Structural characterization of components of protein assemblies by comparative modeling and electron cryo-microscopy

Multiple subunit fitting into a low-resolution density map of a macromolecular complex using a gaussian mixture model

Recently, electron microscopy measurement of single particles has enabled us to reconstruct a low-resolution 3D density map of large biomolecular complexes. If structures of the complex subunits can be solved by x-ray crystallography at atomic resolution, fitting these models into the 3D density map can generate an atomic resolution model of the entire large complex. The fitting of multiple subunits, however, generally requires large computational costs; therefore, development of an efficient algorithm is required. We developed a fast fitting program, “gmfit”, which employs a Gaussian mixture model (GMM) to represent approximated shapes of the 3D density map and the atomic models. A GMM is a distribution function composed by adding together several 3D Gaussian density functions. Because our model analytically provides an integral of a product of two distribution functions, it enables us to quickly calculate the fitness of the density map and the atomic models. Using the integral, two types of potential energy function are introduced: the attraction potential energy between a 3D density map and each subunit, and the repulsion potential energy between subunits. The restraint energy for symmetry is also employed to build symmetrical origomeric complexes. To find the optimal configuration of subunits, we randomly generated initial configurations of subunit models, and performed a steepest-descent method using forces and torques of the three potential energies. Comparison between an original density map and its GMM showed that the required number of Gaussian distribution functions for a given accuracy depended on both resolution and molecular size. We then performed test fitting calculations for simulated low-resolution density maps of atomic models of homodimer, trimer, and hexamer, using different search parameters. The results indicated that our method was able to rebuild atomic models of a complex even for maps of 30 Å resolution if sufficient numbers (eight or more) of Gaussian distribution functions were employed for each subunit, and the symmetric restraints were assigned for complexes with more than three subunits. As a more realistic test, we tried to build an atomic model of the GroEL/ES complex by fitting 21-subunit atomic models into the 3D density map obtained by cryoelectron microscopy using the C7 symmetric restraints. A model with low root mean-square deviations (14.7 Å) was obtained as the lowest-energy model, showing that our fitting method was reasonably accurate. Inclusion of other restraints from biological and biochemical experiments could further enhance the accuracy.

Subnanometer-resolution electron cryomicroscopy-based domain models for the cytoplasmic region of skeletal muscle RyR channel

The skeletal muscle Ca(2+) release channel (RyR1), a homotetramer, regulates the release of Ca(2+) from the sarcoplasmic reticulum to initiate muscle contraction. In this work, we have delineated the RyR1 monomer boundaries in a subnanometer-resolution electron cryomicroscopy (cryo-EM) density map. In the cytoplasmic region of each RyR1 monomer, 36 alpha-helices and 7 beta-sheets can be resolved. A beta-sheet was also identified close to the membrane-spanning region that resembles the cytoplasmic pore structures of inward rectifier K(+) channels. Three structural folds, generated for amino acids 12-565 using comparative modeling and cryo-EM density fitting, localize close to regions implicated in communication with the voltage sensor in the transverse tubules. Eleven of the 15 disease-related residues for these domains are mapped to the surface of these models. Four disease-related residues are found in a basin at the interfaces of these regions, creating a pocket in which the immunophilin FKBP12 can fit. Taken together, these results provide a structural context for both channel gating and the consequences of certain malignant hyperthermia and central core disease-associated mutations in RyR1.

Fiber formation across the bacterial outer membrane by the chaperone/usher pathway

Gram-negative pathogens commonly exhibit adhesive pili on their surfaces that mediate specific attachment to the host. A major class of pili is assembled via the chaperone/usher pathway. Here, the structural basis for pilus fiber assembly and secretion performed by the outer membrane assembly platform--the usher--is revealed by the crystal structure of the translocation domain of the P pilus usher PapC and single particle cryo-electron microscopy imaging of the FimD usher bound to a translocating type 1 pilus assembly intermediate. These structures provide molecular snapshots of a twinned-pore translocation machinery in action. Unexpectedly, only one pore is used for secretion, while both usher protomers are used for chaperone-subunit complex recruitment. The translocating pore itself comprises 24 beta strands and is occluded by a folded plug domain, likely gated by a conformationally constrained beta-hairpin. These structures capture the secretion of a virulence factor across the outer membrane of gram-negative bacteria.

