FREALIGN: high-resolution refinement of single particle structures

The refinement of three-dimensional reconstructions and correction for the contrast transfer function of the microscope are important steps in the determination of macromolecular structures by single particle electron microscopy. The algorithms implemented in the computer program FREALIGN are optimized to perform these tasks efficiently. A general overview and details on how to use FREALIGN are provided. The program is free and available for download on the author's web page.     

Molecular modeling of averaged rigor crossbridges from tomograms of insect flight muscle

Electron tomography, correspondence analysis, molecular model building, and real-space refinement provide detailed 3-D structures for in situ myosin crossbridges in the nucleotide-free state (rigor), thought to represent the end of the power stroke. Unaveraged tomograms from a 25-nm longitudinal section of insect flight muscle preserved native structural variation. Recurring crossbridge motifs that repeat every 38.7 nm along the actin filament were extracted from the tomogram and classified by correspondence analysis into 25 class averages, which improved the signal to noise ratio. Models based on the atomic structures of actin and of myosin subfragment 1 were rebuilt to fit 11 class averages. A real-space refinement procedure was applied to quantitatively fit the reconstructions and to minimize steric clashes between domains introduced during the fitting. These combined procedures show that no single myosin head structure can fit all the in situ crossbridges. The validity of the approach is supported by agreement of these atomic models with fluorescent probe data from vertebrate muscle as well as with data from regulatory light chain crosslinking between heads of smooth muscle heavy meromyosin when bound to actin.     

A data mining approach for analyzing density maps representing macromolecular structures

Results of electron microscopy-based three-dimensional reconstructions of macromolecules or their complexes are usually stored as density maps. Each point ("voxel") in the map represents a density value and one approach for studying details of the map is to display an isosurface enclosing areas of interest. We have taken a data mining approach not only focusing on the areas of immediate interest but determining all possible separate entities ("blobs") from a density map. After the entire density map is analyzed with our mining program BLOBBER, properties of all detected blobs can be browsed and sets of blobs can be visualized using our VIZBLOB program. Since BLOBBER analyzes density maps using only density information and relates it to spatial relationships, BLOBBER can be used to analyze symmetrical or asymmetrical density maps from any source. To test our program we have analyzed published bacteriophage PRD1 reconstructions. We identified various structural details ranging from individual proteins to major complexes such as the whole capsid shell and more elaborate details of possible connections between membrane interfaces. This approach can also be a useful preprocessing tool for visualizing reconstructions.     

Electron tomography reveals diverse conformations of integrin alphaIIbbeta3 in the active state

We used electron tomography to determine the three-dimensional (3D) structure of integrin alphaIIbbeta3 in the active state. We found that we obtained better density maps when we reconstructed a 3D volume for each individual particle in the tilt series rather than to extract the particle-containing subvolumes from a 3D reconstruction of the entire specimen area. The 3D tomographic reconstructions of 100 particles revealed that activated alphaIIbbeta3 adopts many different conformations. An average of all the individual 3D reconstructions nicely accommodated the crystal structure of the alphaVbeta3 headpiece, confirming the locations assigned to the alpha- and beta-subunit in the density map. The most striking finding of our study is the structural flexibility of the lower leg of the beta-subunit as opposed to the conformational stability of the leg of the alpha-subunit. The good fit of the atomic structure of the betaI domain and the hybrid domain in the active state showed that the hybrid domain swings out, and most particles used for tomography are in the active state. Multivariate statistical analysis and classification applied to the set of 3D reconstructions revealed that more than 90% reconstructions are grouped into the classes that show the active state. Our results demonstrate that electron tomography can be used to classify complexes with a flexible structure such as integrins.     

