MolMovDB: analysis and visualization of conformational change and structural flexibility

FTMove: A Web Server for Detection and Analysis of Cryptic and Allosteric Binding Sites by Mapping Multiple Protein Structures

Protein mapping distributes many copies of different molecular probes on the surface of a target protein in order to determine binding hot spots, regions that are highly preferable for ligand binding. While mapping of X-ray structures by the FTMap server is inherently static, this limitation can be overcome by the simultaneous analysis of multiple structures of the protein. FTMove is an automated web server that implements this approach. From the input of a target protein, by PDB code, the server identifies all structures of the protein available in the PDB, runs mapping on them, and combines the results to form binding hot spots and binding sites. The user may also upload their own protein structures, bypassing the PDB search for similar structures. Output of the server consists of the consensus binding sites and the individual mapping results for each structure - including the number of probes located in each binding site, for each structure. This level of detail allows the users to investigate how the strength of a binding site relates to the protein conformation, other binding sites, and the presence of ligands or mutations. In addition, the structures are clustered on the basis of their binding properties. The use of FTMove is demonstrated by application to 22 proteins with known allosteric binding sites; the orthosteric and allosteric binding sites were identified in all but one case, and the sites were typically ranked among the top five. The FTMove server is publicly available at https://ftmove.bu.edu.

D3PM: a comprehensive database for protein motions ranging from residue to domain

Background

Knowledge of protein motions is significant to understand its functions. While currently available databases for protein motions are mostly focused on overall domain motions, little attention is paid on local residue motions. Albeit with relatively small scale, the local residue motions, especially those residues in binding pockets, may play crucial roles in protein functioning and ligands binding.

Results

A comprehensive protein motion database, namely D3PM, was constructed in this study to facilitate the analysis of protein motions. The protein motions in the D3PM range from overall structural changes of macromolecule to local flip motions of binding pocket residues. Currently, the D3PM has collected 7679 proteins with overall motions and 3513 proteins with pocket residue motions. The motion patterns are classified into 4 types of overall structural changes and 5 types of pocket residue motions. Impressively, we found that less than 15% of protein pairs have obvious overall conformational adaptations induced by ligand binding, while more than 50% of protein pairs have significant structural changes in ligand binding sites, indicating that ligand-induced conformational changes are drastic and mainly confined around ligand binding sites. Based on the residue preference in binding pocket, we classified amino acids into “pocketphilic” and “pocketphobic” residues, which should be helpful for pocket prediction and drug design.

Conclusion

D3PM is a comprehensive database about protein motions ranging from residue to domain, which should be useful for exploring diverse protein motions and for understanding protein function and drug design. The D3PM is available on www.d3pharma.com/D3PM/index.php.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04595-0.

Analysis of changes of cavity volumes in predefined directions of protein motions and cavity flexibility

Dynamics of protein cavities associated with protein fluctuations and conformational plasticity is essential for their biological function. NMR ensembles, molecular dynamics (MD) simulations, and normal mode analysis (NMA) provide appropriate frameworks to explore functionally relevant protein dynamics and cavity changes relationships. Within this context, we have recently developed analysis of null areas (ANA), an efficient method to calculate cavity volumes. ANA is based on a combination of algorithms that guarantees its robustness against numerical differentiations. This is a unique feature with respect to other methods. Herein, we present an updated and improved version that expands it use to quantify changes in cavity features, like volume and flexibility, due to protein structural distortions performed on predefined biologically relevant directions, for example, directions of largest contribution to protein fluctuations (principal component analysis [PCA modes]) obtained by MD simulations or ensembles of NMR structures, collective NMA modes or any other direction of motion associated with specific conformational changes. A web page has been developed where its facilities are explained in detail. First, we show that ANA can be useful to explore gradual changes of cavity volume and flexibility associated with protein ligand binding. Secondly, we perform a comparison study of the extent of variability between protein backbone structural distortions, and changes in cavity volumes and flexibilities evaluated for an ensemble of NMR active and inactive conformers of the epidermal growth factor receptor structures. Finally, we compare changes in size and flexibility between sets of NMR structures for different homologous chains of dynein.

"Protein" no longer means what it used to

Every biologist knows that the word protein describes a group of macromolecules essential to sustain life on Earth. As biologists, we are invariably trained under a protein paradigm established since the early twentieth century. However, in recent years, the term protein unveiled itself as an euphemism to describe the overwhelming heterogeneity of these compounds. Most of our current studies are targeted on carefully selected subsets of proteins, but we tend to think and write about these as representative of the whole population. Here we discuss how seeking for universal definitions and general rules in any arbitrarily segmented study would be misleading about the conclusions. Of course, it is not our purpose to discourage the use of the word protein. Instead, we suggest to embrace the extended universe of proteins to reach a deeper understanding of their full potential, realizing that the term encompasses a group of molecules very heterogeneous in terms of size, shape, chemistry and functions, i.e. the term protein no longer means what it used to.