Protein structure fitting and refinement guided by cryo-EM density

For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 A). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At approximately 10 A resolution, Calpha rmsd between the initial and final structures was reduced on average by approximately 53%. The method is automated and can refine both experimental and predicted atomic structures.

Integrating diverse data for structure determination of macromolecular assemblies

To understand the cell, we need to determine the macromolecular assembly structures, which may consist of tens to hundreds of components. First, we review the varied experimental data that characterize the assemblies at several levels of resolution. We then describe computational methods for generating the structures using these data. To maximize completeness, resolution, accuracy, precision, and efficiency of the structure determination, a computational approach is required that uses spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. This approach is illustrated by determining the configuration of the 456 proteins in the nuclear pore complex (NPC) from baker's yeast. With these tools, we are poised to integrate structural information gathered at multiple levels of the biological hierarchy--from atoms to cells--into a common framework.

Using surface envelopes to constrain molecular modeling

Molecular density information (as measured by electron microscopic reconstructions or crystallographic density maps) can be a powerful source of information for molecular modeling. Molecular density constrains models by specifying where atoms should and should not be. Low-resolution density information can often be obtained relatively quickly, and there is a need for methods that use it effectively. We have previously described a method for scoring molecular models with surface envelopes to discriminate between plausible and implausible fits. We showed that we could successfully filter out models with the wrong shape based on this discrimination power. Ideally, however, surface information should be used during the modeling process to constrain the conformations that are sampled. In this paper, we describe an extension of our method for using shape information during computational modeling. We use the envelope scoring metric as part of an objective function in a global optimization that also optimizes distances and angles while avoiding collisions. We systematically tested surface representations of proteins (using all nonhydrogen heavy atoms) with different abundance of distance information and showed that the root mean square deviation (RMSD) of models built with envelope information is consistently improved, particularly in data sets with relatively small sets of short-range distances.

EMatch: an efficient method for aligning atomic resolution subunits into intermediate-resolution cryo-EM maps of large macromolecular assemblies

Structural analysis of biological machines is essential for inferring their function and mechanism. Nevertheless, owing to their large size and instability, deciphering the atomic structure of macromolecular assemblies is still considered as a challenging task that cannot keep up with the rapid advances in the protein-identification process. In contrast, structural data at lower resolution is becoming more and more available owing to recent advances in cryo-electron microscopy (cryo-EM) techniques. Once a cryo-EM map is acquired, one of the basic questions asked is what are the folds of the components in the assembly and what is their configuration. Here, a novel knowledge-based computational method, named EMatch, towards tackling this task for cryo-EM maps at 6-10 A resolution is presented. The method recognizes and locates possible atomic resolution structural homologues of protein domains in the assembly. The strengths of EMatch are demonstrated on a cryo-EM map of native GroEL at 6 A resolution.

EMatch: discovery of high resolution structural homologues of protein domains in intermediate resolution cryo-EM maps

Cryo-EM has become an increasingly powerful technique for elucidating the structure, dynamics, and function of large flexible macromolecule assemblies that cannot be determined at atomic resolution. However, due to the relatively low resolution of cryo-EM data, a major challenge is to identify components of complexes appearing in cryo-EM maps. Here, we describe EMatch, a novel integrated approach for recognizing structural homologues of protein domains present in a 6-10 A resolution cryo-EM map and constructing a quasi-atomic structural model of their assembly. The method is highly efficient and has been successfully validated on various simulated data. The strength of the method is demonstrated by a domain assembly of an experimental cryo-EM map of native GroEL at 6 A resolution.

Density-based score for selecting near-native atomic models of unknown structures

We present a low-resolution density-based scoring scheme for selecting high-quality models from a large pool of lesser quality models. We use pre-configured decoy data sets that contain large numbers of models with different degrees of correctness to evaluate the performance of the strategy. We find that the scoring scheme consistently identifies one of the highest quality models for a wide variety of target structures, resolution ranges, and noise models. Tests with experimental data yield similar results.

