 in the transmembrane (TM) domain. NCT and PS1 play important roles in binding amyloid β precursor proteins and modulating PS1 catalytic activity. Yet, the molecular mechanisms of coupling between substrate/modulator binding and catalytic activity remain to be elucidated. Recent determination of intact human γ-secretase cryo-electron microscopy structure has opened the way for a detailed investigation of the structural dynamics of this complex. Our analysis, based on a membrane-coupled anisotropic network model, reveals two types of NCT motions, bending and twisting, with respect to PS1. These underlie the fluctuations between the "open" and "closed" states of the lid-like NCT with respect to a hydrophilic loop 1 (HL1) on PS1, thus allowing or blocking access of the substrate peptide (EC portion) to HL1 and to the neighboring helix TM2. In addition to this alternating access mechanism, fluctuations in the volume of the PS1 central cavity facilitate the exposure of the catalytic site for substrate cleavage. Druggability simulations show that γ-secretase presents several hot spots for either orthosteric or allosteric inhibition of catalytic activity, consistent with experimental data. In particular, a hinge region at the interface between the EC and TM domains, near the interlobe groove of NCT, emerges as an allo-targeting site that would impact the coupling between HL1/TM2 and the catalytic pocket, opening, to our knowledge, new avenues for structure-based design of novel allosteric modulators of γ-secretase protease activity.

Improving virtual screening of G protein-coupled receptors via ligand-directed modeling

G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state.

G protein-coupled receptors (GPCRs) are a major target for drug discovery. These receptors are highly dynamic membrane proteins, and have had limited tractability using with biophysical screens that are widely adopted for globular protein targets. Thus, structure-based virtual screening (SBVS) holds great promise as a complement to physical screening for rational design of novel drugs. Indeed, the increasing number of atomic-detail GPCR X-ray crystal structures has coincided with an increase in prospective SBVS studies that have identified novel compounds. However, experimentally solved GPCR structures do not meet the full demand for SBVS, as the GPCR structural landscape is incomplete, lacking both in coverage of available GPCRs, and diversity in both receptor conformations and the chemistry of co-crystalised ligands. Here we present a novel computational GPCR binding pocket refinement method that can generate predictive GPCR/ligand complexes with improved SBVS performance. This ligand-directed modeling workflow uses parallel processing and efficient algorithms to search the GPCR/ligand conformational space faster and more efficiently than the widely used protein refinement method molecular dynamics. In this study, the resulting models are evaluated both structurally, and in retrospective SBVS. We demonstrate improved performance of refined models over their starting structures in the majority of our test cases.

A reduced mechanical model for cAMP-modulated gating in HCN channels

We developed an in silico mechanical model to analyze the process of cAMP-induced conformational modulations in hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, which conduct cations across the membrane of mammalian heart and brain cells. The structural analysis reveals a quaternary twist in the cytosolic parts of the four subunits in the channel tetramer. This motion augments the intrinsic dynamics of the very same protein structure. The pronounced differences between the cAMP bound and unbound form include a mutual interaction between the C-linker of the cyclic nucleotide binding domain (CNBD) and the linker between the S4 and S5 transmembrane domain of the channel. This allows a mechanistic annotation of the twisting motion in relation to the allosteric modulation of voltage-dependent gating of this channel by cAMP.

Using THz Spectroscopy, Evolutionary Network Analysis Methods, and MD Simulation to Map the Evolution of Allosteric Communication Pathways in c-Type Lysozymes

It is now widely accepted that protein function is intimately tied with the navigation of energy landscapes. In this framework, a protein sequence is not described by a distinct structure but rather by an ensemble of conformations. And it is through this ensemble that evolution is able to modify a protein's function by altering its landscape. Hence, the evolution of protein functions involves selective pressures that adjust the sampling of the conformational states. In this work, we focus on elucidating the evolutionary pathway that shaped the function of individual proteins that make-up the mammalian c-type lysozyme subfamily. Using both experimental and computational methods, we map out specific intermolecular interactions that direct the sampling of conformational states and accordingly, also underlie shifts in the landscape that are directly connected with the formation of novel protein functions. By contrasting three representative proteins in the family we identify molecular mechanisms that are associated with the selectivity of enhanced antimicrobial properties and consequently, divergent protein function. Namely, we link the extent of localized fluctuations involving the loop separating helices A and B with shifts in the equilibrium of the ensemble of conformational states that mediate interdomain coupling and concurrently moderate substrate binding affinity. This work reveals unique insights into the molecular level mechanisms that promote the progression of interactions that connect the immune response to infection with the nutritional properties of lactation, while also providing a deeper understanding about how evolving energy landscapes may define present-day protein function.