Moving beyond static snapshots: Protein dynamics and the Protein Data Bank

Proteins are the molecular machines of living systems. Their dynamics are an intrinsic part of their evolutionary selection in carrying out their biological functions. Although the dynamics are more difficult to observe than a static, average structure, we are beginning to observe these dynamics and form sound mechanistic connections between structure, dynamics, and function. This progress is highlighted in case studies from myoglobin and adenylate kinase to the ribosome and molecular motors where these molecules are being probed with a multitude of techniques across many timescales. New approaches to time-resolved crystallography are allowing simple “movies” to be taken of proteins in action, and new methods of mapping the variations in cryo-electron microscopy are emerging to reveal a more complete description of life’s machines. The results of these new methods are aided in their dissemination by continual improvements in curation and distribution by the Protein Data Bank and their partners around the world.

HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions by using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures. The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.

Synchronous and Asynchronous Response in Dynamically Perturbed Proteins

We present a dynamic perturbation-response model of proteins based on the Gaussian Network Model, where a residue is perturbed periodically, and the dynamic response of other residues is determined. The model shows that periodic perturbation causes a synchronous response in phase with the perturbation and an asynchronous response that is out of phase. The asynchronous component results from the viscous effects of the solvent and other dispersive factors in the system. The model is based on the solution of the Langevin equation in the presence of solvent, noise, and perturbation. We introduce several novel ideas: The concept of storage and loss compliance of the protein and their dependence on structure and frequency; the amount of work lost and the residues that contribute significantly to the lost work; new dynamic correlations that result from perturbation; causality, that is, the response of j when i is perturbed is not equal to the response of i when j is perturbed. As examples, we study two systems, namely, bovine rhodopsin and the class of nanobodies. The general results obtained are (i) synchronous and asynchronous correlations depend strongly on the frequency of perturbation, their magnitude decreases with increasing frequency, (ii) time-delayed mean-squared fluctuations of residues have only synchronous components. Asynchronicity is present only in cross correlations, that is, correlations between different residues, (iii) perturbation of loop residues leads to a large dissipation of work, (iv) correlations satisfy the hypothesis of pre-existing pathways according to which information transfer by perturbation rides on already existing equilibrium correlations in the system, (v) dynamic perturbation can introduce a selective response in the system, where the perturbation of each residue excites different sets of responding residues, and (vi) it is possible to identify nondissipative residues whose perturbation does not lead to dissipation in the protein. Despite its simplicity, the model explains several features of allosteric manipulation.

Exploring Conformational Space with Thermal Fluctuations Obtained by Normal-Mode Analysis

Proteins in their native states can be represented as ensembles of conformers in dynamical equilibrium. Thermal fluctuations are responsible for transitions between these conformers. Normal-modes analysis (NMA) using elastic network models (ENMs) provides an efficient procedure to explore global dynamics of proteins commonly associated with conformational transitions. In the present work, we present an iterative approach to explore protein conformational spaces by introducing structural distortions according to their equilibrium dynamics at room temperature. The approach can be used either to perform unbiased explorations of conformational space or to explore guided pathways connecting two different conformations, e.g., apo and holo forms. In order to test its performance, four proteins with different magnitudes of structural distortions upon ligand binding have been tested. In all cases, the conformational selection model has been confirmed and the conformational space between apo and holo forms has been encompassed. Different strategies have been tested that impact on the efficiency either to achieve a desired conformational change or to achieve a balanced exploration of the protein conformational multiplicity.

Perturb-Scan-Pull: A Novel Method Facilitating Conformational Transitions in Proteins

Conformational transitions in proteins facilitate precise physiological functions. Therefore, it is crucial to understand the mechanisms underlying these processes to modulate protein function. Yet, studying structural and dynamical properties of proteins is notoriously challenging due to the complexity of the underlying potential energy surfaces (PES). We have previously developed the perturbation-response scanning (PRS) method to identify key residues that participate in the communication network responsible for specific conformational transitions. PRS is based on a residue-by-residue scan of the protein to determine the subset of residues/forces which provide the closest conformational change leading to a target conformational state, inasmuch as linear response theory applies to these motions. Here, we develop a novel method to further evaluate if conformational transitions may be triggered on the PES. We aim to study functionally relevant conformational transitions in proteins by using results obtained from PRS and feeding them as inputs to steered molecular dynamics simulations. The success and the transferability of the method are evaluated on three protein systems having different complexities of motion on the PES: calmodulin, adenylate kinase, and bacterial ferric binding protein. We find that the method captures the target conformation, while providing key residues and the optimum paths with relatively low free energy profiles.

Predicting Protein Functional Motions: an Old Recipe with a New Twist

Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.

Considerations on the Rational Design of Covalently Conjugated Cell-Penetrating Peptides (CPPs) for Intracellular Delivery of Proteins: A Guide to CPP Selection Using Glucarpidase as the Model Cargo Molecule

Access of proteins to their intracellular targets is limited by a hydrophobic barrier called the cellular membrane. Conjugation with cell-penetrating peptides (CPPs) has been shown to improve protein transduction into the cells. This conjugation can be either covalent or non-covalent, each with its unique pros and cons. The CPP-protein covalent conjugation may result in undesirable structural and functional alterations in the target protein. Therefore, we propose a systematic approach to evaluate different CPPs for covalent conjugations. This guide is presented using the carboxypeptidase G2 (CPG2) enzyme as the target protein. Seventy CPPs -out of 1155- with the highest probability of uptake efficiency were selected. These peptides were then conjugated to the N- or C-terminus of CPG2. Translational efficacy of the conjugates, robustness and thermodynamic properties of the chimera, aggregation possibility, folding rate, backbone flexibility, and aspects of in vivo administration such as protease susceptibility were predicted. The effect of the position of conjugation was evaluated using unpaired t-test (p < 0.05). It was concluded that N-terminal conjugation resulted in higher quality constructs. Seventeen CPP-CPG2/CPG2-CPP constructs were identified as the most promising. Based on this study, the bioinformatics workflow that is presented may be universally applied to any CPP-protein conjugate design.

