Functional aspects of protein flexibility

On the possible role of protein vibrations in information processing in the brain: three Russian dolls

Until recently it was held that the neurocomputations conducted by the brain involved only whole neurons as the operating units. This may however represent only a part of the mechanism. This theoretical and academic position article reviews the considerable evidence that allosteric interactions between proteins (as extensively described by Fuxe et al., 2014), and in particular protein vibrations in neurons, form small scale codes that are involved as parts of the complex information processing systems of the brain. The argument is then developed to suggest that the protein allosteric and vibration codes (that operate at the molecular level) are nested within a medium scale coding system whose computational units are organelles (such as microtubules). This medium scale code is nested in turn inside a large scale coding system, whose computational units are individual neurons. The hypothesis suggests that these three levels interact vertically in both directions thus materially increasing the computational capacity of the brain. The whole hierarchy is thus similar to three nested Russian dolls. This theoretical development may be of use in the design of experiments to test it.

Globular and disordered-the non-identical twins in protein-protein interactions

In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1).

The statistical conformation of a highly flexible protein: small-angle X-ray scattering of S. aureus protein A

Staphylococcal protein A (SpA) is a multidomain protein consisting of five globular IgG binding domains separated by a conserved six- to nine-residue flexible linker. We collected SAXS data on the N-terminal protein-binding half of SpA (SpA-N) and constructs consisting of one to five domain modules in order to determine statistical conformation of this important S. aureus virulence factor. We fit the SAXS data to a scattering function based on a new polymer physics model, which provides an analytical description of the SpA-N statistical conformation. We describe a protocol for systematically determining the appropriate level of modeling to fit a SAXS data set based on goodness of fit and whether the addition of parameters improves it. In the case of SpA-N, the analytical polymer physics description provides a depiction of the statistical conformation of a flexible protein that, while lacking atomistic detail, properly reflects the information content of the data.

A multiparametric computational algorithm for comprehensive assessment of genetic mutations in mucopolysaccharidosis type IIIA (Sanfilippo syndrome)

Mucopolysaccharidosis type IIIA (MPS-IIIA, Sanfilippo syndrome) is a Lysosomal Storage Disease caused by cellular deficiency of N-sulfoglucosamine sulfohydrolase (SGSH). Given the large heterogeneity of genetic mutations responsible for the disease, a comprehensive understanding of the mechanisms by which these mutations affect enzyme function is needed to guide effective therapies. We developed a multiparametric computational algorithm to assess how patient genetic mutations in SGSH affect overall enzyme biogenesis, stability, and function. 107 patient mutations for the SGSH gene were obtained from the Human Gene Mutation Database representing all of the clinical mutations documented for Sanfilippo syndrome. We assessed each mutation individually using ten distinct parameters to give a comprehensive predictive score of the stability and misfolding capacity of the SGSH enzyme resulting from each of these mutations. The predictive score generated by our multiparametric algorithm yielded a standardized quantitative assessment of the severity of a given SGSH genetic mutation toward overall enzyme activity. Application of our algorithm has identified SGSH mutations in which enzymatic malfunction of the gene product is specifically due to impairments in protein folding. These scores provide an assessment of the degree to which a particular mutation could be treated using approaches such as chaperone therapies. Our multiparametric protein biogenesis algorithm advances a key understanding in the overall biochemical mechanism underlying Sanfilippo syndrome. Importantly, the design of our multiparametric algorithm can be tailored to many other diseases of genetic heterogeneity for which protein misfolding phenotypes may constitute a major component of disease manifestation.

On the relationship between low-frequency normal modes and the large-scale conformational changes of proteins

Normal mode analysis is a computational technique that allows to study the dynamics of biological macromolecules. It was first applied to small protein cases, more than thirty years ago. The interest in this technique then raised when it was realized that it can provide insights about the large-scale conformational changes a protein can experience, for instance upon ligand binding. As it was also realized that studying highly simplified protein models can provide similar insights, meaning that this kind of analysis can be both quick and simple to handle, several applications were proposed, in the context of various structural biology techniques. This review focuses on these applications, as well as on how the functional relevance of the lowest-frequency modes of proteins was established.

Integrating protein structural dynamics and evolutionary analysis with Bio3D

Background

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution.

Results

Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case.

Conclusions

The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0399-6) contains supplementary material, which is available to authorized users.

