The relation of the X-ray B-factor to protein dynamics: insights from recent dynamic solid-state NMR data

In addressing the potential use of B-factors derived from X-ray scattering data of proteins for the understanding the (functional) dynamics of proteins, we present a comparison of B-factors of five different proteins (SH3 domain, Crh, GB1, ubiquitin and thioredoxin) with data from recent solid-state nuclear magnetic resonance experiments reflecting true (rotational) dynamics on well-defined timescales. Apart from trivial correlations involving mobile loop regions and chain termini, we find no significant correlation of B-factors with the dynamic data on any of the investigated timescales, concluding that there is no unique and general correlation of B-factors with the internal reorientational dynamics of proteins.     

A-site residues move independently from P-site residues in all-atom molecular dynamics simulations of the 70S bacterial ribosome

The ribosome is a large macromolecular machine, and correlated motion between residues is necessary for coordinating function across multiple protein and RNA chains. We ran two all-atom, explicit solvent molecular dynamics simulations of the bacterial ribosome and calculated correlated motion between residue pairs by using mutual information. Because of the short timescales of our simulation (ns), we expect that dynamics are largely local fluctuations around the crystal structure. We hypothesize that residues that show coupled dynamics are functionally related, even on longer timescales. We validate our model by showing that crystallographic B-factors correlate well with the entropy calculated as part of our mutual information calculations. We reveal that A-site residues move relatively independently from P-site residues, effectively insulating A-site functions from P-site functions during translation.     

Critical evaluation of simple network models of protein dynamics and their comparison with crystallographic B-factors

In recent years, elastic network models (ENM) have been widely used to describe low-frequency collective motions in proteins. These models are often validated and calibrated by fitting mean-square atomic displacements estimated from x-ray crystallography (B-factors). We show that a proper calibration procedure must account for the rigid-body motion and constraints imposed by the crystalline environment on the protein. These fundamental aspects of protein dynamics in crystals are often ignored in currently used ENMs, leading to potentially erroneous network parameters. Here we develop an ENM that properly takes the rigid-body motion and crystalline constraints into account. Its application to the crystallographic B-factors reveals that they are dominated by rigid-body motion and thus are poorly suited for the calibration of models for internal protein dynamics. Furthermore, the translation libration screw (TLS) model that treats proteins as rigid bodies is considerably more successful in interpreting the experimental B-factors than ENMs. This conclusion is reached on the basis of a comparative study of various models of protein dynamics. To evaluate their performance, we used a data set of 330 protein structures that combined the sets previously used in the literature to test and validate different models. We further propose an extended TLS model that treats the bulk of the protein as a rigid body while allowing for flexibility of chain ends. This model outperforms other simple models of protein dynamics in interpreting the crystallographic B-factors.     

Deriving correlated motions in proteins from X-ray structure refinement by using TLS parameters

Dynamic information in proteins may provide valuable information for understanding allosteric regulation of protein complexes or long-range effects of the mutations on enzyme activity. Experimental data such as X-ray B-factors or NMR order parameters provide a convenient estimate of atomic fluctuations (or atomic auto-correlated motions) in proteins. However, it is not as straightforward to obtain atomic cross-correlated motions in proteins — one usually resorts to more sophisticated computational methods such as Molecular Dynamics, normal mode analysis or atomic network models. In this report, we show that atomic cross-correlations can be reliably obtained directly from protein structure using X-ray refinement data. We have derived an analytic form of atomic correlated motions in terms of the original TLS parameters used to refine the B-factors of X-ray structures. The correlated maps computed using this equation are well correlated with those of the method based on a mechanical model (the correlation coefficient is 0.75) for a non-homologous dataset comprising 100 structures. We have developed an approach to compute atomic cross-correlations directly from X-ray protein structure. Being in analytic form, it is fast and provides a feasible way to compute correlated motions in proteins in a high throughput way. In addition, avoiding sophisticated computational operations; it provides a quick, reliable way, especially for non-computational biologists, to obtain dynamics information directly from protein structure relevant to its function.     