ART-RRT: As-Rigid-As-Possible search for protein conformational transition paths

The possible functions of a protein are strongly related to its structural rearrangements in the presence of other molecules or environmental changes. Hence, the evaluation of transition paths of proteins, which encodes conformational changes between stable states, is important since it may reveal the underlying mechanisms of the biochemical processes related to these motions. During the last few decades, different geometry-based methods have been proposed to predict such transition paths. However, in the cases where the solution requires complex motions, these methods, which typically constrain only locally the molecular structures, could produce physically irrelevant solutions involving self-intersection. Recently, we have proposed ART-RRT, an efficient method for finding ligand-unbinding pathways. It relies on the exploration of energy valleys in low-dimensional spaces, taking advantage of some mechanisms inspired from computer graphics to ensure the consistency of molecular structures. This article extends ART-RRT to the problem of finding probable conformational transition between two stable states for proteins. It relies on a bidirectional exploration rooted on the two end states and introduces an original strategy to attempt connections between the explored regions. The resulting method is able to produce at low computational cost biologically realistic paths free from self-intersection. These paths can serve as valuable input to other advanced methods for the study of proteins. A better understanding of conformational changes of proteins is important since it may reveal the underlying mechanisms of the biochemical processes related to such motions. Recently, the ART-RRT method has been introduced for finding ligand-unbinding pathways. This article presents an adaptation of the method for finding probable conformational transition between two stable states of a protein. The method is not only computationally cost-effective but also able to produce biologically realistic paths which are free from self-intersection.

Inherent versus induced protein flexibility: Comparisons within and between apo and holo structures

Understanding how ligand binding influences protein flexibility is important, especially in rational drug design. Protein flexibility upon ligand binding is analyzed herein using 305 proteins with 2369 crystal structures with ligands (holo) and 1679 without (apo). Each protein has at least two apo and two holo structures for analysis. The inherent variation in structures with and without ligands is first established as a baseline. This baseline is then compared to the change in conformation in going from the apo to holo states to probe induced flexibility. The inherent backbone flexibility across the apo structures is roughly the same as the variation across holo structures. The induced backbone flexibility across apo-holo pairs is larger than that of the apo or holo states, but the increase in RMSD is less than 0.5 Å. Analysis of χ1 angles revealed a distinctly different pattern with significant influences seen for ligand binding on side-chain conformations in the binding site. Within the apo and holo states themselves, the variation of the χ1 angles is the same. However, the data combining both apo and holo states show significant displacements. Upon ligand binding, χ1 angles are frequently pushed to new orientations outside the range seen in the apo states. Influences on binding-site variation could not be easily attributed to features such as ligand size or x-ray structure resolution. By combining these findings, we find that most binding site flexibility is compatible with the common practice in flexible docking, where backbones are kept rigid and side chains are allowed some degree of flexibility.

Predicting loop conformational ensembles

Motivation

Protein function is often facilitated by the existence of multiple stable conformations. Structure prediction algorithms need to be able to model these different conformations accurately and produce an ensemble of structures that represent a target's conformational diversity rather than just a single state. Here, we investigate whether current loop prediction algorithms are capable of this. We use the algorithms to predict the structures of loops with multiple experimentally determined conformations, and the structures of loops with only one conformation, and assess their ability to generate and select decoys that are close to any, or all, of the observed structures.

Results

We find that while loops with only one known conformation are predicted well, conformationally diverse loops are modelled poorly, and in most cases the predictions returned by the methods do not resemble any of the known conformers. Our results contradict the often-held assumption that multiple native conformations will be present in the decoy set, making the production of accurate conformational ensembles impossible, and hence indicating that current methodologies are not well suited to prediction of conformationally diverse, often functionally important protein regions.

Contact

marks@stats.ox.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Generating conformational transition paths with low potential-energy barriers for proteins

The knowledge of conformational transition paths in proteins can be useful for understanding protein mechanisms. Recently, we have introduced the As-Rigid-As-Possible (ARAP) interpolation method, for generating interpolation paths between two protein conformations. The method was shown to preserve well the rigidity of the initial conformation along the path. However, because the method is totally geometry-based, the generated paths may be inconsistent because the atom interactions are ignored. Therefore, in this article, we would like to introduce a new method to generate conformational transition paths with low potential-energy barriers for proteins. The method is composed of three processing stages. First, ARAP interpolation is used for generating an initial path. Then, the path conformations are enhanced by a clash remover. Finally, Nudged Elastic Band, a path-optimization method, is used to produce a low-energy path. Large energy reductions are found in the paths obtained from the method than in those obtained from the ARAP interpolation method alone. The results also show that ARAP interpolation is a good candidate for generating an initial path because it leads to lower potential-energy paths than two other common methods for path interpolation.