Shedding light on protein folding, structural and functional dynamics by single molecule studies

The advent of advanced single molecule measurements unveiled a great wealth of dynamic information revolutionizing our understanding of protein dynamics and behavior in ways unattainable by conventional bulk assays. Equipped with the ability to record distribution of behaviors rather than the mean property of a population, single molecule measurements offer observation and quantification of the abundance, lifetime and function of multiple protein states. They also permit the direct observation of the transient and rarely populated intermediates in the energy landscape that are typically averaged out in non-synchronized ensemble measurements. Single molecule studies have thus provided novel insights about how the dynamic sampling of the free energy landscape dictates all aspects of protein behavior; from its folding to function. Here we will survey some of the state of the art contributions in deciphering mechanisms that underlie protein folding, structural and functional dynamics by single molecule fluorescence microscopy techniques. We will discuss a few selected examples highlighting the power of the emerging techniques and finally discuss the future improvements and directions.

A disordered region in the EvpP protein from the type VI secretion system of Edwardsiella tarda is essential for EvpC binding

The type VI secretion system (T6SS) of pathogenic bacteria plays important roles in both virulence and inter-bacterial competitions. The effectors of T6SS are presumed to be transported either by attaching to the tip protein or by interacting with HcpI (haemolysin corregulated protein 1). In Edwardsiella tarda PPD130/91, the T6SS secreted protein EvpP (E. tardavirulent protein P) is found to be essential for virulence and directly interacts with EvpC (Hcp-like), suggesting that it could be a potential effector. Using limited protease digestion, nuclear magnetic resonance heteronuclear Nuclear Overhauser Effects, and hydrogen-deuterium exchange mass spectrometry, we confirmed that the dimeric EvpP (40 kDa) contains a substantial proportion (40%) of disordered regions but still maintains an ordered and folded core domain. We show that an N-terminal, 10-kDa, protease-resistant fragment in EvpP connects to a shorter, 4-kDa protease-resistant fragment through a highly flexible region, which is followed by another disordered region at the C-terminus. Within this C-terminal disordered region, residues Pro143 to Ile168 are essential for its interaction with EvpC. Unlike the highly unfolded T3SS effector, which has a lower molecular weight and is maintained in an unfolded conformation with a dedicated chaperone, the T6SS effector seems to be relatively larger, folded but partially disordered and uses HcpI as a chaperone.

The role of proline substitutions within flexible regions on thermostability of luciferase

Improving the stability of firefly luciferase has been a critical issue for its wider industrial applications. Studies about hyperthermophile proteins show that flexibility could be an effective indicator to find out weak spots to engineering thermostability of proteins. However, the relationship among flexibility, activity and stability in most of proteins is unclear. Proline is the most rigid residue and can be introduced to rigidify flexible regions to enhance thermostability of proteins. We firstly apply three different methods, molecular dynamics (MD) simulation, B-FITTER and framework rigidity optimized dynamics algorithm (FRODA) to determine the flexible regions of Photinus pyralis luciferase: Fragment 197-207; Fragment 471-481 and Fragment 487-495. Then, introduction of proline is used to rigidify these flexible regions. Two mutants D476P and H489P within most flexible regions are finally designed. In the results, H489P mutant shows improved thermostability while maintaining its catalytic efficiency compared to that of wild type luciferase. Flexibility analysis confirms that the overall rigidity and local rigidity of H489P mutant are greatly strengthened. D476P mutant shows decreased thermosatbility and the reason for this is elucidated at the molecular level. S307P mutation is randomly chosen outside the flexible regions as a control. Thermostability analysis shows that S307P mutation has decreased kinetic stability and enhanced thermodynamic stability.

Bovine serum albumin with glycated carboxyl groups shows membrane-perturbing activities

The aim of the present study aimed to investigate whether glycated bovine serum albumin (BSA) showed novel activities on the lipid-water interface. Mannosylated BSA (Man-BSA) was prepared by modification of the carboxyl groups with p-aminophenyl α-d-mannopyranoside. In contrast to BSA, Man-BSA notably induced membrane permeability of egg yolk phosphatidylcholine (EYPC)/egg yolk sphingomyelin (EYSM)/cholesterol (Chol) and EYPC/EYSM vesicles. Noticeably, Man-BSA induced the fusion of EYPC/EYSM/Chol vesicles, but not of EYPC/EYSM vesicles. Although BSA and Man-BSA showed similar binding affinity for lipid vesicles, the lipid-bound conformation of Man-BSA was distinct from that of BSA. Moreover, Man-BSA adopted distinct structure upon binding with the EYPC/EYSM/Chol and EYPC/EYSM vesicles. Man-BSA could induce the fusion of EYPC/EYSM/Chol vesicles with K562 and MCF-7 cells, while Man-BSA greatly induced the leakage of Chol-depleted K562 and MCF-7 cells. The modified BSA prepared by conjugating carboxyl groups with p-aminophenyl α-d-glucopyranoside also showed membrane-perturbing activities. Collectively, our data indicate that conjugation of carboxyl groups with monosaccharide generates functional BSA with membrane-perturbing activities on the lipid-water interface.