Structural compliance: A new metric for protein flexibility

Proteins are the active players in performing essential molecular activities throughout biology, and their dynamics has been broadly demonstrated to relate to their mechanisms. The intrinsic fluctuations have often been used to represent their dynamics and then compared to the experimental B-factors. However, proteins do not move in a vacuum and their motions are modulated by solvent that can impose forces on the structure. In this paper, we introduce a new structural concept, which has been called the structural compliance, for the evaluation of the global and local deformability of the protein structure in response to intramolecular and solvent forces. Based on the application of pairwise pulling forces to a protein elastic network, this structural quantity has been computed and sometimes is even found to yield an improved correlation with the experimental B-factors, meaning that it may serve as a better metric for protein flexibility. The inverse of structural compliance, namely the structural stiffness, has also been defined, which shows a clear anticorrelation with the experimental data. Although the present applications are made to proteins, this approach can also be applied to other biomolecular structures such as RNA. This present study considers only elastic network models, but the approach could be applied further to conventional atomic molecular dynamics. Compliance is found to have a slightly better agreement with the experimental B-factors, perhaps reflecting its bias toward the effects of local perturbations, in contrast to mean square fluctuations. The code for calculating protein compliance and stiffness is freely accessible at https://jerniganlab.github.io/Software/PACKMAN/Tutorials/compliance .     

Optimization and evaluation of a coarse-grained model of protein motion using x-ray crystal data

Simple coarse-grained models, such as the Gaussian network model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution (相似文献   

vGNM: a better model for understanding the dynamics of proteins in crystals

The dynamics of proteins are important for understanding their functions. In recent years, the simple coarse-grained Gaussian Network Model (GNM) has been fairly successful in interpreting crystallographic B-factors. However, the model clearly ignores the contribution of the rigid body motions and the effect of crystal packing. The model cannot explain the fact that the same protein may have significantly different B-factors under different crystal packing conditions. In this work, we propose a new GNM, called vGNM, which takes into account both the contribution of the rigid body motions and the effect of crystal packing, by allowing the amplitude of the internal modes to be variables. It hypothesizes that the effect of crystal packing should cause some modes to be amplified and others to become less important. In doing so, vGNM is able to resolve the apparent discrepancy in experimental B-factors among structures of the same protein but with different crystal packing conditions, which GNM cannot explain. With a small number of parameters, vGNM is able to reproduce experimental B-factors for a large set of proteins with significantly better correlations (having a mean value of 0.81 as compared to 0.59 by GNM). The results of applying vGNM also show that the rigid body motions account for nearly 60% of the total fluctuations, in good agreement with previous findings.     

Dynamics of the Hck-SH3 domain: comparison of experiment with multiple molecular dynamics simulations

Molecular dynamics calculations provide a method by which the dynamic properties of molecules can be explored over timescales and at a level of detail that cannot be obtained experimentally from NMR or X-ray analyses. Recent work (Philippopoulos M, Mandel AM, Palmer AG III, Lim C, 1997, Proteins 28:481-493) has indicated that the accuracy of these simulations is high, as measured by the correspondence of parameters extracted from these calculations to those determined through experimental means. Here, we investigate the dynamic behavior of the Src homology 3 (SH3) domain of hematopoietic cell kinase (Hck) via 5N backbone relaxation NMR studies and a set of four independent 4 ns solvated molecular dynamics calculations. We also find that molecular dynamics simulations accurately reproduce fast motion dynamics as estimated from generalized order parameter (S2) analysis for regions of the protein that have experimentally well-defined coordinates (i.e., stable secondary structural elements). However, for regions where the coordinates are not well defined, as indicated by high local root-mean-square deviations among NMR-determined structural family members or high B-factors/low electron density in X-ray crystallography determined structures, the parameters calculated from a short to moderate length (less than 5-10 ns) molecular dynamics trajectory are dependent on the particular coordinates chosen as a starting point for the simulation.     

Conformational substates in enzyme mechanism: the 120 K structure of alpha-lytic protease at 1.5 A resolution.