Chromosomal Context Affects the Molecular Evolution of Sex-linked Genes and Their Autosomal Counterparts in Turtles and Other Vertebrates

Sex chromosomes evolve differently from autosomes because natural selection acts distinctly on them given their reduced recombination and smaller population size. Various studies of sex-linked genes compared with different autosomal genes within species support these predictions. Here, we take a novel alternative approach by comparing the rate of evolution between subsets of genes that are sex-linked in selected reptiles/vertebrates and the same genes located in autosomes in other amniotes. We report for the first time the faster evolution of Z-linked genes in a turtle (the Chinese softshell turtle Pelodiscus sinensis) relative to autosomal orthologs in other taxa, including turtles with temperature-dependent sex determination (TSD). This faster rate was absent in its close relative, the spiny softshell turtle (Apalone spinifera), thus revealing important lineage effects, and was only surpassed by mammalian-X linked genes. In contrast, we found slower evolution of X-linked genes in the musk turtle Staurotypus triporcatus (XX/XY) and homologous Z-linked chicken genes. TSD lineages displayed overall faster sequence evolution than taxa with genotypic sex determination (GSD), ruling out global effects of GSD on molecular evolution beyond those by sex-linkage. Notably, results revealed a putative selective sweep around two turtle genes involved in vertebrate gonadogenesis (Pelodiscus-Z-linked Nf2 and Chrysemys-autosomal Tspan7). Our observations reveal important evolutionary changes at the gene level mediated by chromosomal context in turtles despite their low overall evolutionary rate and illuminate sex chromosome evolution by empirically testing expectations from theoretical models. Genome-wide analyses are warranted to test the generality and prevalence of the observed patterns.

Localizing Conformational Hinges by NMR: Where Do Hepatitis B Virus Core Proteins Adapt for Capsid Assembly?

The hepatitis B virus (HBV) icosahedral nucleocapsid is assembled from 240 chemically identical core protein molecules and, structurally, comprises four groups of symmetrically nonequivalent subunits. We show here that this asymmetry is reflected in solid-state NMR spectra of the capsids, in which peak splitting is observed for a subset of residues. We compare this information to dihedral angle variations from available 3D structures and also to computational predictions of "dynamic" domains and molecular hinges. We find that although, at the given resolution, dihedral angles variations directly obtained from the X-ray structures are not precise enough to be interpreted, the chemical-shift information from NMR correlates, and interestingly goes beyond, information from bioinformatics approaches. Our study reveals the high sensitivity with which NMR can detect the residues allowing the subtle conformational adaptations needed in lattice formation. Our findings are important for understanding the formation and modulation of protein assemblies in general.

Structure of a human catalytic step I spliceosome

Splicing by the spliceosome involves branching and exon ligation. The branching reaction leads to the formation of the catalytic step I spliceosome (C complex). Here we report the cryo-electron microscopy structure of the human C complex at an average resolution of 4.1 angstroms. Compared with the Saccharomyces cerevisiae C complex, the human complex contains 11 additional proteins. The step I splicing factors CCDC49 and CCDC94 (Cwc25 and Yju2 in S. cerevisiae, respectively) closely interact with the DEAH-family adenosine triphosphatase/helicase Prp16 and bridge the gap between Prp16 and the active-site RNA elements. These features, together with structural comparison of the human C and C* complexes, provide mechanistic insights into ribonucleoprotein remodeling and allow the proposition of a working mechanism for the C-to-C* transition.

Normal mode analysis as a method to derive protein dynamics information from the Protein Data Bank

Normal mode analysis (NMA) can facilitate quick and systematic investigation of protein dynamics using data from the Protein Data Bank (PDB). We developed an elastic network model-based NMA program using dihedral angles as independent variables. Compared to the NMA programs that use Cartesian coordinates as independent variables, key attributes of the proposed program are as follows: (1) chain connectivity related to the folding pattern of a polypeptide chain is naturally embedded in the model; (2) the full-atom system is acceptable, and owing to a considerably smaller number of independent variables, the PDB data can be used without further manipulation; (3) the number of variables can be easily reduced by some of the rotatable dihedral angles; (4) the PDB data for any molecule besides proteins can be considered without coarse-graining; and (5) individual motions of constituent subunits and ligand molecules can be easily decomposed into external and internal motions to examine their mutual and intrinsic motions. Its performance is illustrated with an example of a DNA-binding allosteric protein, a catabolite activator protein. In particular, the focus is on the conformational change upon cAMP and DNA binding, and on the communication between their binding sites remotely located from each other. In this illustration, NMA creates a vivid picture of the protein dynamics at various levels of the structures, i.e., atoms, residues, secondary structures, domains, subunits, and the complete system, including DNA and cAMP. Comparative studies of the specific protein in different states, e.g., apo- and holo-conformations, and free and complexed configurations, provide useful information for studying structurally and functionally important aspects of the protein.

Directional Force Originating from ATP Hydrolysis Drives the GroEL Conformational Change

Protein functional mechanisms usually require conformational changes, and often there are known structures for the different conformational states. However, usually neither the origin of the driving force nor the underlying pathways for these conformational transitions is known. Exothermic chemical reactions may be an important source of forces that drive conformational changes. Here we investigate this type of force originating from ATP hydrolysis in the chaperonin GroEL, by applying forces originating from the chemical reaction. Specifically, we apply directed forces to drive the GroEL conformational changes and learn that there is a highly specific direction for applied forces to drive the closed form to the open form. For this purpose, we utilize coarse-grained elastic network models. Principal component analysis on 38 GroEL experimental structures yields the most important motions, and these are used in structural interpolation for the construction of a coarse-grained free energy landscape. In addition, we investigate a more random application of forces with a Monte Carlo method and demonstrate pathways for the closed-open conformational transition in both directions by computing trajectories that are shown upon the free energy landscape. Initial root mean square deviation (RMSD) between the open and closed forms of the subunit is 14.7 Å and final forms from our simulations reach an average RMSD of 3.6 Å from the target forms, closely matching the level of resolution of the coarse-grained model.