iGNM 2.0: the Gaussian network model database for biomolecular structural dynamics

Gaussian network model (GNM) is a simple yet powerful model for investigating the dynamics of proteins and their complexes. GNM analysis became a broadly used method for assessing the conformational dynamics of biomolecular structures with the development of a user-friendly interface and database, iGNM, in 2005. We present here an updated version, iGNM 2.0 http://gnmdb.csb.pitt.edu/, which covers more than 95% of the structures currently available in the Protein Data Bank (PDB). Advanced search and visualization capabilities, both 2D and 3D, permit users to retrieve information on inter-residue and inter-domain cross-correlations, cooperative modes of motion, the location of hinge sites and energy localization spots. The ability of iGNM 2.0 to provide structural dynamics data on the large majority of PDB structures and, in particular, on their biological assemblies makes it a useful resource for establishing the bridge between structure, dynamics and function.

Adaptability of protein structures to enable functional interactions and evolutionary implications

Several studies in recent years have drawn attention to the ability of proteins to adapt to intermolecular interactions by conformational changes along structure-encoded collective modes of motions. These so-called soft modes, primarily driven by entropic effects, facilitate, if not enable, functional interactions. They represent excursions on the conformational space along principal low-ascent directions/paths away from the original free energy minimum, and they are accessible to the protein even before protein-protein/ligand interactions. An emerging concept from these studies is the evolution of structures or modular domains to favor such modes of motion that will be recruited or integrated for enabling functional interactions. Structural dynamics, including the allosteric switches in conformation that are often stabilized upon formation of complexes and multimeric assemblies, emerge as key properties that are evolutionarily maintained to accomplish biological activities, consistent with the paradigm sequence→structure→dynamics→function where 'dynamics' bridges structure and function.

Cooperative Dynamics of Intact AMPA and NMDA Glutamate Receptors: Similarities and Subfamily-Specific Differences

Ionotropic glutamate receptors (iGluRs) are tetrameric ion channels that mediate excitatory neurotransmission. Recent structures of α-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) and N-methyl-D-aspartate (NMDA) receptors permit a comparative analysis of whole-receptor dynamics for the first time. Despite substantial differences in the packing of their two-domain extracellular region, the two iGluRs share similar dynamics, elucidated by elastic network models. Motions accessible to either structure enable conformational interconversion, such as compression of the AMPA receptor toward the more tightly packed NMDA receptor conformation, which has been linked to allosteric regulation. Pivoting motions coupled to concerted rotations of the transmembrane ion channel are prominent between dimers of distal N-terminal domains in the loosely packed AMPA receptor. The occurrence and functional relevance of these motions is verified by cross-linking experiments designed to probe the computationally predicted distance changes. Together with the identification of hotspot residues acting as mediators of allosteric communication, our data provide a glimpse into the dynamic spectrum of iGluRs.

The use of experimental structures to model protein dynamics

The number of solved protein structures submitted in the Protein Data Bank (PDB) has increased dramatically in recent years. For some specific proteins, this number is very high-for example, there are over 550 solved structures for HIV-1 protease, one protein that is essential for the life cycle of human immunodeficiency virus (HIV) which causes acquired immunodeficiency syndrome (AIDS) in humans. The large number of structures for the same protein and its variants include a sample of different conformational states of the protein. A rich set of structures solved experimentally for the same protein has information buried within the dataset that can explain the functional dynamics and structural mechanism of the protein. To extract the dynamics information and functional mechanism from the experimental structures, this chapter focuses on two methods-Principal Component Analysis (PCA) and Elastic Network Models (ENM). PCA is a widely used statistical dimensionality reduction technique to classify and visualize high-dimensional data. On the other hand, ENMs are well-established simple biophysical method for modeling the functionally important global motions of proteins. This chapter covers the basics of these two. Moreover, an improved ENM version that utilizes the variations found within a given set of structures for a protein is described. As a practical example, we have extracted the functional dynamics and mechanism of HIV-1 protease dimeric structure by using a set of 329 PDB structures of this protein. We have described, step by step, how to select a set of protein structures, how to extract the needed information from the PDB files for PCA, how to extract the dynamics information using PCA, how to calculate ENM modes, how to measure the congruency between the dynamics computed from the principal components (PCs) and the ENM modes, and how to compute entropies using the PCs. We provide the computer programs or references to software tools to accomplish each step and show how to use these programs and tools. We also include computer programs to generate movies based on PCs and ENM modes and describe how to visualize them.