A rapid method of protein structure alignment

A reduction in the time required to compare two protein structures has been achieved for a previously developed structure alignment method, by reducing the number of residue pair comparisons which must be performed between the two structures. Subsets of residue pairs are selected by an iterative procedure. Initially, selection is based on similarities in solvent accessible surface areas or torsional angles or a combination of both properties, giving subsets containing approximately 2% of the total number of residue pairs. Using these subsets, a rough comparison of the two structures is generated by the structural alignment program. The information returned from this can be used to identify more accurately topologically equivalent residues in the two proteins, thus enabling a new and much smaller subset (less than 0.2% of the total number of residue pairs) to be selected. The process of iterative refinement of the residue pair subsets is repeated once more, when in 95% of the structure comparisons tested, the correct alignment of the proteins was obtained. Times required to compare the structures using the refined subsets are insignificant compared to the initial comparison, so that considerable increases in speed are possible. The method was tested on two groups of proteins, a set of remotely related alpha/beta nucleotide proteins and the variable and constant domains of the immunoglobulins. Increases in speed ranging from 50-fold to greater than 150-fold were obtained depending on the degree of similarity of the two structures. In some comparisons the alignment was improved due to the reduction in noise obtained by comparing mainly equivalent residues.     

Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion

Electron tomography is a powerful technique capable of giving unique insights into the three-dimensional structural organization of pleomorphic biological objects. However, visualization and interpretation of the resulting volumetric data are hampered by an extremely low signal-to-noise ratio, especially when ice-embedded biological specimens are investigated. Usually, isosurface representation or volume rendering of such data is hindered without any further signal enhancement. We propose a novel technique for noise reduction based on nonlinear anisotropic diffusion. The approach combines efficient noise reduction with excellent signal preservation and is clearly superior to conventional methods (e.g., low-pass and median filtering) and invariant wavelet transform filtering. The gain in the signal-to-noise ratio is verified and demonstrated by means of Fourier shell correlation. Improved visualization performance after processing the 3D images is demonstrated with two examples, tomographic reconstructions of chromatin and of a mitochondrion. Parameter settings and discretization stencils are presented in detail.     

Finding rigid bodies in protein structures: Application to flexible fitting into cryoEM maps

We present RIBFIND, a method for detecting flexibility in protein structures via the clustering of secondary structural elements (SSEs) into rigid bodies. To test the usefulness of the method in refining atomic structures within cryoEM density we incorporated it into our flexible fitting protocol (Flex-EM). Our benchmark includes 13 pairs of protein structures in two conformations each, one of which is represented by a corresponding cryoEM map. Refining the structures in simulated and experimental maps at the 5–15 Å resolution range using rigid bodies identified by RIBFIND shows a significant improvement over using individual SSEs as rigid bodies. For the 15 Å resolution simulated maps, using RIBFIND-based rigid bodies improves the initial fits by 40.64% on average, as compared to 26.52% when using individual SSEs. Furthermore, for some test cases we show that at the sub-nanometer resolution range the fits can be further improved by applying a two-stage refinement protocol (using RIBFIND-based refinement followed by an SSE-based refinement). The method is stand-alone and could serve as a general interactive tool for guiding flexible fitting into EM maps.     

Determining protein topology from skeletons of secondary structures

We report a novel computational procedure for determining protein native topology, or fold, by defining loop connectivity based on skeletons of secondary structures that can usually be obtained from low to intermediate-resolution density maps. The procedure primarily involves a knowledge-based geometry filter followed by an energetics-based evaluation. It was tested on a large set of skeletons covering a wide range of protein architecture, including one modeled from an experimentally determined 7.6A cryo-electron microscopy (cryo-EM) density map. The results showed that the new procedure could effectively deduce protein folds without high-resolution structural data, a feature that could also be used to recognize native fold in structure prediction and to interpret data in fields like structure genomics. Most importantly, in the energetics-based evaluation, it was revealed that, despite the inevitable errors in the artificially constructed structures and limited accuracy of knowledge-based potential functions, the average energy of an ensemble of structures with slightly different configurations around the native skeleton is a much more robust parameter for marking native topology than the energy of individual structures in the ensemble. This result implies that, among all the possible topology candidates for a given skeleton, evolution has selected the native topology as the one that can accommodate the largest structural variations, not the one rigidly trapped in a deep, but narrow, conformational energy well.     

