Topological models of heteromeric protein assemblies from mass spectrometry: application to the yeast eIF3:eIF5 complex.

Describing, understanding, and modulating the function of the cell require elucidation of the structures of macromolecular assemblies. Here, we describe an integrative method for modeling heteromeric complexes using as a starting point disassembly pathways determined by native mass spectrometry (MS). In this method, the pathway data and other available information are encoded as a scoring function on the positions of the subunits of the complex. The method was assessed on its ability to reproduce the native contacts in five benchmark cases with simulated MS data and two cases with real MS data. To illustrate the power of our method, we purified the yeast initiation factor 3 (eIF3) complex and characterized it by native MS and chemical crosslinking MS. We established substoichiometric binding of eIF5 and derived a model for the five-subunit eIF3 complex, at domain level, consistent with its role as a scaffold for other initiation factors.

Structural characterization by cross-linking reveals the detailed architecture of a coatomer-related heptameric module from the nuclear pore complex.

Most cellular processes are orchestrated by macromolecular complexes. However, structural elucidation of these endogenous complexes can be challenging because they frequently contain large numbers of proteins, are compositionally and morphologically heterogeneous, can be dynamic, and are often of low abundance in the cell. Here, we present a strategy for the structural characterization of such complexes that has at its center chemical cross-linking with mass spectrometric readout. In this strategy, we isolate the endogenous complexes using a highly optimized sample preparation protocol and generate a comprehensive, high-quality cross-linking dataset using two complementary cross-linking reagents. We then determine the structure of the complex using a refined integrative method that combines the cross-linking data with information generated from other sources, including electron microscopy, X-ray crystallography, and comparative protein structure modeling. We applied this integrative strategy to determine the structure of the native Nup84 complex, a stable hetero-heptameric assembly (∼ 600 kDa), 16 copies of which form the outer rings of the 50-MDa nuclear pore complex (NPC) in budding yeast. The unprecedented detail of the Nup84 complex structure reveals previously unseen features in its pentameric structural hub and provides information on the conformational flexibility of the assembly. These additional details further support and augment the protocoatomer hypothesis, which proposes an evolutionary relationship between vesicle coating complexes and the NPC, and indicates a conserved mechanism by which the NPC is anchored in the nuclear envelope.

Modeling of proteins and their assemblies with the Integrative Modeling Platform.

To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resolution structural characterization of these assemblies is frequently beyond the reach of current experimental methods, such as X-ray crystallography, NMR spectroscopy, electron microscopy, footprinting, chemical cross-linking, FRET spectroscopy, small angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build models of the assembly structures that are consistent with all of the available datasets, and therefore more accurate, precise, and complete. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as well as possible. These generated models can then potentially inform about the precision and accuracy of structure determination, the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific use cases.

SALIGN: a web server for alignment of multiple protein sequences and structures.

SUMMARY: Accurate alignment of protein sequences and/or structures is crucial for many biological analyses, including functional annotation of proteins, classifying protein sequences into families, and comparative protein structure modeling. Described here is a web interface to SALIGN, the versatile protein multiple sequence/structure alignment module of MODELLER. The web server automatically determines the best alignment procedure based on the inputs, while allowing the user to override default parameter values. Multiple alignments are guided by a dendrogram computed from a matrix of all pairwise alignment scores. When aligning sequences to structures, SALIGN uses structural environment information to place gaps optimally. If two multiple sequence alignments of related proteins are input to the server, a profile-profile alignment is performed. All features of the server have been previously optimized for accuracy, especially in the contexts of comparative modeling and identification of interacting protein partners. AVAILABILITY: The SALIGN web server is freely accessible to the academic community at http://salilab.org/salign. SALIGN is a module of the MODELLER software, also freely available to academic users (http://salilab.org/modeller). CONTACT: sali@salilab.org; madhusudhan@bii.a-star.edu.sg.

Putting the pieces together: integrative modeling platform software for structure determination of macromolecular assemblies.

A set of software tools for building and distributing models of macromolecular assemblies uses an integrative structure modeling approach, which casts the building of models as a computational optimization problem where information is encoded into a scoring function used to evaluate candidate models.

Modeling of proteins and their assemblies with the integrative modeling platform.

To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resolution structural characterization of these assemblies is frequently beyond the reach of current experimental methods, such as X-ray crystallography, NMR spectroscopy, electron microscopy, footprinting, chemical cross-linking, FRET spectroscopy, small-angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build computational models of the assembly structures that are consistent with all of the available datasets. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as much as possible. These generated models can then potentially inform about the precision and accuracy of structure determination, the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific-use cases.

MultiFit: a web server for fitting multiple protein structures into their electron microscopy density map.