Insight into the dynamic properties of alpha-lytic protease (alpha LP) has been obtained through the use of low-temperature X-ray crystallography and multiple-conformation refinement. Previous studies of alpha LP have shown that the residues around the active site are able to move significantly to accommodate substrates of different sizes. Here we show a link between the ability to accommodate ligands and the dynamics of the binding pocket. Although the structure of alpha LP at 120 K has B-factors with a uniformly low value of 4.8 A2 for the main chain, four regions stand out as having significantly higher B-factors. Because thermal motion should be suppressed at cryogenic temperatures, the high B-factors are interpreted as the result of trapped conformational substates. The active site residues that are perturbed during accommodation of different substrates are precisely those showing conformational substates, implying that substrate binding selects a subset of conformations from the ensemble of accessible states. To better characterize the precise nature of these substates, a protein model consisting of 16 structures has been refined and evaluated. The model reveals a number of features that could not be well-described by conventional B-factors: for example, 40% of the main-chain residue conformations are distributed asymmetrically or in discrete clusters. Furthermore, these data demonstrate an unexpected correlation between motions on either side of the binding pocket that we suggest is a consequence of "dynamic close packing." These results provide strong evidence for the role of protein dynamics in substrate binding and are consistent with the results of dynamic studies of ligand binding in myoglobin and ribonuclease A.     

Predicting the order in which contacts are broken during single molecule protein stretching experiments

We combine two methods to enable the prediction of the order in which contacts are broken under external stretching forces in single molecule experiments. These two methods are Gō-like models and elastic network models. The Gō-like models have shown remarkable success in representing many aspects of protein behavior, including the reproduction of experimental data obtained from atomic force microscopy. The simple elastic network models are often used successfully to predict the fluctuations of residues around their mean positions, comparing favorably with the experimentally measured crystallographic B-factors. The behavior of biomolecules under external forces has been demonstrated to depend principally on their elastic properties and the overall shape of their structure. We have studied in detail the muscle protein titin and green fluorescent protein and tested for ten other proteins. First, we stretch the proteins computationally by performing stochastic dynamics simulations with the Gō-like model. We obtain the force-displacement curves and unfolding scenarios of possible mechanical unfolding. We then use the elastic network model to calculate temperature factors (B-factors) and compare the slowest modes of motion for the stretched proteins and compare them with the predicted order of breaking contacts between residues in the Gō-like model. Our results show that a simple Gaussian network model is able to predict contacts that break in the next time stage of stretching. Additionally, we have found that the contact disruption is strictly correlated with the highest force exerted by the backbone on these residues. Our prediction of bond-breaking agrees well with the unfolding scenario obtained with the Gō-like model. We anticipate that this method will be a useful new tool for interpreting stretching experiments.     

Conformational sampling and dynamics of membrane proteins from 10-nanosecond computer simulations

In the current report, we provide a quantitative analysis of the convergence of the sampling of conformational space accomplished in molecular dynamics simulations of membrane proteins of duration in the order of 10 nanoseconds. A set of proteins of diverse size and topology is considered, ranging from helical pores such as gramicidin and small beta-barrels such as OmpT, to larger and more complex structures such as rhodopsin and FepA. Principal component analysis of the C(alpha)-atom trajectories was employed to assess the convergence of the conformational sampling in both the transmembrane domains and the whole proteins, while the time-dependence of the average structure was analyzed to obtain single-domain information. The membrane-embedded regions, particularly those of small or structurally simple proteins, were found to achieve reasonable convergence. By contrast, extra-membranous domains lacking secondary structure are often markedly under-sampled, exhibiting a continuous structural drift. This drift results in a significant imprecision in the calculated B-factors, which detracts from any quantitative comparison to experimental data. In view of such limitations, we suggest that similar analyses may be valuable in simulation studies of membrane protein dynamics, in order to attach a level of confidence to any biologically relevant observations.     