M-TASSER: an algorithm for protein quaternary structure prediction

In a cell, it has been estimated that each protein on average interacts with roughly 10 others, resulting in tens of thousands of proteins known or suspected to have interaction partners; of these, only a tiny fraction have solved protein structures. To partially address this problem, we have developed M-TASSER, a hierarchical method to predict protein quaternary structure from sequence that involves template identification by multimeric threading, followed by multimer model assembly and refinement. The final models are selected by structure clustering. M-TASSER has been tested on a benchmark set comprising 241 dimers having templates with weak sequence similarity and 246 without multimeric templates in the dimer library. Of the total of 207 targets predicted to interact as dimers, 165 (80%) were correctly assigned as interacting with a true positive rate of 68% and a false positive rate of 17%. The initial best template structures have an average root mean-square deviation to native of 5.3, 6.7, and 7.4 Å for the monomer, interface, and dimer structures. The final model shows on average a root mean-square deviation improvement of 1.3, 1.3, and 1.5 Å over the initial template structure for the monomer, interface, and dimer structures, with refinement evident for 87% of the cases. Thus, we have developed a promising approach to predict full-length quaternary structure for proteins that have weak sequence similarity to proteins of solved quaternary structure.     

Refinement of the influenza virus hemagglutinin by simulated annealing

We have applied the method of simulated annealing to the refinement of the 3 A resolution crystal structure of the influenza virus hemagglutinin glycoprotein, using the program X-PLOR. Two different methods were introduced into X-PLOR to treat the non-crystallographic symmetry present in this and in other crystal structures. In the first, only the unique protomer atoms are refined; by application of the non-crystallographic symmetry operators to the protomer atoms, the X-ray structure factor derivatives are effectively averaged, and a non-bonded energy term models the interactions of the protomer with its neighbors in the oligomer without explicit refinement of the other protomers in the crystallographic asymmetric unit. In the second method, the entire asymmetric unit is refined, but an effective energy term is added to the empirical energy that restrains symmetry-related atomic positions to their average values after least-squares superposition. Several other modifications and additions were made to previously published X-PLOR protocols, including weighting of the X-ray terms, maintenance of the temperature of the molecular dynamics simulation, treatment of charged groups, changes in the values of certain empirical energy parameters, and the use of N-linked carbohydrate empirical energy parameters. The hemagglutinin refinement proceeded in several stages. An initial round of simulated annealing of the monomer was followed by rigid-body refinement of the 3-fold non-crystallographic symmetry axis position and a second round of monomer refinement. A third round was performed on the trimer using non-crystallographic symmetry restraints in all regions except those in lattice contacts showing obvious derivations from 3-fold symmetry. The refinement was completed with several rounds of conventional positional and isotropic temperature factor refinement needed to correct bad model geometry introduced by high-temperature molecular dynamics in regions of weak electron density. This structure was then used as the basis for refinement of three crystallographically isomorphous hemagglutinin structures, including complexes with the influenza virus receptor, sialic acid. Model geometry comparable to well-refined high-resolution structures was obtained with relatively little manual intervention, demonstrating the ability of simulated annealing refinement to produce highly idealized structures at moderate resolution.     

Automatic CTF correction for single particles based upon multivariate statistical analysis of individual power spectra

Three-dimensional electron cryomicroscopy of randomly oriented single particles is a method that is suitable for the determination of three-dimensional structures of macromolecular complexes at molecular resolution. However, the electron-microscopical projection images are modulated by a contrast transfer function (CTF) that prevents the calculation of three-dimensional reconstructions of biological complexes at high resolution from uncorrected images. We describe here an automated method for the accurate determination and correction of the CTF parameters defocus, twofold astigmatism and amplitude-contrast proportion from single-particle images. At the same time, the method allows the frequency-dependent signal decrease (B factor) and the non-convoluted background signal to be estimated. The method involves the classification of the power spectra of single-particle images into groups with similar CTF parameters; this is done by multivariate statistical analysis (MSA) and hierarchically ascending classification (HAC). Averaging over several power spectra generates class averages with enhanced signal-to-noise ratios. The correct CTF parameters can be deduced from these class averages by applying an iterative correlation procedure with theoretical CTF functions; they are then used to correct the raw images. Furthermore, the method enables the tilt axis of the sample holder to be determined and allows the elimination of individual poor-quality images that show high drift or charging effects.     

Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy

A computational procedure is described for assigning the absolute hand of the structure of a protein or assembly determined by single-particle electron microscopy. The procedure requires a pair of micrographs of the same particle field recorded at two tilt angles of a single tilt-axis specimen holder together with the three-dimensional map whose hand is being determined. For orientations determined from particles on one micrograph using the map, the agreement (average phase residual) between particle images on the second micrograph and map projections is determined for all possible choices of tilt angle and axis. Whether the agreement is better at the known tilt angle and axis of the microscope or its inverse indicates whether the map is of correct or incorrect hand. An increased discrimination of correct from incorrect hand (free hand difference), as well as accurate identification of the known values for the tilt angle and axis, can be used as targets for rapidly optimizing the search or refinement procedures used to determine particle orientations. Optimized refinement reduces the tendency for the model to match noise in a single image, thus improving the accuracy of the orientation determination and therefore the quality of the resulting map. The hand determination and refinement optimization procedure is applied to image pairs of the dihydrolipoyl acetyltransferase (E2) catalytic core of the pyruvate dehydrogenase complex from Bacillus stearothermophilus taken by low-dose electron cryomicroscopy. Structure factor amplitudes of a three-dimensional map of the E2 catalytic core obtained by averaging untilted images of 3667 icosahedral particles are compared to a scattering reference using a Guinier plot. A noise-dependent structure factor weight is derived and used in conjunction with a temperature factor (B=-1000A(2)) to restore high-resolution contrast without amplifying noise and to visualize molecular features to 8.7A resolution, according to a new objective criterion for resolution assessment proposed here.     

Unified 3-D structure and projection orientation refinement using quasi-Newton algorithm

We describe an algorithm for simultaneous refinement of a three-dimensional (3-D) density map and of the orientation parameters of two-dimensional (2-D) projections that are used to reconstruct this map. The application is in electron microscopy, where the 3-D structure of a protein has to be determined from a set of 2-D projections collected at random but initially unknown angles. The design of the algorithm is based on the assumption that initial low resolution approximation of the density map and reasonable guesses for orientation parameters are available. Thus, the algorithm is applicable in final stages of the structure refinement, when the quality of the results is of main concern. We define the objective function to be minimized in real space and solve the resulting nonlinear optimization problem using a Quasi-Newton algorithm. We calculate analytical derivatives with respect to density distribution and the finite difference approximations of derivatives with respect to orientation parameters. We demonstrate that calculation of derivatives is robust with respect to noise in the data. This is due to the fact that noise is annihilated by the back-projection operations. Our algorithm is distinguished from other orientation refinement methods (i) by the simultaneous update of the density map and orientation parameters resulting in a highly efficient computational scheme and (ii) by the high quality of the results produced by a direct minimization of the discrepancy between the 2-D data and the projected views of the reconstructed 3-D structure. We demonstrate the speed and accuracy of our method by using simulated data.     

Three-dimensional solution structure of apo-neocarzinostatin from Streptomyces carzinostaticus determined by NMR spectroscopy.