Specificity and affinity quantification of flexible recognition from underlying energy landscape topography

Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition.

Flexibility in biomolecular recognition is crucial for the function. Flexibility often leads to moderate binding affinity but high binding specificity, challenging the conventional wisdom that high specificity is guaranteed by high affinity. Currently, understanding of the relationship between affinity and specificity in flexible biomolecular recognition is still obscure, even in a qualitative way. By exploring the intrinsic biomolecular recognition energy landscapes, we provided a novel way to quantify the thermodynamic intrinsic specificity by energy landscape topography and kinetic specificity by association rate. We show quantitatively that flexibility decreases binding affinity while increases binding specificity, and the relative changes in affinity and specificity are strongly correlated with the degree of flexibility. Our results show that more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Importantly, we demonstrated that flexibility modulates affinity and specificity through the underlying energy landscape. Our study establishes the quantitative relationship among flexibility, affinity and specificity, bridging the gap between theory and experiments.

From protein sequence to dynamics and disorder with DynaMine

Protein function and dynamics are closely related; however, accurate dynamics information is difficult to obtain. Here based on a carefully assembled data set derived from experimental data for proteins in solution, we quantify backbone dynamics properties on the amino-acid level and develop DynaMine--a fast, high-quality predictor of protein backbone dynamics. DynaMine uses only protein sequence information as input and shows great potential in distinguishing regions of different structural organization, such as folded domains, disordered linkers, molten globules and pre-structured binding motifs of different sizes. It also identifies disordered regions within proteins with an accuracy comparable to the most sophisticated existing predictors, without depending on prior disorder knowledge or three-dimensional structural information. DynaMine provides molecular biologists with an important new method that grasps the dynamical characteristics of any protein of interest, as we show here for human p53 and E1A from human adenovirus 5.

SDS, a structural disruption score for assessment of missense variant deleteriousness

We have developed a novel structure-based evaluation for missense variants that explicitly models protein structure and amino acid properties to predict the likelihood that a variant disrupts protein function. A structural disruption score (SDS) is introduced as a measure to depict the likelihood that a case variant is functional. The score is constructed using characteristics that distinguish between causal and neutral variants within a group of proteins. The SDS score is correlated with standard sequence-based deleteriousness, but shows promise for improving discrimination between neutral and causal variants at less conserved sites. The prediction was performed on 3-dimentional structures of 57 gene products whose homozygous SNPs were identified as case-exclusive variants in an exome sequencing study of epilepsy disorders. We contrasted the candidate epilepsy variants with scores for likely benign variants found in the EVS database, and for positive control variants in the same genes that are suspected to promote a range of diseases. To derive a characteristic profile of damaging SNPs, we transformed continuous scores into categorical variables based on the score distribution of each measurement, collected from all possible SNPs in this protein set, where extreme measures were assumed to be deleterious. A second epilepsy dataset was used to replicate the findings. Causal variants tend to receive higher sequence-based deleterious scores, induce larger physico-chemical changes between amino acid pairs, locate in protein domains, buried sites or on conserved protein surface clusters, and cause protein destabilization, relative to negative controls. These measures were agglomerated for each variant. A list of nine high-priority putative functional variants for epilepsy was generated. Our newly developed SDS protocol facilitates SNP prioritization for experimental validation.

The DynaMine webserver: predicting protein dynamics from sequence

Protein dynamics are important for understanding protein function. Unfortunately, accurate protein dynamics information is difficult to obtain: here we present the DynaMine webserver, which provides predictions for the fast backbone movements of proteins directly from their amino-acid sequence. DynaMine rapidly produces a profile describing the statistical potential for such movements at residue-level resolution. The predicted values have meaning on an absolute scale and go beyond the traditional binary classification of residues as ordered or disordered, thus allowing for direct dynamics comparisons between protein regions. Through this webserver, we provide molecular biologists with an efficient and easy to use tool for predicting the dynamical characteristics of any protein of interest, even in the absence of experimental observations. The prediction results are visualized and can be directly downloaded. The DynaMine webserver, including instructive examples describing the meaning of the profiles, is available at http://dynamine.ibsquare.be.