Structure, dynamics and implied gating mechanism of a human cyclic nucleotide-gated channel

Cyclic nucleotide-gated (CNG) ion channels are nonselective cation channels, essential for visual and olfactory sensory transduction. Although the channels include voltage-sensor domains (VSDs), their conductance is thought to be independent of the membrane potential, and their gating regulated by cytosolic cyclic nucleotide-binding domains. Mutations in these channels result in severe, degenerative retinal diseases, which remain untreatable. The lack of structural information on CNG channels has prevented mechanistic understanding of disease-causing mutations, precluded structure-based drug design, and hampered in silico investigation of the gating mechanism. To address this, we built a 3D model of the cone tetrameric CNG channel, based on homology to two distinct templates with known structures: the transmembrane (TM) domain of a bacterial channel, and the cyclic nucleotide-binding domain of the mouse HCN2 channel. Since the TM-domain template had low sequence-similarity to the TM domains of the CNG channels, and to reconcile conflicts between the two templates, we developed a novel, hybrid approach, combining homology modeling with evolutionary coupling constraints. Next, we used elastic network analysis of the model structure to investigate global motions of the channel and to elucidate its gating mechanism. We found the following: (i) In the main mode of motion, the TM and cytosolic domains counter-rotated around the membrane normal. We related this motion to gating, a proposition that is supported by previous experimental data, and by comparison to the known gating mechanism of the bacterial KirBac channel. (ii) The VSDs could facilitate gating (supplementing the pore gate), explaining their presence in such 'voltage-insensitive' channels. (iii) Our elastic network model analysis of the CNGA3 channel supports a modular model of allosteric gating, according to which protein domains are quasi-independent: they can move independently, but are coupled to each other allosterically.

Mechanisms of CFTR functional variants that impair regulated bicarbonate permeation and increase risk for pancreatitis but not for cystic fibrosis

CFTR is a dynamically regulated anion channel. Intracellular WNK1-SPAK activation causes CFTR to change permeability and conductance characteristics from a chloride-preferring to bicarbonate-preferring channel through unknown mechanisms. Two severe CFTR mutations (CFTRsev) cause complete loss of CFTR function and result in cystic fibrosis (CF), a severe genetic disorder affecting sweat glands, nasal sinuses, lungs, pancreas, liver, intestines, and male reproductive system. We hypothesize that those CFTR mutations that disrupt the WNK1-SPAK activation mechanisms cause a selective, bicarbonate defect in channel function (CFTRBD) affecting organs that utilize CFTR for bicarbonate secretion (e.g. the pancreas, nasal sinus, vas deferens) but do not cause typical CF. To understand the structural and functional requirements of the CFTR bicarbonate-preferring channel, we (a) screened 984 well-phenotyped pancreatitis cases for candidate CFTRBD mutations from among 81 previously described CFTR variants; (b) conducted electrophysiology studies on clones of variants found in pancreatitis but not CF; (c) computationally constructed a new, complete structural model of CFTR for molecular dynamics simulation of wild-type and mutant variants; and (d) tested the newly defined CFTRBD variants for disease in non-pancreas organs utilizing CFTR for bicarbonate secretion. Nine variants (CFTR R74Q, R75Q, R117H, R170H, L967S, L997F, D1152H, S1235R, and D1270N) not associated with typical CF were associated with pancreatitis (OR 1.5, p = 0.002). Clones expressed in HEK 293T cells had normal chloride but not bicarbonate permeability and conductance with WNK1-SPAK activation. Molecular dynamics simulations suggest physical restriction of the CFTR channel and altered dynamic channel regulation. Comparing pancreatitis patients and controls, CFTRBD increased risk for rhinosinusitis (OR 2.3, p<0.005) and male infertility (OR 395, p<<0.0001). WNK1-SPAK pathway-activated increases in CFTR bicarbonate permeability are altered by CFTRBD variants through multiple mechanisms. CFTRBD variants are associated with clinically significant disorders of the pancreas, sinuses, and male reproductive system.