Interconversion of inactive to active conformation of MARK2: Insights from molecular modeling and molecular dynamics simulation

The Ser/Thr protein kinase MARK2, also known as Par1b, belongs to the highly-conserved family of PAR proteins which regulate cell polarity and partitioning through the animal kingdom. In the current study, inactive and active structures of human MARK2 were constructed by modeling and molecular dynamics simulation, based on available incomplete crystal structures in Protein Data Bank, to investigate local structural changes through which MARK2 switches from inactive to active state. None of the MARK2 wild type inactive crystal structures represent the position of activation segment. So, the contribution of this loop to the formation of inactive state is not clear. In the modeled structure of inactive MARK2, activation segment occludes the enzyme active site and assumes a relatively stable position. We also presented a detailed description of the major structural changes occur through the activation process and proposed a framework on how these deviations might be affected by the phosphorylation of Thr208 or existence of the UBA domain. Inspection of protein active state in the presence of Mg-ATP, demonstrated the precise arrangement of the various parts of enzyme around Mg-ATP and the importance of their stability in localization of the resulting complex. The results also confirmed the alleged mild auto-inhibitory role of the UBA domain and suggested a reason for the necessity of this role, based on structural similarities to other related kinases.

Knowledge-based entropies improve the identification of native protein structures

Evaluating protein structures requires reliable free energies with good estimates of both potential energies and entropies. Although there are many demonstrated successes from using knowledge-based potential energies, computing entropies of proteins has lagged far behind. Here we take an entirely different approach and evaluate knowledge-based conformational entropies of proteins based on the observed frequencies of contact changes between amino acids in a set of 167 diverse proteins, each of which has two alternative structures. The results show that charged and polar interactions break more often than hydrophobic pairs. This pattern correlates strongly with the average solvent exposure of amino acids in globular proteins, as well as with polarity indices and the sizes of the amino acids. Knowledge-based entropies are derived by using the inverse Boltzmann relationship, in a manner analogous to the way that knowledge-based potentials have been extracted. Including these new knowledge-based entropies almost doubles the performance of knowledge-based potentials in selecting the native protein structures from decoy sets. Beyond the overall energy-entropy compensation, a similar compensation is seen for individual pairs of interacting amino acids. The entropies in this report have immediate applications for 3D structure prediction, protein model assessment, and protein engineering and design.

Single molecule optical measurements of orientation and rotations of biological macromolecules

Subdomains of macromolecules often undergo large orientation changes during their catalytic cycles that are essential for their activity. Tracking these rearrangements in real time opens a powerful window into the link between protein structure and functional output. Site-specific labeling of individual molecules with polarized optical probes and measurement of their spatial orientation can give insight into the crucial conformational changes, dynamics, and fluctuations of macromolecules. Here we describe the range of single molecule optical technologies that can extract orientation information from these probes, review the relevant types of probes and labeling techniques, and highlight the advantages and disadvantages of these technologies for addressing specific inquiries.

Similarity Search of Flexible 3D Molecules Combining Local and Global Shape Descriptors

In this paper, a framework for shape-based similarity search of 3D molecular structures is presented. The proposed framework exploits simultaneously the discriminative capabilities of a global, a local, and a hybrid local-global shape feature to produce a geometric descriptor that achieves higher retrieval accuracy than each feature does separately. Global and hybrid features are extracted using pairwise computations of diffusion distances between the points of the molecular surface, while the local feature is based on accumulating pairwise relations among oriented surface points into local histograms. The local features are integrated into a global descriptor vector using the bag-of-features approach. Due to the intrinsic property of its constituting shape features to be invariant to articulations of the 3D objects, the framework is appropriate for similarity search of flexible 3D molecules, while at the same time it is also accurate in retrieving rigid 3D molecules. The proposed framework is evaluated in flexible and rigid shape matching of 3D protein structures as well as in shape-based virtual screening of large ligand databases with quite promising results.

Mesh Generation and Flexible Shape Comparisons for Bio-Molecules

Novel approaches for generating and comparing flexible (non-rigid) molecular surface meshes are developed. The mesh-generating method is fast and memory-efficient. The resulting meshes are smooth and accurate, and possess high mesh quality. An isometric-invariant shape descriptor based on the Laplace- Beltrami operator is then explored for mesh comparing. The new shape descriptor is more powerful in discriminating different surface shapes but rely only on a small set of signature values. The shape descriptor is applied to shape comparison between molecules with deformed structures. The proposed methods are implemented into a program that can be used as a stand-alone software tool or as a plug-in to other existing molecular modeling tools. Particularly, the code is encapsulated into a software toolkit with a user-friendly graphical interface developed by the authors.