Toward in silico biomolecular manipulation through static modes: atomic scale characterization of HIV-1 protease flexibility

Probing biomolecular flexibility with atomic-scale resolution is a challenging task in current computational biology for fundamental understanding and prediction of biomolecular interactions and associated functions. This paper makes use of the static mode method to study HIV-1 protease considered as a model system to investigate the full biomolecular flexibility at the atomic scale, the screening of active site biomechanical properties, the blind prediction of allosteric sites, and the design of multisite strategies to target deformations of interest. Relying on this single calculation run of static modes, we demonstrate that in silico predictive design of an infinite set of complex excitation fields is reachable, thanks to the storage of the static modes in a data bank that can be used to mimic single or multiatom contact and efficiently anticipate conformational changes arising from external stimuli. All along this article, we compare our results to data previously published and propose a guideline for efficient, predictive, and custom in silico experiments.

Mechanism of Assembly of the Non-Covalent Spectrin Tetramerization Domain from Intrinsically Disordered Partners

Interdomain interactions of spectrin are critical for maintenance of the erythrocyte cytoskeleton. In particular, “head-to-head” dimerization occurs when the intrinsically disordered C-terminal tail of β-spectrin binds the N-terminal tail of α-spectrin, folding to form the “spectrin tetramer domain”. This non-covalent three-helix bundle domain is homologous in structure and sequence to previously studied spectrin domains. We find that this tetramer domain is surprisingly kinetically stable. Using a protein engineering Φ-value analysis to probe the mechanism of formation of this tetramer domain, we infer that the domain folds by the docking of the intrinsically disordered β-spectrin tail onto the more structured α-spectrin tail.

Engineering proteins for thermostability through rigidifying flexible sites

Engineering proteins for thermostability is an exciting and challenging field since it is critical for broadening the industrial use of recombinant proteins. Thermostability of proteins arises from the simultaneous effect of several forces such as hydrophobic interactions, disulfide bonds, salt bridges and hydrogen bonds. All of these interactions lead to decreased flexibility of polypeptide chain. Structural studies of mesophilic and thermophilic proteins showed that the latter need more rigid structures to compensate for increased thermal fluctuations. Hence flexibility can be an indicator to pinpoint weak spots for enhancing thermostability of enzymes. A strategy has been proven effective in enhancing proteins' thermostability with two steps: predict flexible sites of proteins firstly and then rigidify these sites. We refer to this approach as rigidify flexible sites (RFS) and give an overview of such a method through summarizing the methods to predict flexibility of a protein, the methods to rigidify residues with high flexibility and successful cases regarding enhancing thermostability of proteins using RFS.

Structure and dynamic properties of membrane proteins using NMR

Integral membrane proteins are one of the most challenging groups of macromolecules despite their apparent conformational simplicity. They manage and drive transport, circulate information, and participate in cellular movements via interactions with other proteins and through intricate conformational changes. Their structural and functional decoding is challenging and has imposed demanding experimental development. Solution nuclear magnetic resonance (NMR) spectroscopy is one of the techniques providing the capacity to make a significant difference in the deciphering of the membrane protein structure-function paradigm. The method has evolved dramatically during the last decade resulting in a plethora of new experiments leading to a significant increase in the scientific repertoire for studying membrane proteins. Besides solving the three-dimensional structures using state-of-the-art approaches, a large variety of developments of well-established techniques are available providing insight into membrane protein flexibility, dynamics, and interactions. Inspired by the speed of development in the application of new strategies, by invention of methods to measure solvent accessibility and describe low-populated states, this review seeks to introduce the vast possibilities solution NMR can offer to the study of membrane protein structure-function analyses with special focus on applicability.