The three-dimensional solution structure of apo-neocarzinostatin has been resolved from nuclear magnetic resonance spectroscopy data. Up to 1034 constraints were used to generate an initial set of 45 structures using a distance geometry algorithm (DSPACE). From this set, ten structures were subjected to refinement by restrained energy minimization and molecular dynamics. The average atomic root mean square deviations between the final ten structures and the mean structure obtained by averaging their coordinates run from 0.085 nm for the best defined beta-sheet regions of the protein to 0.227 nm for the side chains of the most flexible loops. The solution structure of apo-neocarzinostatin is closely similar to that of the related proteins, macromomycin and actinoxanthin. It contains a seven-stranded antiparallel beta-barrel which forms, together with two external loops, a deep cavity that is the chromophore binding site. It is noteworthy that aromatic side chains extend into the binding cleft. They may be responsible for the stabilization of the holo-protein complex and for the chromophore specificity within the antitumoral family.     

A variable target intensity-restrained global optimization (VARTIGO) procedure for determining three-dimensional structures of polypeptides from NOESY data: Application to gramicidin-S

Summary A global optimization method for intensity-restrained structure refinement, based on variable target function (VTF) analysis, is illustrated using experimental data on a model peptide, gramicidin-S (GS) dissolved in DMSO. The method (referred to as VARTIGO for variable target intensity-restrained global optimization) involves minimization of a target function in which the range of NOE contacts is gradually increased in successive cycles of optimization in dihedral angle space. Several different starting conformations (including all-trans) have been tested to establish the validity of the method. Not all optimizations were successful, but these were readily identifiable from their large NOE R-factors. We also show that it is possible to simultaneously optimize the rotational correlation time along with the dihedral angles. The structural features of GS thus obtained from the successful optimizations are in excellent agreement with the available experimental data. A comparison is made with structures generated from an intensity-restrained single target function (STF) analysis. The results on GS suggest that VARTIGO refinement is capable of yielding better quality structures. Our work also underscores the need for a simultaneous analysis of different NOE R-factors in judging the quality of optimized structures. The NOESY data on GS in DMSO appear to provide evidence for the presence of two orientations for the ornithine side chain, in fast exchange. The NOESY spectra for this case were analyzed using a relaxation rate matrix which is a weighted average of the relaxation rate matrices for the individual conformations.     

Refinement of homology-based protein structures by molecular dynamics simulation techniques

The use of classical molecular dynamics simulations, performed in explicit water, for the refinement of structural models of proteins generated ab initio or based on homology has been investigated. The study involved a test set of 15 proteins that were previously used by Baker and coworkers to assess the efficiency of the ROSETTA method for ab initio protein structure prediction. For each protein, four models generated using the ROSETTA procedure were simulated for periods of between 5 and 400 nsec in explicit solvent, under identical conditions. In addition, the experimentally determined structure and the experimentally derived structure in which the side chains of all residues had been deleted and then regenerated using the WHATIF program were simulated and used as controls. A significant improvement in the deviation of the model structures from the experimentally determined structures was observed in several cases. In addition, it was found that in certain cases in which the experimental structure deviated rapidly from the initial structure in the simulations, indicating internal strain, the structures were more stable after regenerating the side-chain positions. Overall, the results indicate that molecular dynamics simulations on a tens to hundreds of nanoseconds time scale are useful for the refinement of homology or ab initio models of small to medium-size proteins.     

Refinement of the solution structure of the ribonucleotide 5'r(GCAUGC)2: combined use of nuclear magnetic resonance and restrained molecular dynamics

The solution structure of the self-complementary hexamer 5'r(GCAUGC)2 is investigated by means of nuclear magnetic resonance spectroscopy and restrained molecular dynamics. The proton resonances are assigned in a sequential manner, and a set of 110 approximate interproton distance restraints are derived from the two-dimensional nuclear Overhauser enhancement spectra. These distances are used as the basis of a structure refinement by restrained molecular dynamics in which the experimental restraints are incorporated into the total energy function of the system in the form of effective potentials. Eight restrained molecular dynamics simulations are carried out, four starting from a structure with regular A-type geometry and four from one with regular B-type geometry. The atomic root mean square (rms) difference between the initial structures is 3.2 A. In the case of all eight simulations, convergence is achieved both globally and locally to a set of very similar A-type structures with an average atomic rms difference between them of 0.8 +/- 0.2 A. Further, the atomic rms differences between the restrained dynamics structures obtained by starting out from the same initial structures but with different random number seeds for the assignment of the initial velocities are the same as those between the restrained dynamics structures starting out from the two different initial structures. These results suggest that the restrained dynamics structures represent good approximations of the solution structure. The converged structures exhibit clear sequence-dependent variation in some of the helical parameters, in particular helix twist, roll, slide, and propellor twist.(ABSTRACT TRUNCATED AT 250 WORDS)     