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

CCProf: exploring conformational change profile of proteins

In many biological processes, proteins have important interactions with various molecules such as proteins, ions or ligands. Many proteins undergo conformational changes upon these interactions, where regions with large conformational changes are critical to the interactions. This work presents the CCProf platform, which provides conformational changes of entire proteins, named conformational change profile (CCP) in the context. CCProf aims to be a platform where users can study potential causes of novel conformational changes. It provides 10 biological features, including conformational change, potential binding target site, secondary structure, conservation, disorder propensity, hydropathy propensity, sequence domain, structural domain, phosphorylation site and catalytic site. All these information are integrated into a well-aligned view, so that researchers can capture important relevance between different biological features visually. The CCProf contains 986 187 protein structure pairs for 3123 proteins. In addition, CCProf provides a 3D view in which users can see the protein structures before and after conformational changes as well as binding targets that induce conformational changes. All information (e.g. CCP, binding targets and protein structures) shown in CCProf, including intermediate data are available for download to expedite further analyses.

Database URL: http://zoro.ee.ncku.edu.tw/ccprof/

A stochastic roadmap method to model protein structural transitions

Evidence is emerging that the role of protein structure in disease needs to be rethought. Sequence mutations in proteins are often found to affect the rate at which a protein switches between structures. Modeling structural transitions in wildtype and variant proteins is central to understanding the molecular basis of disease. This paper investigates an efficient algorithmic realization of the stochastic roadmap simulation framework to model structural transitions in wildtype and variants of proteins implicated in human disorders. Our results indicate that the algorithm is able to extract useful information on the impact of mutations on protein structure and 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.

Parsimony in Protein Conformational Change

Protein conformational change is analyzed by finding the minimalist backbone torsion angle rotations that superpose crystal structures within experimental error. Of several approaches for enforcing parsimony during flexible least-squares superposition, an ℓ(1)-norm restraint provided greatest consistency with independent indications of flexibility from nuclear magnetic resonance relaxation dispersion and chemical shift perturbation in arginine kinase and four previously studied systems. Crystallographic cross-validation shows that the dihedral parameterization describes conformational change more accurately than rigid-group approaches. The rotations that superpose the principal elements of structure constitute a small fraction of the raw (φ, ψ) differences that also reflect local conformation and experimental error. Substantial long-range displacements can be mediated by modest dihedral rotations, accommodated even within α helices and β sheets without disruption of hydrogen bonding at the hinges. Consistency between ligand-associated and intrinsic motions (in the unliganded state) implies that induced changes tend to follow low-barrier paths between conformational sub-states that are in intrinsic dynamic equilibrium.

Computing ensembles of transitions with molecular dynamics simulations

A molecular understanding of conformational change is important for connecting structure and function. Without the ability to sample on the meaningful large-scale conformational changes, the ability to infer biological function and to understand the effect of mutations and changes in environment is not possible. Our Dynamic Importance Sampling method (DIMS), part of the CHARMM simulation package, is a method that enables sampling over ensembles of transition intermediates. This chapter outlines the context for the method and the usage within the program.

Solution structure of a designed cyclic peptide ligand for nickel and copper ions

Nuclear magnetic resonance (NMR) spectroscopy was used to study a cyclic peptide derived from the amino-terminal copper-and-nickel-binding (ATCUN) motif. The three-dimensional structure of the unliganded peptide in aqueous solution was solved by simulated annealing using distance constraints derived from Nuclear Overhauser Effects. A structural model for the Ni(II)-bound complex was also produced based on NMR evidence and prior spectroscopic data, which are consistent with crystal structures of linear ATCUN complexes. Structural interpolation, or "morphing," was used to understand the transition of this highly structured cyclic peptide from its unliganded structure to its metal-ion-bound structure.

Polyphony: superposition independent methods for ensemble-based drug discovery

Background

Structure-based drug design is an iterative process, following cycles of structural biology, computer-aided design, synthetic chemistry and bioassay. In favorable circumstances, this process can lead to the structures of hundreds of protein-ligand crystal structures. In addition, molecular dynamics simulations are increasingly being used to further explore the conformational landscape of these complexes. Currently, methods capable of the analysis of ensembles of crystal structures and MD trajectories are limited and usually rely upon least squares superposition of coordinates.

Results

Novel methodologies are described for the analysis of multiple structures of a protein. Statistical approaches that rely upon residue equivalence, but not superposition, are developed. Tasks that can be performed include the identification of hinge regions, allosteric conformational changes and transient binding sites. The approaches are tested on crystal structures of CDK2 and other CMGC protein kinases and a simulation of p38α. Known interaction - conformational change relationships are highlighted but also new ones are revealed. A transient but druggable allosteric pocket in CDK2 is predicted to occur under the CMGC insert. Furthermore, an evolutionarily-conserved conformational link from the location of this pocket, via the αEF-αF loop, to phosphorylation sites on the activation loop is discovered.

Conclusions

New methodologies are described and validated for the superimposition independent conformational analysis of large collections of structures or simulation snapshots of the same protein. The methodologies are encoded in a Python package called Polyphony, which is released as open source to accompany this paper [http://wrpitt.bitbucket.org/polyphony/].