THz time scale structural rearrangements and binding modes in lysozyme-ligand interactions

Predicting the conformational changes in proteins that are relevant for substrate binding is an ongoing challenge in the aim of elucidating the functional states of proteins. The motions that are induced by protein-ligand interactions are governed by the protein global modes. Our measurements indicate that the detected changes in the global backbone motion of the enzyme upon binding reflect a shift from the large-scale collective dominant mode in the unbound state towards a functional twisting deformation that assists in closing the binding cleft. Correlated motion in lysozyme has been implicated in enzyme function in previous studies, but detailed characterization of the internal fluctuations that enable the protein to explore the ensemble of conformations that ultimately foster large-scale conformational change is yet unknown. For this reason, we use THz spectroscopy to investigate the picosecond time scale binding modes and collective structural rearrangements that take place in hen egg white lysozyme (HEWL) when bound by the inhibitor (NAG)3. These protein thermal motions correspond to fluctuations that have a role in both selecting and sampling from the available protein intrinsic conformations that communicate function. Hence, investigation of these fast, collective modes may provide knowledge about the mechanism leading to the preferred binding process in HEWL-(NAG)3. Specifically, in this work we find that the picosecond time scale hydrogen-bonding rearrangements taking place in the protein hydration shell with binding modify the packing density within the hydrophobic core on a local level. These localized, intramolecular contact variations within the protein core appear to facilitate the large cooperative movements within the interfacial region separating the α- and β- domain that mediate binding. The THz time-scale fluctuations identified in the protein-ligand system may also reveal a molecular mechanism for substrate recognition.

Investigation of the influence of external factors on the conformational dynamics of rhodopsin-like receptors by means of molecular dynamics simulation

The study reports about the influence of binding of orthosteric ligands on the conformational dynamics of β-2-adrenoreceptor. Using molecular dynamics (MD) simulation, we found that there was a little fraction of active states of the receptor in its apo (ligand-free) ensemble. Analysis of MD trajectories indicated that such spontaneous activation of the receptor is accompanied by the motion in intracellular part of its alpha-helices. Thus, receptor's constitutive activity directly results from its conformational dynamics. On the other hand, the binding of a full agonist resulted in a significant shift of the initial equilibrium towards its active state. Finally, the binding of the inverse agonist stabilized the receptor in its inactive state. It is likely that the binding of inverse agonists might be a universal way of constitutive activity inhibition in vivo. Our results indicate that ligand binding redistribute pre-existing conformational degrees of freedom (in accordance to the Monod-Wyman-Changeux Model) of the receptor rather than cause induced fit in it. Therefore, the ensemble of biologically relevant receptor conformations is encoded in its spatial structure, and individual conformations from that ensemble might be used by the cell in conformity with the physiological behavior.

Elastic network normal mode dynamics reveal the GPCR activation mechanism

G-protein-coupled receptors (GPCR) are a family of membrane-embedded metabotropic receptors which translate extracellular ligand binding into an intracellular response. Here, we calculate the motion of several GPCR family members such as the M2 and M3 muscarinic acetylcholine receptors, the A2A adenosine receptor, the β2 -adrenergic receptor, and the CXCR4 chemokine receptor using elastic network normal modes. The normal modes reveal a dilation and a contraction of the GPCR vestibule associated with ligand passage, and activation, respectively. Contraction of the vestibule on the extracellular side is correlated with cavity formation of the G-protein binding pocket on the intracellular side, which initiates intracellular signaling. Interestingly, the normal modes of rhodopsin do not correlate well with the motion of other GPCR family members. Electrostatic potential calculation of the GPCRs reveal a negatively charged field around the ligand binding site acting as a siphon to draw-in positively charged ligands on the membrane surface. Altogether, these results expose the GPCR activation mechanism and show how conformational changes on the cell surface side of the receptor are allosterically translated into structural changes on the inside.

