Determining macromolecular assembly structures by molecular docking and fitting into an electron density map

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/.

UCSF Chimera, MODELLER, and IMP: an integrated modeling system

Structural modeling of macromolecular complexes greatly benefits from interactive visualization capabilities. Here we present the integration of several modeling tools into UCSF Chimera. These include comparative modeling by MODELLER, simultaneous fitting of multiple components into electron microscopy density maps by IMP MultiFit, computing of small-angle X-ray scattering profiles and fitting of the corresponding experimental profile by IMP FoXS, and assessment of amino acid sidechain conformations based on rotamer probabilities and local interactions by Chimera.

SymmRef: a flexible refinement method for symmetric multimers

Symmetric protein complexes are abundant in the living cell. Predicting their atomic structure can shed light on the mechanism of many important biological processes. Symmetric docking methods aim to predict the structure of these complexes given the unbound structure of a single monomer, or its model. Symmetry constraints reduce the search-space of these methods and make the prediction easier compared to asymmetric protein-protein docking. However, the challenge of modeling the conformational changes that the monomer might undergo is a major obstacle. In this article, we present SymmRef, a novel method for refinement and reranking of symmetric docking solutions. The method models backbone and side-chain movements and optimizes the rigid-body orientations of the monomers. The backbone movements are modeled by normal modes minimization and the conformations of the side-chains are modeled by selecting optimal rotamers. Since solved structures of symmetric multimers show asymmetric side-chain conformations, we do not use symmetry constraints in the side-chain optimization procedure. The refined models are re-ranked according to an energy score. We tested the method on a benchmark of unbound docking challenges. The results show that the method significantly improves the accuracy and the ranking of symmetric rigid docking solutions. SymmRef is available for download at http:// bioinfo3d.cs.tau.ac.il/SymmRef/download.html.

Bound anions differentially stabilize multiprotein complexes in the absence of bulk solvent

The combination of ion mobility separation with mass spectrometry is an emergent and powerful structural biology tool, capable of simultaneously assessing the structure, topology, dynamics, and composition of large protein assemblies within complex mixtures. An integral part of the ion mobility-mass spectrometry measurement is the ionization of intact multiprotein complexes and their removal from bulk solvent. This process, during which a substantial portion of protein structure and organization is likely to be preserved, imposes a foreign environment on proteins that may cause structural rearrangements to occur. Thus, a general means must be identified to stabilize protein structures in the absence of bulk solvent. Our approach to this problem involves the protection of protein complex structure through the addition of salts in solution prior to desorption/ionization. Anionic components of the added salts bind to the complex either in solution or during the electrospray process, and those that remain bound in the gas phase tend to have high gas phase acidities. The resulting 'shell' of counterions is able to carry away excess energy from the protein complex ion upon activation and can result in significant structural stabilization of the gas-phase protein assembly overall. By using ion mobility-mass spectrometry, we observe both the dissociation and unfolding transitions for four tetrameric protein complexes bound to populations of 12 different anions using collisional activation. The data presented here quantifies, for the first time, the influence of a large range of counterions on gas-phase protein structure and allows us to rank and classify counterions as structure stabilizers in the absence of bulk solvent. Our measurements indicate that tartrate, citrate, chloride, and nitrate anions are among the strongest stabilizers of gas-phase protein structure identified in this screen. The rank order determined by our data is substantially different when compared to the known Hofmeister salt series in solution. While this is an expected outcome of our work, due to the diminished influence of anion and protein solvation by water, our data correlates well to expected anion binding in solution and highlights the fact that both hydration layer and anion-protein binding effects are critical for Hofmeister-type stabilization in solution. Finally, we present a detailed mechanism of action for counterion stabilization of proteins and their complexes in the gas-phase, which indicates that anions must bind with high affinity, but must dissociate readily from the protein in order to be an effective stabilizer. Anion-resolved data acquired for smaller protein systems allows us to classify anions into three categories based on their ability to stabilize protein and protein complex structure in the absence of bulk solvent.

GPU-powered tools boost molecular visualization

Recent advances in experimental structure determination provide a wealth of structural data on huge macromolecular assemblies such as the ribosome or viral capsids, available in public databases. Further structural models arise from reconstructions using symmetry orders or fitting crystal structures into low-resolution maps obtained by electron-microscopy or small angle X-ray scattering experiments. Visual inspection of these huge structures remains an important way of unravelling some of their secrets. However, such visualization cannot conveniently be carried out using conventional rendering approaches, either due to performance limitations or due to lack of realism. Recent developments, in particular drawing benefit from the capabilities of Graphics Processing Units (GPUs), herald the next generation of molecular visualization solutions addressing these issues. In this article, we present advances in computer science and visualization that help biologists visualize, understand and manipulate large and complex molecular systems, introducing concepts that remain little-known in the bioinformatics field. Furthermore, we compile currently available software and methods enhancing the shape perception of such macromolecular assemblies, for example based on surface simplification or lighting ameliorations.

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.

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.