Decoding the structural events in substrate-gating mechanism of eukaryotic prolyl oligopeptidase using normal mode analysis and molecular dynamics simulations

Prolyl oligopeptidase (POP) is a serine protease, unique for its ability to cleave various small oligopeptides shorter than 30 amino acids. POP is an important drug target since it is implicated in various neurological disorders. Although there is structural evidence that bacterial POPs undergo huge interdomain movements and acquire an "open" state in the substrate-unbound form, hitherto, no crystal structure is available in the substrate-unbound domain-open form of eukaryotic POPs. Indeed, there is no difference between the substrate-unbound/bound states of eukaryotic POPs. This raises unanswered questions about whether difference in the substrate access pathway exists between bacterial and eukaryotic POPs. Here, we have used normal mode analysis and molecular dynamics to unravel the mechanism of substrate entry in mammalian POPs, which has been debated until now. Motions observed using normal modes of porcine and bacterial POPs were analyzed and compared, augmented by molecular dynamics of these proteins. Identical to bacterial POPs, interdomain opening was found to be the possible pathway for the substrate-gating in mammals as well. On the basis of our analyses and evidences, a mechanistic model of substrate entry in POPs has been proposed. Up-down movement of N-terminal hydrolase domain resulted in twisting motion of two domains, followed by the conformational changes of interdomain loop regions, which facilitate interdomain opening. Similar to bacterial POPs, an open form of porcine POP is also proposed with domain-closing motion. This work has direct implications for the development of novel inhibitors of mammalian POPs to understand the etiology of various neurological diseases.

MORPH-PRO: a novel algorithm and web server for protein morphing

Background

Proteins are known to be dynamic in nature, changing from one conformation to another while performing vital cellular tasks. It is important to understand these movements in order to better understand protein function. At the same time, experimental techniques provide us with only single snapshots of the whole ensemble of available conformations. Computational protein morphing provides a visualization of a protein structure transitioning from one conformation to another by producing a series of intermediate conformations.

Results

We present a novel, efficient morphing algorithm, Morph-Pro based on linear interpolation. We also show that apart from visualization, morphing can be used to provide plausible intermediate structures. We test this by using the intermediate structures of a c-Jun N-terminal kinase (JNK1) conformational change in a virtual docking experiment. The structures are shown to dock with higher score to known JNK1-binding ligands than structures solved using X-Ray crystallography. This experiment demonstrates the potential applications of the intermediate structures in modeling or virtual screening efforts.

Conclusions

Visualization of protein conformational changes is important for characterization of protein function. Furthermore, the intermediate structures produced by our algorithm are good approximations to true structures. We believe there is great potential for these computationally predicted structures in protein-ligand docking experiments and virtual screening. The Morph-Pro web server can be accessed at http://morph-pro.bioinf.spbau.ru.

VLDP web server: a powerful geometric tool for analysing protein structures in their environment

Protein structures are an ensemble of atoms determined experimentally mostly by X-ray crystallography or Nuclear Magnetic Resonance. Studying 3D protein structures is a key point for better understanding protein function at a molecular level. We propose a set of accurate tools, for analysing protein structures, based on the reliable method of Voronoi–Laguerre tessellations. The Voronoi Laguerre Delaunay Protein web server (VLDPws) computes the Laguerre tessellation on a whole given system first embedded in solvent. Through this fine description, VLDPws gives the following data: (i) Amino acid volumes evaluated with high precision, as confirmed by good correlations with experimental data. (ii) A novel definition of inter-residue contacts within the given protein. (iii) A measure of the residue exposure to solvent that significantly improves the standard notion of accessibility in some cases. At present, no equivalent web server is available. VLDPws provides output in two complementary forms: direct visualization of the Laguerre tessellation, mostly its polygonal molecular surfaces; files of volumes; and areas, contacts and similar data for each residue and each atom. These files are available for download for further analysis. VLDPws can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/vldp.

X-ray structure of the mammalian GIRK2-βγ G-protein complex

G protein-gated inward rectifier K⁺ (GIRK) channels allow neurotransmitters, via G protein-coupled receptor stimulation, to control cellular electrical excitability. In cardiac and neuronal cells this control regulates heart rate and neural circuit activity. We present the 3.5 Å resolution crystal structure of the mammalian GIRK2 channel in complex with βγ G protein subunits, the central signaling complex that links G protein-coupled receptor stimulation to K⁺ channel activity. Short-range atomic and long-range electrostatic interactions stabilize four βγ G protein subunits at the interfaces between four K⁺ channel subunits, inducing a pre-open state of the channel. The pre-open state exhibits a conformation that is intermediate between the closed and constitutively active mutant, open conformations. The resultant structural picture is compatible with “membrane delimited” activation of GIRK channels by G proteins and the characteristic burst kinetics of channel gating. The structures also permit a conceptual understanding of how the signaling lipid PIP₂ and intracellular Na⁺ ions participate in multi-ligand regulation of GIRK channels.

Partial cooperative unfolding in proteins as observed by hydrogen exchange mass spectrometry

Many proteins do not exist in a single rigid conformation. Protein motions, or dynamics, exist and in many cases are important for protein function. The analysis of protein dynamics relies on biophysical techniques that can distinguish simultaneously existing populations of molecules and their rates of interconversion. Hydrogen exchange (HX) detected by mass spectrometry (MS) is contributing to our understanding of protein motions by revealing unfolding and dynamics on a wide timescale, ranging from seconds to hours to days. In this review we discuss HX MS-based analyses of protein dynamics, using our studies of multi-domain kinases as examples. Using HX MS, we have successfully probed protein dynamics and unfolding in the isolated SH3, SH2 and kinase domains of the c-Src and Abl kinase families, as well as the role of inter- and intra-molecular interactions in the global control of kinase function. Coupled with high-resolution structural information, HX MS has proved to be a powerful and versatile tool for the analysis of the conformational dynamics in these kinase systems, and has provided fresh insight regarding the regulatory control of these important signaling proteins. HX MS studies of dynamics are applicable not only to the proteins we illustrate here, but to a very wide range of proteins and protein systems, and should play a role in both classification of and greater understanding of the prevalence of protein motion.