A simple method to measure protein side-chain mobility using NMR chemical shifts

Protein side-chain motions are involved in many important biological processes including enzymatic catalysis, allosteric regulation, and the mediation of protein-protein, protein-DNA, protein-RNA, and protein-cofactor interactions. NMR spectroscopy has long been used to provide insights into the motions of side-chain groups. Currently, the method of choice for studying side-chain dynamics by NMR is the measurement of methyl (2)H autorelaxation. Methyl (2)H autorelaxation exhibits simple relaxation mechanisms and can be straightforwardly converted to meaningful dynamic parameters. However, methyl groups can only be found in 6 of 19 side-chain bearing amino acids. Consequently, only a sparse assessment of protein side-chain dynamics is possible. Therefore, there is a significant interest in developing novel methods of studying side-chain motions that can be applied to all types of side-chains. Here, we show how side-chain chemical shifts can be used to determine the magnitude of fast side-chain motions in proteins. The chemical shift method is applicable to all side-chain bearing residues and does not require any additional measurements beyond standard NMR experiments for backbone and side-chain assignments.

Mapping the intramolecular signal propagation pathways in protein using Bayesian change point analysis of atomic motions

We propose to use change points of atomic positions in the molecular dynamics trajectory as indicators of the propagating signals in protein. We designate these changes as signals because they can propagate within the molecule in the form of "perturbation wave", transmit energy or information between different parts of protein, and serve as allosteric signals. We found that change points can distinguish between thermal fluctuations of atoms (noise) and signals in a protein despite the differences in the motility of amino acid residues. Clustering of the spatially close residues that were experiencing change points close in time, allowed us to map pathways of signal propagation in a protein at the atomic level of resolution. We propose a potential mechanism for the origin of the signal and its propagation that relies on the autonomic coherence resonance in atomic fluctuations. According to this mechanism, random synchronization of fluctuations of neighboring atoms results in a resonance, which increases amplitude of vibration of these atoms. This increase can be transmitted to the atoms colliding with the resonant atoms, leading to the propagating signal. The wavelet-based coherence analysis of the inter-atomic distances between carbon-alpha atoms and surrounding atoms for the residue pairs that belong to the same communication pathway allowed us to find time periods with temporarily locked phases, confirming the occurrence of conditions for resonance. Analysis of the mapped pathways demonstrated that they form a network that connects different regions of the protein.

Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure

Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and β-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.

Structural dynamics flexibility informs function and evolution at a proteome scale

Protein structures are dynamic entities with a myriad of atomic fluctuations, side-chain rotations, and collective domain movements. Although the importance of these dynamics to proper functioning of proteins is emerging in the studies of many protein families, there is a lack of broad evidence for the critical role of protein dynamics in shaping the biological functions of a substantial fraction of residues for a large number of proteins in the human proteome. Here, we propose a novel dynamic flexibility index (dfi) to quantify the dynamic properties of individual residues in any protein and use it to assess the importance of protein dynamics in 100 human proteins. Our analyses involving functionally critical positions, disease-associated and putatively neutral population variations, and the rate of interspecific substitutions per residue produce concordant patterns at a proteome scale. They establish that the preservation of dynamic properties of residues in a protein structure is critical for maintaining the protein/biological function. Therefore, structural dynamics needs to become a major component of the analysis of protein function and evolution. Such analyses will be facilitated by the dfi, which will also enable the integrative use of structural dynamics with evolutionary conservation in genomic medicine as well as functional genomics investigations.

Effects of molecular crowding on the dynamics of intrinsically disordered proteins

Inside cells, the concentration of macromolecules can reach up to 400 g/L. In such crowded environments, proteins are expected to behave differently than in vitro. It has been shown that the stability and the folding rate of a globular protein can be altered by the excluded volume effect produced by a high density of macromolecules. However, macromolecular crowding effects on intrinsically disordered proteins (IDPs) are less explored. These proteins can be extremely dynamic and potentially sample a wide ensemble of conformations under non-denaturing conditions. The dynamic properties of IDPs are intimately related to the timescale of conformational exchange within the ensemble, which govern target recognition and how these proteins function. In this work, we investigated the macromolecular crowding effects on the dynamics of several IDPs by measuring the NMR spin relaxation parameters of three disordered proteins (ProTα, TC1, and α-synuclein) with different extents of residual structures. To aid the interpretation of experimental results, we also performed an MD simulation of ProTα. Based on the MD analysis, a simple model to correlate the observed changes in relaxation rates to the alteration in protein motions under crowding conditions was proposed. Our results show that 1) IDPs remain at least partially disordered despite the presence of high concentration of other macromolecules, 2) the crowded environment has differential effects on the conformational propensity of distinct regions of an IDP, which may lead to selective stabilization of certain target-binding motifs, and 3) the segmental motions of IDPs on the nanosecond timescale are retained under crowded conditions. These findings strongly suggest that IDPs function as dynamic structural ensembles in cellular environments.