ADP_EM: fast exhaustive multi-resolution docking for high-throughput coverage

MOTIVATION

Efficient fitting tools are needed to take advantage of a fast growth of atomic models of protein domains from crystallography or comparative modeling, and low-resolution density maps of larger molecular assemblies. Here, we report a novel fitting algorithm for the exhaustive and fast overlay of partial high-resolution models into a low-resolution density map. The method incorporates a fast rotational search based on spherical harmonics (SH) combined with a simple translational scanning.

RESULTS

This novel combination makes it possible to accurately dock atomic structures into low-resolution electron-density maps in times ranging from seconds to a few minutes. The high-efficiency achieved with simulated and experimental test cases preserves the exhaustiveness needed in these heterogeneous-resolution merging tools. The results demonstrate its efficiency, robustness and high-throughput coverage.

AVAILABILITY

http://sbg.cib.csic.es/Software/ADP_EM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Flexible fitting in 3D-EM with incomplete data on superfamily variability

We present a substantial improvement of S-flexfit, our recently proposed method for flexible fitting in three dimensional electron microscopy (3D-EM) at a resolution range of 8-12A, together with a comparison of the method capabilities with Normal Mode Analysis (NMA), application examples and a user's guide. S-flexfit uses the evolutionary information contained in protein domain databases like CATH, by means of the structural alignment of the elements of a protein superfamily. The added development is based on a recent extension of the Singular Value Decomposition (SVD) algorithm specifically designed for situations with missing data: Incremental Singular Value Decomposition (ISVD). ISVD can manage gaps and allows considering more aminoacids in the structural alignment of a superfamily, extending the range of application and producing better models for the fitting step of our methodology. Our previous SVD-based flexible fitting approach can only take into account positions with no gaps in the alignment, being appropriate when the superfamily members are relatively similar and there are few gaps. However, with new data coming from structural proteomics works, the later situation is becoming less likely, making ISVD the technique of choice for further works. We present the results of using ISVD in the process of flexible fitting with both simulated and experimental 3D-EM maps (GroEL and Poliovirus 135S cell entry intermediate).

Ab initio modeling of the herpesvirus VP26 core domain assessed by CryoEM density

Efforts in structural biology have targeted the systematic determination of all protein structures through experimental determination or modeling. In recent years, 3-D electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structures of these large macromolecular assemblies to intermediate resolutions (6–10 Å). While these structures provide a snapshot of the assembly and its components in well-defined functional states, the resolution limits the ability to build accurate structural models. In contrast, sequence-based modeling techniques are capable of producing relatively robust structural models for isolated proteins or domains. In this work, we developed and applied a hybrid modeling approach, utilizing cryoEM density and ab initio modeling to produce a structural model for the core domain of a herpesvirus structural protein, VP26. Specifically, this method, first tested on simulated data, utilizes the cryoEM density map as a geometrical constraint in identifying the most native-like models from a gallery of models generated by ab initio modeling. The resulting model for the core domain of VP26, based on the 8.5-Å resolution herpes simplex virus type 1 (HSV-1) capsid cryoEM structure and mutational data, exhibited a novel fold. Additionally, the core domain of VP26 appeared to have a complementary interface to the known upper-domain structure of VP5, its cognate binding partner. While this new model provides for a better understanding of the assembly and interactions of VP26 in HSV-1, the approach itself may have broader applications in modeling the components of large macromolecular assemblies.

Efforts in structural genomics have targeted the systematic determination of all protein structures primarily using X-ray crystallography and nuclear magnetic resonance. These initiatives have typically focused on domains, single-protein and in some cases small complexes, and as such macromolecular machines are relatively underrepresented. However, in recent years, electron cryomicroscopy (cryoEM) has assumed an increasingly important role in determining the structure of large macromolecular machines in their biologically active states to intermediate resolutions (5–10 Å). Concurrently, modeling techniques, such as comparative and ab initio modeling, have played an increasingly important role in structure determination of small proteins not amenable to other structural techniques. In this work, Baker and colleagues have leveraged ab initio modeling and cryoEM to assess and identify structural models for the macromolecular components within a large complex. Specifically, the cryoEM density can be used to select the most native-like models from a large gallery of potential models. Applied to the smallest herpesvirus capsid protein, VP26 (12 kDa), it was possible to determine its core domain structure (residues 42–105), which helped to elucidate interactions among the structural protein in the virion. Beyond VP26, these techniques potentially provide a new pathway for accurate structure determination of proteins in their biological and functional states.