Advances in electron microscopy (EM) allow for structure determination of large biological assemblies at increasingly higher resolutions. A key step in this process is fitting multiple component structures into an EM-derived density map of their assembly. Here, we describe a web server for this task. The server takes as input a set of protein structures in the PDB format and an EM density map in the MRC format. The output is an ensemble of models ranked by their quality of fit to the density map. The models can be viewed online or downloaded from the website. The service is available at; http://salilab.org/multifit/ and http://bioinfo3d.cs.tau.ac.il/.

Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization).

BACKGROUND: Searching the enormous amount of information available in biomedical literature to extract novel functional relationships among genes remains a challenge in the field of bioinformatics. While numerous (software) tools have been developed to extract and identify gene relationships from biological databases, few effectively deal with extracting new (or implied) gene relationships, a process which is useful in interpretation of discovery-oriented genome-wide experiments. RESULTS: In this study, we develop a Web-based bioinformatics software environment called FAUN or Feature Annotation Using Nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity and parameterization of NMF for processing gene sets are discussed. FAUN is tested on three manually constructed gene document collections. Its utility and performance as a knowledge discovery tool is demonstrated using a set of genes associated with Autism. CONCLUSIONS: FAUN not only assists researchers to use biomedical literature efficiently, but also provides utilities for knowledge discovery. This Web-based software environment may be useful for the validation and analysis of functional associations in gene subsets identified by high-throughput experiments.

Integrative structure modeling of macromolecular assemblies from proteomics data.

Proteomics techniques have been used to generate comprehensive lists of protein interactions in a number of species. However, relatively little is known about how these interactions result in functional multiprotein complexes. This gap can be bridged by combining data from proteomics experiments with data from established structure determination techniques. Correspondingly, integrative computational methods are being developed to provide descriptions of protein complexes at varying levels of accuracy and resolution, ranging from complex compositions to detailed atomic structures.

Detection of specific solvent rearrangement regions of an enzyme: NMR and ITC studies with aminoglycoside phosphotransferase(3')-IIIa.

This work describes differential effects of solvent in complexes of the aminoglycoside phosphotransferase(3')-IIIa (APH) with different aminoglycosides and the detection of change in solvent structure at specific sites away from substrates. Binding of kanamycins to APH occurs with a larger negative DeltaH in H2O relative to D2O (DeltaDeltaH(H2O-D2O) < 0), while the reverse is true for neomycins. Unusually large negative DeltaCp values were observed for binding of aminoglycosides to APH. DeltaCp for the APH-neomycin complex was -1.6 kcal x mol(-1) x deg(-1). A break at 30 degrees C was observed in the APH-kanamycin complex yielding DeltaCp values of -0.7 kcal x mol(-1) x deg(-1) and -3.8 kcal x mol(-1) x deg(-1) below and above 30 degrees C, respectively. Neither the change in accessible surface area (DeltaASA) nor contributions from heats of ionization were sufficient to explain the large negative DeltaCp values. Most significantly, 15N-1H HSQC experiments showed that temperature-dependent shifts of the backbone amide protons of Leu 88, Ser 91, Cys 98, and Leu143 revealed a break at 30 degrees C only in the APH-kanamycin complex in spectra collected between 21 degrees C and 38 degrees C. These amino acids represent solvent reorganization sites that experience a change in solvent structure in their immediate environment as structurally different ligands bind to the enzyme. These residues were away from the substrate binding site and distributed in three hydrophobic patches in APH. Overall, our results show that a large number of factors affect DeltaCp and binding of structurally different ligand groups cause different solvent structure in the active site as well as differentially affecting specific sites away from the ligand binding site.

Redox-dependent structural differences in putidaredoxin derived from homologous structure refinement via residual dipolar couplings.

Structural differences in the [2Fe-2S] ferredoxin, putidaredoxin (Pdx), from the camphor hydroxylation pathway of Pseudomonas putida have been investigated as a function of oxidation state of the iron cluster. Pdx is involved in biological electron transfer to cytochrome P450(cam) (CYP101). Redox-dependent differences have been observed previously for Pdx in terms of binding affinities to CYP101, NMR spectral differences, and dynamic properties. To further characterize these differences, structure refinement of both oxidized and reduced Pdx has been carried out using a hybrid approach utilizing paramagnetic distance restraints and NMR orientational restraints in the form of backbone (15)N residual dipolar couplings. Use of these new restraints has improved the structure of oxidized Pdx considerably over the earlier solution NMR structure without RDC restraints, with the new structure now much closer in overall fold to the recently published X-ray crystal structures. We now observe better defined relative orientations of the major secondary structure elements as also of the conformation of the metal binding loop region. Extension of this approach to structure calculation of reduced Pdx has identified structural differences that are primarily localized for residues in the C-terminal interaction domain consisting of the functionally important residue Trp 106 and regions near the metal binding loop in Pdx. These redox-dependent structural differences in Pdx correlate to dynamic changes observed before and may be linked to differences in binding and electron transfer properties between oxidized and reduced Pdx.