Comparing proteins by their internal dynamics: exploring structure-function relationships beyond static structural alignments

The growing interest for comparing protein internal dynamics owes much to the realisation that protein function can be accompanied or assisted by structural fluctuations and conformational changes. Analogously to the case of functional structural elements, those aspects of protein flexibility and dynamics that are functionally oriented should be subject to evolutionary conservation. Accordingly, dynamics-based protein comparisons or alignments could be used to detect protein relationships that are more elusive to sequence and structural alignments. Here we provide an account of the progress that has been made in recent years towards developing and applying general methods for comparing proteins in terms of their internal dynamics and advance the understanding of the structure-function relationship.

Computer-Aided Protein Directed Evolution: a Review of Web Servers, Databases and other Computational Tools for Protein Engineering

The combination of computational and directed evolution methods has proven a winning strategy for protein engineering. We refer to this approach as computer-aided protein directed evolution (CAPDE) and the review summarizes the recent developments in this rapidly growing field. We will restrict ourselves to overview the availability, usability and limitations of web servers, databases and other computational tools proposed in the last five years. The goal of this review is to provide concise information about currently available computational resources to assist the design of directed evolution based protein engineering experiment.

A dynamic model of long-range conformational adaptations triggered by nucleotide binding in GroEL-GroES

The molecular chaperone, GroEL, essential for correct protein folding in E. coli, is composed of 14 identical subunits organized in two interacting rings, each providing a folding chamber for non-native substrate proteins. The oligomeric assembly shows positive cooperativity within each ring and negative cooperativity between the rings. Although it is well known that ATP and long-range allosteric interactions drive the functional cycle of GroEL, an atomic resolution view of how ligand binding modulates conformational adaptations over long distances remains a major challenge. Moreover, little is known on the relation between equilibrium dynamics at physiological temperatures and the allosteric transitions in GroEL. Here we present multiple all-atom molecular dynamics simulations of the GroEL-GroES assemblies at different stages of the functional cycle. Combined with an extensive analysis of the complete set of experimentally available structures, principal component analysis and conformer plots, we provide an explicit evaluation of the accessible conformational space of unliganded GroEL. Our results suggest the presence of pre-existing conformers at the equatorial domain level, and a shift of the conformational ensemble upon ATP-binding. At the inter-ring interface the simulations capture a remarkable offset motion of helix D triggered by ATP-binding to the folding active ring. The reorientation of helix D, previously only observed upon GroES association, correlates with a change of the internal dynamics in the opposite ring. This work contributes to the understanding of the molecular mechanisms in GroEL and highlights the ability of all-atom MD simulations to model long-range structural changes and allosteric events in large systems.

xPyder: a PyMOL plugin to analyze coupled residues and their networks in protein structures

A versatile method to directly identify and analyze short- or long-range coupled or communicating residues in a protein conformational ensemble is of extreme relevance to achieve a complete understanding of protein dynamics and structural communication routes. Here, we present xPyder, an interface between one of the most employed molecular graphics systems, PyMOL, and the analysis of dynamical cross-correlation matrices (DCCM). The approach can also be extended, in principle, to matrices including other indexes of communication propensity or intensity between protein residues, as well as the persistence of intra- or intermolecular interactions, such as those underlying protein dynamics. The xPyder plugin for PyMOL 1.4 and 1.5 is offered as Open Source software via the GPL v2 license, and it can be found, along with the installation package, the user guide, and examples, at http://linux.btbs.unimib.it/xpyder/.

Association of CfLGBP gene polymorphism with disease susceptibility/resistance of Zhikong scallop (Chlamys farreri) to Listonella anguillarum

Lipopolysaccharide and β-1, 3-glucan binding protein (LGBP) is a pattern recognition receptor (PRR) recognizing and binding both LPS and β-1, 3-glucan, playing important roles in innate immunity. In the present study, the single nucleotide polymorphisms (SNPs) were assessed in LGBP gene from scallop Chlamys farreri (designated CfLGBP), and eight SNPs were found in its potential LPS and glucanase binding motif. The locus +7679 with the transition of G-A, which produced an amino acid substitution at codon 360 from a non polar Glycine to polar Serine, was selected to inspect their association with disease resistance/susceptibility to Listonella anguillarum. Three genotypes G/G, G/A and A/A, were revealed at locus +7679, and their frequencies were 89.7%, 7.7% and 2.6% in the resistant stock, while 63.2%, 34.2% and 2.6% in the susceptible stock, respectively. The frequency of genotypes G/G and G/A were significantly different (P < 0.05) between the two stocks. The pathogen-associated molecular patterns (PAMP) binding activity of two recombinant proteins, rCfLGBP (G) with G variant at locus +7679 and rCfLGBP (S) with A variant at locus +7679, were elucidated by ELISA assay. The binding affinities of both LPS and β-glucan binding affinity were varied in a dose-dependent manner, where the binding affinity of rCfLGBP (G) was significantly higher than that of rCfLGBP (S) (P < 0.05). The results collectively suggested that the polymorphism of +7679 G/G in CfLGBP possibly enhances the binding activity of LPS and β-glucan, and was associated to disease resistance of scallop against L. anguillarum, which could be a potential marker applied in future selection of scallop with enhanced resistance to L. anguillarum.