Flexible Fitting in 3D-EM Guided by the Structural Variability of Protein Superfamilies

A method for flexible fitting of molecular models into three-dimensional electron microscopy (3D-EM) reconstructions at a resolution range of 8-12 A is proposed. The approach uses the evolutionarily related structural variability existing among the protein domains of a given superfamily, according to structural databases such as CATH. A structural alignment of domains belonging to the superfamily, followed by a principal components analysis, is performed, and the first three principal components of the decomposition are explored. Using rigid body transformations for the secondary structure elements (SSEs) plus the cyclic coordinate descent algorithm to close the loops, stereochemically correct models are built for the structure to fit. All of the models are fitted into the 3D-EM map, and the best one is selected based on crosscorrelation measures. This work applies the method to both simulated and experimental data and shows that the flexible fitting was able to produce better results than rigid body fitting.

A composite score for predicting errors in protein structure models

Reliable prediction of model accuracy is an important unsolved problem in protein structure modeling. To address this problem, we studied 24 individual assessment scores, including physics-based energy functions, statistical potentials, and machine learning-based scoring functions. Individual scores were also used to construct approximately 85,000 composite scoring functions using support vector machine (SVM) regression. The scores were tested for their abilities to identify the most native-like models from a set of 6000 comparative models of 20 representative protein structures. Each of the 20 targets was modeled using a template of <30% sequence identity, corresponding to challenging comparative modeling cases. The best SVM score outperformed all individual scores by decreasing the average RMSD difference between the model identified as the best of the set and the model with the lowest RMSD (DeltaRMSD) from 0.63 A to 0.45 A, while having a higher Pearson correlation coefficient to RMSD (r=0.87) than any other tested score. The most accurate score is based on a combination of the DOPE non-hydrogen atom statistical potential; surface, contact, and combined statistical potentials from MODPIPE; and two PSIPRED/DSSP scores. It was implemented in the SVMod program, which can now be applied to select the final model in various modeling problems, including fold assignment, target-template alignment, and loop modeling.

Refinement of Protein Structures by Iterative Comparative Modeling and CryoEM Density Fitting

We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52% to 66%, which is half-way between the starting models and the models from the best possible alignments (82%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.

Combining electron microscopy and comparative protein structure modeling

Recently, advances have been made in methods and applications that integrate electron microscopy density maps and comparative modeling to produce atomic structures of macromolecular assemblies. Electron microscopy can benefit from comparative modeling through the fitting of comparative models into electron microscopy density maps. Also, comparative modeling can benefit from electron microscopy through the use of intermediate-resolution density maps in fold recognition, template selection and sequence-structure alignment.

Structural characterization of assemblies from overall shape and subcomplex compositions

We suggest structure characterization of macromolecular assemblies by combining assembly shape determined by electron cyromicroscopy with information about subunit proximity determined by affinity purification. To achieve this aim, structure characterization is expressed as a problem in satisfaction of spatial restraints that (1) represents subunits as spheres, (2) encodes information about the subunit excluded volume, assembly shape, and pulldowns in a scoring function, and (3) finds subunit configurations that satisfy the input restraints by an optimization of the scoring function. Testing of the approach with model systems suggests its feasibility.

Electron cryomicroscopy of biological machines at subnanometer resolution

Advances in electron cryomicroscopy (cryo-EM) have made possible the structural determination of large biological machines in the resolution range of 6-9 angstroms. Rice dwarf virus and the acrosomal bundle represent two distinct types of machines amenable to cryo-EM investigations at subnanometer resolutions. However, calculating the density map is only the first step, and much analysis remains to extract structural insights and the mechanism of action in these machines. This paper will review the computational and visualization methodologies necessary for analysis (structure mining) of the computed cryo-EM maps of these machines. These steps include component segmentation, averaging based on local symmetry among components, density connectivity trace, incorporation of bioinformatics analysis, and fitting of high-resolution component data, if available. The consequences of these analyses can not only identify accurately some of the secondary structure elements of the molecular components in machines but also suggest structural mechanisms related to their biological functions.