Protein oligomers studied by solid-state NMR--the case of the full-length nucleoid-associated protein histone-like nucleoid structuring protein

Members of the histone-like nucleoid structuring protein (H-NS) family play roles both as architectural proteins and as modulators of gene expression in Gram-negative bacteria. The H-NS protein participates in modulatory processes that respond to environmental changes in osmolarity, pH, or temperature. H-NS oligomerization is essential for its activity. Structural models of different truncated forms are available. However, high-resolution structural details of full-length H-NS and its DNA-bound state have largely remained elusive. We report on progress in characterizing the biologically active H-NS oligomers with solid-state NMR. We compared uniformly ((13)C,(15)N)-labeled ssNMR preparations of the isolated N-terminal region (H-NS 1-47) and full-length H-NS (H-NS 1-137). In both cases, we obtained ssNMR spectra of good quality and characteristic of well-folded proteins. Analysis of the results of 2D and 3D (13)C-(13)C and (15)N-(13)C correlation experiments conducted at high magnetic field led to assignments of residues located in different topological regions of the free full-length H-NS. These findings confirm that the structure of the N-terminal dimerization domain is conserved in the oligomeric full-length protein. Small changes in the dimerization interface suggested by localized chemical shift variations between solution and solid-state spectra may be relevant for DNA recoginition.

Dynamics of endoglucanase catalytic domains: implications towards thermostability

Thermostable endoglucanases play a crucial role in the production of biofuels to breakdown plant cellulose. Analyzing their structure-dynamics relationship can inform about the origins of their thermostability. Although tertiary structures of many endoglucanase proteins are available, the relationship between thermostability, structure, and dynamics is not explored fully. We have generated elastic network models for thermostable and mesostable endoglucanases with the (αβ)₈ fold in substrate bound and unbound states. The comparative analyses shed light on the relation between protein dynamics, thermostability, and substrate binding. We observed specific differences in the dynamic behavior of catalytic residues in slow modes: while both the nucleophile and the acid/base donor residues show positively correlated motions in the thermophile, their dynamics is uncoupled in the mesophile. Our proof-of-concept comparison study suggests that global dynamics can be harnessed to further our understanding of thermostability.

Gating and conduction of nano-channel forming proteins: a computational approach

Monitoring conformational changes in ion channels is essential to understand their gating mechanism. Here, we explore the structural dynamics of four outer membrane proteins with different structures and functions in the slowest nonzero modes of vibration. Normal mode analysis was performed on the modified elastic network model of channel in the membrane. According to our results, when membrane proteins were analyzed in the dominant mode, the composed pores, TolC and α-hemolysin showed large motions at the intramembrane β-barrel region while, in other porins, OmpA and OmpF, largest motions observed in the region of external flexible loops. A criterion based on equipartition theorem was used to measure the possible amplitude of vibration in channel forming proteins. The current approach complements theoretical and experimental techniques including HOLE, Molecular Dynamics (MD), and voltage clamp used to address the channel's structure and dynamics and provides the means to conduct a theoretical simultaneous study of the structure and function of the channel. An animated interactive 3D complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:3.

How does KCNE1 regulate the Kv7.1 potassium channel? Model-structure, mutations, and dynamics of the Kv7.1-KCNE1 complex

The voltage-gated potassium channel Kv7.1 and its auxiliary subunit KCNE1 are expressed in the heart and give rise to the major repolarization current. The interaction of Kv7.1 with the single transmembrane helix of KCNE1 considerably slows channel activation and deactivation, raises single-channel conductance, and prevents slow voltage-dependent inactivation. We built a Kv7.1-KCNE1 model-structure. The model-structure agrees with previous disulfide mapping studies and enables us to derive molecular interpretations of electrophysiological recordings that we obtained for two KCNE1 mutations. An elastic network analysis of Kv7.1 fluctuations in the presence and absence of KCNE1 suggests a mechanistic perspective on the known effects of KCNE1 on Kv7.1 function: slow deactivation is attributed to the low mobility of the voltage-sensor domains upon KCNE1 binding, abolishment of voltage-dependent inactivation could result from decreased fluctuations in the external vestibule, and amalgamation of the fluctuations in the pore region is associated with enhanced ion conductivity.