Structural origins of DNA target selection and nucleobase extrusion by a DNA cytosine methyltransferase

BACKGROUND

How DNA 5-cytosine methyltransferases (DCMTases) select their substrate nucleobase for extrusion from DNA duplex is poorly understood.

RESULTS

The crystal structure of a pre-extrusion M.HaeIII DCMTase-substrate DNA complex is reported here.

CONCLUSION

M.HaeIII selects its substrate cytosine for extrusion by selectively interfering with its stacking and hydrogen bonding interactions within the DNA duplex.

SIGNIFICANCE

This is the first structural elucidation of the target cytosine selection by a DCMTase. Epigenetic methylation of cytosine residues in DNA is an essential element of genome maintenance and function in organisms ranging from bacteria to humans. DNA 5-cytosine methyltransferase enzymes (DCMTases) catalyze cytosine methylation via reaction intermediates in which the DNA is drastically remodeled, with the target cytosine residue extruded from the DNA helix and plunged into the active site pocket of the enzyme. We have determined a crystal structure of M.HaeIII DCMTase in complex with its DNA substrate at a previously unobserved state, prior to extrusion of the target cytosine and frameshifting of the DNA recognition sequence. The structure reveals that M.HaeIII selects the target cytosine and destabilizes its base-pairing through a precise, focused, and coordinated assault on the duplex DNA, which isolates the target cytosine from its nearest neighbors and thereby facilitates its extrusion from DNA.

PheVI:09 (Phe6.44) as a sliding microswitch in seven-transmembrane (7TM) G protein-coupled receptor activation

In seven-transmembrane (7TM), G protein-coupled receptors, highly conserved residues function as microswitches, which alternate between different conformations and interaction partners in an extended allosteric interface between the transmembrane segments performing the large scale conformational changes upon receptor activation. Computational analysis using x-ray structures of the β(2)-adrenergic receptor demonstrated that PheVI:09 (6.44), which in the inactive state is locked between the backbone and two hydrophobic residues in transmembrane (TM)-III, upon activation slides ∼2 Å toward TM-V into a tight pocket generated by five hydrophobic residues protruding from TM-III and TM-V. Of these, the residue in position III:16 (3.40) (often an Ile or Val) appears to function as a barrier or gate for the transition between inactive and active conformation. Mutational analysis showed that PheVI:09 is essential for the constitutive and/or agonist-induced signaling of the ghrelin receptor, GPR119, the β(2)-adrenergic receptor, and the neurokinin-1 receptor. Substitution of the residues constituting the hydrophobic pocket between TM-III and TM-V in the ghrelin receptor in four of five positions impaired receptor signaling. In GPR39, representing the 12% of 7TM receptors lacking an aromatic residue at position VI:09, unchanged agonist-induced signaling was observed upon Ala substitution of LeuVI:09 despite reduced cell surface expression of the mutant receptor. It is concluded that PheVI:09 constitutes an aromatic microswitch that stabilizes the active, outward tilted conformation of TM-VI relative to TM-III by sliding into a tight hydrophobic pocket between TM-III and TM-V and that the hydrophobic residue in position III:16 constitutes a gate for this transition.

Probing the diverse landscape of protein flexibility and binding

Protein flexibility spans a broad spectrum, from highly stable folded to intrinsically disordered states. In this review, we discuss how various techniques, including X-ray crystallography, nuclear magnetic resonance spectroscopy and ensemble-modeling strategies employing various experimental measurements, have enabled detailed structural and dynamic characterizations of proteins in their free and bound states. This has revealed a variety of possible binding scenarios in which flexibility can either decrease or increase upon binding. Furthermore, dynamic free-state ensembles have repeatedly been observed to contain transiently formed conformations that partially or completely resemble bound states. These results demonstrate an intimate connection between protein flexibility and protein interactions and illustrate the huge diversity of structure and dynamics in both free proteins and protein complexes.

The KCNE Tango - How KCNE1 Interacts with Kv7.1

The classical tango is a dance characterized by a 2/4 or 4/4 rhythm in which the partners dance in a coordinated way, allowing dynamic contact. There is a surprising similarity between the tango and how KCNE β-subunits "dance" to the fast rhythm of the cell with their partners from the Kv channel family. The five KCNE β-subunits interact with several members of the Kv channels, thereby modifying channel gating via the interaction of their single transmembrane-spanning segment, the extracellular amino terminus, and/or the intracellular carboxy terminus with the Kv α-subunit. Best studied is the molecular basis of interactions between KCNE1 and Kv7.1, which, together, supposedly form the native cardiac I(Ks) channel. Here we review the current knowledge about functional and molecular interactions of KCNE1 with Kv7.1 and try to summarize and interpret the tango of the KCNEs.