Protein NMR Structures Refined without NOE Data

The refinement of low-quality structures is an important challenge in protein structure prediction. Many studies have been conducted on protein structure refinement; the refinement of structures derived from NMR spectroscopy has been especially intensively studied. In this study, we generated flat-bottom distance potential instead of NOE data because NOE data have ambiguity and uncertainty. The potential was derived from distance information from given structures and prevented structural dislocation during the refinement process. A simulated annealing protocol was used to minimize the potential energy of the structure. The protocol was tested on 134 NMR structures in the Protein Data Bank (PDB) that also have X-ray structures. Among them, 50 structures were used as a training set to find the optimal “width” parameter in the flat-bottom distance potential functions. In the validation set (the other 84 structures), most of the 12 quality assessment scores of the refined structures were significantly improved (total score increased from 1.215 to 2.044). Moreover, the secondary structure similarity of the refined structure was improved over that of the original structure. Finally, we demonstrate that the combination of two energy potentials, statistical torsion angle potential (STAP) and the flat-bottom distance potential, can drive the refinement of NMR structures.     

A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction

The principal bottleneck in protein structure prediction is the refinement of models from lower accuracies to the resolution observed by experiment. We developed a novel constraints‐based refinement method that identifies a high number of accurate input constraints from initial models and rebuilds them using restrained torsion angle dynamics (rTAD). We previously created a Bayesian statistics‐based residue‐specific all‐atom probability discriminatory function (RAPDF) to discriminate native‐like models by measuring the probability of accuracy for atom type distances within a given model. Here, we exploit RAPDF to score (i.e., filter) constraints from initial predictions that may or may not be close to a native‐like state, obtain consensus of top scoring constraints amongst five initial models, and compile sets with no redundant residue pair constraints. We find that this method consistently produces a large and highly accurate set of distance constraints from which to build refinement models. We further optimize the balance between accuracy and coverage of constraints by producing multiple structure sets using different constraint distance cutoffs, and note that the cutoff governs spatially near versus distant effects in model generation. This complete procedure of deriving distance constraints for rTAD simulations improves the quality of initial predictions significantly in all cases evaluated by us. Our procedure represents a significant step in solving the protein structure prediction and refinement problem, by enabling the use of consensus constraints, RAPDF, and rTAD for protein structure modeling and refinement. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Generation of native-like protein structures from limited NMR data,modern force fields and advanced conformational sampling

Determining an accurate initial native-like protein fold is one of the most important and time-consuming steps of de novo NMR structure determination. Here we demonstrate that high-quality native-like models can be rapidly generated from initial structures obtained using limited NOE assignments, through replica exchange molecular dynamics refinement with a generalized Born implicit solvent (REX/GB). Conventional structure calculations using an initial sparse NOE set were unable to identify a unique topology for the zinc-bound C-terminal domain of E. coli chaperone Hsp33, due to a lack of unambiguous long range NOEs. An accurate overall topology was eventually obtained through laborious hand identification of long range NOEs. However we were able to obtain high-quality models with backbone RMSD values of about 2 Å with respect to the final structures, using REX/GB refinement with the original limited set of initial NOE restraints. These models could then be used to make further assignments of ambiguous NOEs and thereby speed up the structure determination process. The ability to calculate accurate starting structures from the limited unambiguous NOE set available at the beginning of a structure calculation offers the potential of a much more rapid and automated process for NMR structure determination. Jianhan Chen: Authors contributed equally to this work.Hyung-Sik Won: Authors contributed equally to this work.