Excipients differentially influence the conformational stability and pretransition dynamics of two IgG1 monoclonal antibodies

Since immunoglobulins are conformationally dynamic molecules in solution, we studied the effect of stabilizing and destabilizing excipients on the conformational stability and dynamics of two IgG1 monoclonal antibodies (mAbs; mAb-A and mAb-B) using a variety of biophysical approaches. Even though the two mAbs are of the same IgG1 subtype, the unfolding patterns, aggregation behavior, and pretransition dynamics of these two antibodies were strikingly different in response to external perturbations such as pH, temperature, and presence of excipients. Sucrose and arginine were identified as stabilizers and destabilizers, respectively, on the basis of their influence on conformational stability for both the IgG1 mAbs. The two excipients, however, had distinct effective concentrations and different effects on the conformational stability and pretransition dynamics of the two mAbs as measured by a combination of differential scanning calorimetry, high-resolution ultrasonic spectroscopy, and red-edge excitation shift fluorescence studies. Stabilizing concentrations of sucrose were found to decrease the internal motions of mAb-B, whereas arginine marginally increased its adiabatic compressibility in the pretransition region. Both sucrose and arginine did not influence the pretransition dynamics of mAb-A. The potential reasons for such differences in excipient effects between two IgG1 mAbs are discussed.

Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins

BACKGROUND

Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question "What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?"

RESULTS

A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex.Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in literature, this is, to our knowledge, the first study indicating the prevalence of allostery induced by protein effectors.

CONCLUSIONS

The enrichment of allosteric sites in signalling proteins, whose mutations commonly lead to diseases such as cancer, provides support for the usage of allosteric modulators in combating these diseases.

MAP(2.0)3D: a sequence/structure based server for protein engineering

The Mutagenesis Assistant Program (MAP) is a web-based tool to provide statistical analyses of the mutational biases of directed evolution experiments on amino acid substitution patterns. MAP analysis assists protein engineers in the benchmarking of random mutagenesis methods that generate single nucleotide mutations in a codon. Herein, we describe a completely renewed and improved version of the MAP server, the MAP(2.0)3D server, which correlates the generated amino acid substitution patterns to the structural information of the target protein. This correlation aids in the selection of a more suitable random mutagenesis method with specific biases on amino acid substitution patterns. In particular, the new server represents MAP indicators on secondary and tertiary structure and correlates them to specific structural components such as hydrogen bonds, hydrophobic contacts, salt bridges, solvent accessibility, and crystallographic B-factors. Three model proteins (D-amino oxidase, phytase, and N-acetylneuraminic acid aldolase) are used to illustrate the novel capability of the server. MAP(2.0)3D server is available publicly at http://map.jacobs-university.de/map3d.html.

Is a malleable protein necessarily highly dynamic? The hydrophobic core of the nuclear coactivator binding domain is well ordered

The nuclear coactivator binding domain of CREB binding protein folds into remarkably different structures in complex with different ligands. To understand the mechanism of the structural adaptability in the nuclear coactivator binding domain (NCBD), we have compared the dynamics of the hydrophobic core of NCBD in the ligand-free state and in a well-folded complex with the ligand activator for thyroid hormone and retinoid receptors using multiple NMR methods including methyl chemical shifts, coupling constants, and methyl order parameters. From all NMR measures, the aliphatic side chains in the hydrophobic core are slightly more dynamic in the free protein than in the complex, but have mobility comparable to the hydrophobic cores of average folded proteins. Urea titration monitored by NMR reveals that all parts of the protein, including the side-chain packing in the hydrophobic core, denatures in a single cooperative process. The molten globule characteristics of NCBD are thus restricted to a slowly fluctuating tertiary structure. Consequently, the conformational plasticity of the protein is most likely related to its low overall stability rather than an intrinsically flexible protein structure. The well-defined structure supports a model of molecular recognition dominated by conformational selection, whereas only minor structural adjustments are necessary after the association.