Relaxation kinetics and the glassiness of native proteins: coupling of timescales

We provide evidence that the onset of functional dynamics of folded proteins with elevated temperatures is associated with the effective sampling of its energy landscape under physiological conditions. The analysis is based on data describing the relaxation phenomena governing the backbone dynamics of bovine pancreatic trypsin inhibitor derived from molecular dynamics simulations, previously reported by us. By representing the backbone dynamics of the folded protein by three distinct regimes, it is possible to decompose its seemingly complex dynamics, described by a stretch exponential decay of the backbone motions. Of these three regimes, one is associated with the slow timescales due to the activity along the envelope of the energy surface defining the folded protein. Another, with fast timescales, is due to the activity along the pockets decorating the folded-state envelope. The intermediate regime emerges at temperatures where jumps between the pockets become possible. It is at the temperature window where motions corresponding to all three timescales become operative that the protein becomes active.     

Dynamics of the trimeric AcrB transporter protein inferred from a B-factor analysis of the crystal structure

The Escherichia coli AcrB multidrug transporter recognizes a wide range of toxic chemicals and actively extrudes them from cells. The molecular basis of multidrug transport in AcrB remains unknown. Herein, we describe normal mode analyses to study important regions for drug recognition and extrusion in this transporter. Based on the X-ray structure of AcrB, an elastic network model has been able to correct errors arising from crystal imperfection in the experimental B-factors. The results allow us to understand the functional dynamics of this membrane protein. It is expected that this technique can be applied to other membrane proteins with known structures.     

Determination of Ensemble-Average Pairwise Root Mean-Square Deviation from Experimental B-Factors

Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species, <RMSD²>^1/2, is directly related to average B-factors (<B>) and <RMSF²>^1/2. We show this relationship and explore its limits of validity on a heterogeneous ensemble of structures taken from molecular dynamics simulations of villin headpiece generated using distributed-computing techniques and the Folding@Home cluster. Our results provide a basis for quantifying global structural diversity of macromolecules in crystals directly from x-ray experiments, and we show this on a large set of structures taken from the Protein Data Bank. In particular, we show that the ensemble-average pairwise backbone RMSD for a microscopic ensemble underlying a typical protein x-ray structure is ∼1.1 Å, under the assumption that the principal contribution to experimental B-factors is conformational variability.     

A Direct Coupling between Global and Internal Motions in a Single Domain Protein? MD Investigation of Extreme Scenarios

Proteins are not rigid molecules, but exhibit internal motions on timescales ranging from femto- to milliseconds and beyond. In solution, proteins also experience global translational and rotational motions, sometimes on timescales comparable to those of the internal fluctuations. The possibility that internal and global motions may be directly coupled has intriguing implications, given that enzymes and cell signaling proteins typically associate with binding partners and cellular scaffolds. Such processes alter their global motion and may affect protein function. Here, we present molecular dynamics simulations of extreme case scenarios to examine whether a possible relationship exists. In our model protein, a ubiquitin-like RhoGTPase binding domain of plexin-B1, we removed either internal or global motions. Comparisons with unrestrained simulations show that internal and global motions are not appreciably coupled in this single-domain protein. This lack of coupling is consistent with the observation that the dynamics of water around the protein, which is thought to permit, if not stimulate, internal dynamics, is also largely independent of global motion. We discuss implications of these results for the structure and function of proteins.     

Improved amino acid flexibility parameters

Protein molecules exhibit varying degrees of flexibility throughout their three-dimensional structures, with some segments showing little mobility while others may be so disordered as to be unresolvable by techniques such as X-ray crystallography. Atomic displacement parameters, or B-factors, from X-ray crystallographic studies give an experimentally determined indication of the degree of mobility in a protein structure. To provide better estimators of amino acid flexibility, we have examined B-factors from a large set of high-resolution crystal structures. Because of the differences among structures, it is necessary to normalize the B-factors. However, many proteins have segments of unusually high mobility, which must be accounted for before normalization can be performed. Accordingly, a median-based method from quality control studies was used to identify outliers. After removal of outliers from, and normalization of, each protein chain, the B-factors were collected for each amino acid in the set. It was found that the distribution of normalized B-factors followed a Gumbel, or extreme value distribution, and the location parameter, or mode, of this distribution was used as an estimator of flexibility for the amino acid. These new parameters have a higher correlation with experimentally determined B-factors than parameters from earlier methods.     