Constraints imposed by the membrane selectively guide the alternating access dynamics of the glutamate transporter GltPh

Substrate transport in sodium-coupled amino acid symporters involves a large-scale conformational change that shifts the access to the substrate-binding site from one side of the membrane to the other. The structural change is particularly substantial and entails a unique piston-like quaternary rearrangement in glutamate transporters, as evidenced by the difference between the outward-facing and inward-facing structures resolved for the archaeal aspartate transporter Glt(Ph). These structural changes occur over time and length scales that extend beyond the reach of current fully atomic models, but are regularly explored with the use of elastic network models (ENMs). Despite their success with other membrane proteins, ENM-based approaches for exploring the collective dynamics of Glt(Ph) have fallen short of providing a plausible mechanism. This deficiency is attributed here to the anisotropic constraints imposed by the membrane, which are not incorporated into conventional ENMs. Here we employ two novel (to our knowledge) ENMs to demonstrate that one can largely capture the experimentally observed structural change using only the few lowest-energy modes of motion that are intrinsically accessible to the transporter, provided that the surrounding lipid molecules are incorporated into the ENM. The presence of the membrane reduces the overall energy of the transition compared with conventional models, showing that the membrane not only guides the selected mechanism but also acts as a facilitator. Finally, we show that the dynamics of Glt(Ph) is biased toward transitions of individual subunits of the trimer rather than cooperative transitions of all three subunits simultaneously, suggesting a mechanism of transport that exploits the intrinsic dynamics of individual subunits. Our software is available online at http://www.membranm.csb.pitt.edu.

A model-structure of a periplasm-facing state of the NhaA antiporter suggests the molecular underpinnings of pH-induced conformational changes

The Escherichia coli NhaA antiporter couples the transport of H⁺ and Na⁺ (or Li⁺) ions to maintain the proper pH range and Na⁺ concentration in cells. A crystal structure of NhaA, solved at pH 4, comprises 12 transmembrane helices (TMs), arranged in two domains, with a large cytoplasm-facing funnel and a smaller periplasm-facing funnel. NhaA undergoes conformational changes, e.g. after pH elevation to alkaline ranges, and we used two computational approaches to explore them. On the basis of pseudo-symmetric features of the crystal structure, we predicted the structural architecture of an alternate, periplasm-facing state. In contrast to the crystal structure, the model presents a closed cytoplasmic funnel, and a periplasmic funnel of greater volume. To examine the transporter functional direction of motion, we conducted elastic network analysis of the crystal structure and detected two main normal modes of motion. Notably, both analyses predicted similar trends of conformational changes, consisting of an overall rotational motion of the two domains around a putative symmetry axis at the funnel centers, perpendicular to the membrane plane. This motion, along with conformational changes within specific helices, resulted in closure at the cytoplasmic end and opening at the periplasmic end. Cross-linking experiments, performed between segments on opposite sides of the cytoplasmic funnel, revealed pH-dependent interactions consistent with the proposed conformational changes. We suggest that the model-structure and predicted motion represent alkaline pH-induced conformational changes, mediated by a cluster of evolutionarily conserved, titratable residues, at the cytoplasmic ends of TMs II, V, and IX.

Optimal number of coarse-grained sites in different components of large biomolecular complexes

The computational study of large biomolecular complexes (molecular machines, cytoskeletal filaments, etc.) is a formidable challenge facing computational biophysics and biology. To achieve biologically relevant length and time scales, coarse-grained (CG) models of such complexes usually must be built and employed. One of the important early stages in this approach is to determine an optimal number of CG sites in different constituents of a complex. This work presents a systematic approach to this problem. First, a universal scaling law is derived and numerically corroborated for the intensity of the intrasite (intradomain) thermal fluctuations as a function of the number of CG sites. Second, this result is used for derivation of the criterion for the optimal number of CG sites in different parts of a large multibiomolecule complex. In the zeroth-order approximation, this approach validates the empirical rule of taking one CG site per fixed number of atoms or residues in each biomolecule, previously widely used for smaller systems (e.g., individual biomolecules). The first-order corrections to this rule are derived and numerically checked by the case studies of the Escherichia coli ribosome and Arp2/3 actin filament junction. In different ribosomal proteins, the optimal number of amino acids per CG site is shown to differ by a factor of 3.5, and an even wider spread may exist in other large biomolecular complexes. Therefore, the method proposed in this paper is valuable for the optimal construction of CG models of such complexes.