Dynamics, flexibility and ligand-induced conformational changes in biological macromolecules: a computational approach

Biomolecules possess important dynamical properties that enable them to adapt and alternate their conformation as a response to environmental stimuli. Recent advancements in computational resources and methodology allow a higher capability to mimic in vitro conditions and open up the possibility of studying large systems over longer timescales. Here, we describe commonly used computational approaches for studying the dynamic properties of proteins. We review a selected set of simulation studies on ligand-induced changes in the chaperonin GroEL-GroES, a molecular folding machine, maltose-binding protein, a prototypical member of the periplasmic binding proteins, and the bacterial ribosomal A-site, focusing on aminoglycoside antibiotic recognition. We also discuss a recent quantitative reconstruction of the binding process of benzamidine and trypsin. These studies contribute to the understanding and further development of the medicinal regulation of large biomolecular systems.

Structural features that predict real-value fluctuations of globular proteins

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins.

Exploring c-Met kinase flexibility by sampling and clustering its conformational space

It is now widely recognized that the flexibility of both partners has to be considered in molecular docking studies. However, the question how to handle the best the huge computational complexity of exploring the protein binding site landscape is still a matter of debate. Here we investigate the flexibility of c-Met kinase as a test case for comparing several simulation methods. The c-Met kinase catalytic site is an interesting target for anticancer drug design. In particular, it harbors an unusual plasticity compared with other kinases ATP binding sites. Exploiting this feature may eventually lead to the discovery of new anticancer agents with exquisite specificity. We present in this article an extensive investigation of c-Met kinase conformational space using large-scale computational simulations in order to extend the knowledge already gathered from available X-ray structures. In the process, we compare the relevance of different strategies for modeling and injecting receptor flexibility information into early stage in silico structure-based drug discovery pipeline. The results presented here are currently being exploited in on-going virtual screening investigations on c-Met.

Influence of drying on the secondary structure of intrinsically disordered and globular proteins

Circular dichroism (CD) spectroscopy of five Arabidopsis late embryogenesis abundant (LEA) proteins constituting the plant specific families LEA_5 and LEA_6 showed that they are intrinsically disordered in solution and partially fold during drying. Structural predictions were comparable to these results for hydrated LEA_6, but not for LEA_5 proteins. FTIR spectroscopy showed that verbascose, but not sucrose, strongly affected the structure of the dry proteins. The four investigated globular proteins were only mildly affected by drying in the absence, but strongly in the presence of sugars. These data highlight the larger structural flexibility of disordered compared to globular proteins and the impact of sugars on the structure of both disordered and globular proteins during drying.

Mimicry of the regulatory role of urokinase in lamellipodia formation by introduction of a non-native interdomain disulfide bond in its receptor

The high-affinity interaction between the urokinase-type plasminogen activator (uPA) and its glycolipid-anchored receptor (uPAR) plays a regulatory role for both extravascular fibrinolysis and uPAR-mediated adhesion and migration on vitronectin-coated surfaces. We have recently proposed that the adhesive function of uPAR is allosterically regulated via a "tightening" of its three-domain structure elicited by uPA binding. To challenge this proposition, we redesigned the uPAR structure to limit its inherent conformational flexibility by covalently tethering domains DI and DIII via a non-natural interdomain disulfide bond (uPAR(H47C-N259C)). The corresponding soluble receptor has 1) a smaller hydrodynamic volume, 2) a higher content of secondary structure, and 3) unaltered binding kinetics towards uPA. Most importantly, the purified uPAR(H47C-N259C) also displays a gain in affinity for the somatomedin B domain of vitronectin compared with uPAR(wt), thus recapitulating the improved affinity that accompanies uPA-uPAR(wt) complex formation. This functional mimicry is, intriguingly, operational also in a cellular setting, where it controls lamellipodia formation in uPAR-transfected HEK293 cells adhering to vitronectin. In this respect, the engineered constraint in uPAR(H47C-N259C) thus bypasses the regulatory role of uPA binding, resulting in a constitutively active uPAR. In conclusion, our data argue for a biological relevance of the interdomain dynamics of the glycolipid-anchored uPAR on the cell surface.