Recognition of different DNA sequences by a DNA-binding protein alters protein dynamics differentially

λ-Repressor-operator sites interaction, particularly O(R)1 and O(R)2, is a key component of the λ-genetic switch. FRET from the dansyl bound to the C-terminal domain of the protein, to the intercalated EtBr in the operator DNA indicates that the structure of the protein is more compact in the O(R)2 complex than in the O(R)1 complex. Fluorescence anisotropy reveals enhanced flexibility of the C-terminal domain of the repressor at fast timescales after complex formation with O(R)1. In contrast, O(R)2 bound repressor shows no significant enhancement of protein dynamics at these timescales. These differences are shown to be important for correct protein-protein interactions. Altered protein dynamics upon specific DNA sequence recognition may play important roles in assembly of regulatory proteins at the correct positions.     

Evolutionary Conservation of Protein Backbone Flexibility

Internal protein dynamics is essential for biological function. During evolution, protein divergence is functionally constrained: properties more relevant for function vary more slowly than less important properties. Thus, if protein dynamics is relevant for function, it should be evolutionary conserved. In contrast with the well-studied evolution of protein structure, the evolutionary divergence of protein dynamics has not been addressed systematically before, apart from a few case studies. X-Ray diffraction analysis gives information not only on protein structure but also on B-factors, which characterize the flexibility that results from protein dynamics. Here we study the evolutionary divergence of protein backbone dynamics by comparing the C_α flexibility (B-factor) profiles for a large dataset of homologous proteins classified into families and superfamilies. We show that C_α flexibility profiles diverge slowly, so that they are conserved at family and superfamily levels, even for pairs of proteins with nonsignificant sequence similarity. We also analyze and discuss the correlations among the divergences of flexibility, sequence, and structure. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: Dr. David Pollock]     

Concordance of residual dipolar couplings, backbone order parameters and crystallographic B-factors for a small alpha/beta protein: a unified picture of high probability, fast atomic motions in proteins

Using ensemble refinement of the third immunoglobulin binding domain (GB3) of streptococcal protein G (a small alpha/beta protein of 56 residues), we demonstrate that backbone (N-H, N-C', Calpha-Halpha, Calpha-C') residual dipolar coupling data in five independent alignment media, generalized order parameters from 15N relaxation data, and B-factors from a high-resolution (1.1A), room temperature crystal structure are entirely consistent with one another within experimental error. The optimal ensemble size representation is between four and eight, as assessed by complete cross-validation of the residual dipolar couplings. Thus, in the case of GB3, all three observables reflect the same low-amplitude anisotropic motions arising from fluctuations in backbone phi/psi torsion angles in the picosecond to nanosecond regime in both solution and crystalline environments, yielding a unified picture of fast, high-probability atomic motions in proteins. An understanding of these motions is crucial for understanding the impact of protein dynamics on protein function, since they provide part of the driving force for triggered conformational changes that occur, for example, upon ligand binding, signal transduction and enzyme catalysis.     

Why protein R-factors are so large: a self-consistent analysis

The R-factor and R-free are commonly used to measure the quality of protein models obtained in X-ray crystallography. Well-refined protein structures usually have R-factors in the range of 20-25%, whereas intrinsic errors in the experimental data are usually around 5%. We use molecular dynamics simulations to perform a self-consistent analysis by which we determine the major factors contributing to large values of protein R-factors. The analysis shows that significant R-factor values can arise from the use of isotropic B-factors to model anisotropic protein motions and from coordinate errors. Even in the absence of coordinate errors, the use of isotropic B-factors can cause the R-factors to be around 10%; for coordinate errors smaller than 0.2 A, the two errors types make similar contributions. The inaccuracy of the energy function used and multistate protein dynamics are unlikely to make significant contributions to the large R-factors.