Identification of motions in membrane proteins by elastic network models and their experimental validation

Identifying the functional motions of membrane proteins is difficult because they range from large-scale collective dynamics to local small atomic fluctuations at different timescales that are difficult to measure experimentally due to the hydrophobic nature of these proteins. Elastic Network Models, and in particular their most widely used implementation, the Anisotropic Network Model (ANM), have proven to be useful computational methods in many recent applications to predict membrane protein dynamics. These models are based on the premise that biomolecules possess intrinsic mechanical characteristics uniquely defined by their particular architectures. In the ANM, interactions between residues in close proximity are represented by harmonic potentials with a uniform spring constant. The slow mode shapes generated by the ANM provide valuable information on the global dynamics of biomolecules that are relevant to their function. In its recent extension in the form of ANM-guided molecular dynamics (MD), this coarse-grained approach is augmented with atomic detail. The results from ANM and its extensions can be used to guide experiments and thus speedup the process of quantifying motions in membrane proteins. Testing the predictions can be accomplished through (a) direct observation of motions through studies of structure and biophysical probes, (b) perturbation of the motions by, e.g., cross-linking or site-directed mutagenesis, and (c) by studying the effects of such perturbations on protein function, typically through ligand binding and activity assays. To illustrate the applicability of the combined computational ANM-experimental testing framework to membrane proteins, we describe-alongside the general protocols-here the application of ANM to rhodopsin, a prototypical member of the pharmacologically relevant G-protein coupled receptor family.

The harmonic analysis of cylindrically symmetric proteins: a comparison of Dronpa and a DNA sliding clamp

The harmonic analysis of two types of proteins with cylindrical symmetry is performed by the Standard Force Field Normal Mode Analysis and by the elastic network model. For both proteins the global elastic modes are assigned to their characteristic topologies. Dronpa is a rigid β-barrel structure, presenting the twisting, bending and breathing motion of a cylindrical rod. The β sliding clamp of Escherichia coli is a hexagonal β-wheel, consisting of rigid segments. In its spectrum four classes of vibrations are identified which are characteristic of an elastic torus. Correlation diagrams and RMSF analysis are compared. The results provide not only a comprehensive validation of the use of both methods to describe the elastic behavior according to the low-frequency normal modes, but also depict the correlated motions of β-barrel and β-wheel proteins. The harmonic flexibility of the Dronpa protein is compared to the principal components of molecular dynamics (MD) simulation. A functionally important localized cleft opening mode is found, which is not detected by harmonic analysis.

Computational generation inhibitor-bound conformers of p38 MAP kinase and comparison with experiments

The p38 MAP kinases play a critical role in regulating stress-activated pathways, and serve as molecular targets for controlling inflammatory diseases. Computer-aided efforts for developing p38 inhibitors have been hampered by the necessity to include the enzyme conformational flexibility in ligand docking simulations. A useful strategy in such complicated cases is to perform ensemble-docking provided that a representative set of conformers is available for the target protein either from computations or experiments. We explore here the abilities of two computational approaches, molecular dynamics (MD) simulations and anisotropic network model (ANM) normal mode analysis, for generating potential ligand-bound conformers starting from the apo state of p38, and benchmark them against the space of conformers (or the reference modes of structural changes) inferred from principal component analysis of 134 experimentally resolved p38 kinase structures. ANM-generated conformations are found to provide a significantly better coverage of the inhibitor-bound conformational space observed experimentally, compared to MD simulations performed in explicit water, suggesting that ANM-based sampling of conformations can be advantageously employed as input structural models in docking simulations.

Constraint-based, homology model of the extracellular domain of the epithelial Na+ channel α subunit reveals a mechanism of channel activation by proteases

The epithelial Na(+) channel (ENaC) mediates Na(+) transport across high resistance epithelia. This channel is assembled from three homologous subunits with the majority of the protein's mass found in the extracellular domains. Acid-sensing ion channel 1 (ASIC1) is homologous to ENaC, but a key functional domain is highly divergent. Here we present molecular models of the extracellular region of α ENaC based on a large data set of mutations that attenuate inhibitory peptide binding in combination with comparative modeling based on the resolved structure of ASIC1. The models successfully rationalized the data from the peptide binding screen. We engineered new mutants that had not been tested based on the models and successfully predict sites where mutations affected peptide binding. Thus, we were able to confirm the overall general fold of our structural models. Further analysis suggested that the α subunit-derived inhibitory peptide affects channel gating by constraining motions within two major domains in the extracellular region, the thumb and finger domains.