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

Current View on EpCAM Structural Biology

EpCAM, a carcinoma cell-surface marker protein and a therapeutic target, has been primarily addressed as a cell adhesion molecule. With regard to recent discoveries of its role in signaling with implications in cell proliferation and differentiation, and findings contradicting a direct role in mediating adhesion contacts, we provide a comprehensive and updated overview on the available structural data on EpCAM and interpret it in the light of recent reports on its function. First, we describe the structure of extracellular part of EpCAM, both as a subunit and part of a cis-dimer which, according to several experimental observations, represents a biologically relevant oligomeric state. Next, we provide a thorough evaluation of reports on EpCAM as a homophilic cell adhesion molecule with a structure-based explanation why direct EpCAM participation in cell–cell contacts is highly unlikely. Finally, we review the signaling aspect of EpCAM with focus on accessibility of signaling-associated cleavage sites.

Experimentally-driven protein structure modeling

Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.

Cross-linking/mass spectrometry at the crossroads

Cross-linking/mass spectrometry (XL-MS) has come a long way. Originally, XL-MS was used to study relatively small, purified proteins. Meanwhile, it is employed to investigate protein-protein interactions on a proteome-wide level, giving snapshots of cellular processes. Currently, XL-MS is at the intersection of a multitude of workflows and the impact this technique has in addressing specific biological questions is steadily growing. This article is intended to give a bird's-eye view of the current status of XL-MS, the benefits of using MS-cleavable cross-linkers, and the challenges posed in the future development of this powerful technology. We also illustrate how XL-MS can deliver valuable structural insights into protein complexes when used in combination with other structural techniques, such as electron microscopy. Graphical abstract.

Structural Biology in the Multi-Omics Era

Rapid developments in cryogenic electron microscopy have opened new avenues to probe the structures of protein assemblies in their near native states. Recent studies have begun applying single -particle analysis to heterogeneous mixtures, revealing the potential of structural-omics approaches that combine the power of mass spectrometry and electron microscopy. Here we highlight advances and challenges in sample preparation, data processing, and molecular modeling for handling increasingly complex mixtures. Such advances will help structural-omics methods extend to cellular-level models of structural biology.

Coarse-grained (hybrid) integrative modeling of biomolecular interactions

The computational modeling field has vastly evolved over the past decades. The early developments of simplified protein systems represented a stepping stone towards establishing more efficient approaches to sample intricated conformational landscapes. Downscaling the level of resolution of biomolecules to coarser representations allows for studying protein structure, dynamics and interactions that are not accessible by classical atomistic approaches. The combination of different resolutions, namely hybrid modeling, has also been proved as an alternative when mixed levels of details are required. In this review, we provide an overview of coarse-grained/hybrid models focusing on their applicability in the modeling of biomolecular interactions. We give a detailed list of ready-to-use modeling software for studying biomolecular interactions allowing various levels of coarse-graining and provide examples of complexes determined by integrative coarse-grained/hybrid approaches in combination with experimental information.

Integrative structure and function of the yeast exocyst complex

Exocyst is an evolutionarily conserved hetero-octameric tethering complex that plays a variety of roles in membrane trafficking, including exocytosis, endocytosis, autophagy, cell polarization, cytokinesis, pathogen invasion, and metastasis. Exocyst serves as a platform for interactions between the Rab, Rho, and Ral small GTPases, SNARE proteins, and Sec1/Munc18 regulators that coordinate spatial and temporal fidelity of membrane fusion. However, its mechanism is poorly described at the molecular level. Here, we determine the molecular architecture of the yeast exocyst complex by an integrative approach, based on a 3D density map from negative-stain electron microscopy (EM) at ~16 Å resolution, 434 disuccinimidyl suberate and 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride cross-links from chemical-crosslinking mass spectrometry, and partial atomic models of the eight subunits. The integrative structure is validated by a previously determined cryo-EM structure, cross-links, and distances from in vivo fluorescence microscopy. Our subunit configuration is consistent with the cryo-EM structure, except for Sec5. While not observed in the cryo-EM map, the integrative model localizes the N-terminal half of Sec3 near the Sec6 subunit. Limited proteolysis experiments suggest that the conformation of Exo70 is dynamic, which may have functional implications for SNARE and membrane interactions. This study illustrates how integrative modeling based on varied low-resolution structural data can inform biologically relevant hypotheses, even in the absence of high-resolution data.

Protein Footprinting: Auxiliary Engine to Power the Structural Biology Revolution

Structural biology is entering an exciting time where many new high-resolution structures of large complexes and membrane proteins are determined regularly. These advances have been driven by over fifteen years of technology advancements, first in macromolecular crystallography, and recently in Cryo-electron microscopy. These structures are allowing detailed questions about functional mechanisms of the structures, and the biology enabled by these structures, to be addressed for the first time. At the same time, mass spectrometry technologies for protein structure analysis, "footprinting" studies, have improved their sensitivity and resolution dramatically and can provide detailed sub-peptide and residue level information for validating structures and interactions or understanding the dynamics of structures in the context of ligand binding or assembly. In this perspective, we review the use of protein footprinting to extend our understanding of macromolecular systems, particularly for systems challenging for analysis by other techniques, such as intrinsically disordered proteins, amyloidogenic proteins, and other proteins/complexes so far recalcitrant to existing methods. We also illustrate how the availability of high-resolution structural information can be a foundation for a suite of hybrid approaches to divine structure-function relationships beyond what individual techniques can deliver.

Principles for Integrative Structural Biology Studies

Integrative structure determination is a powerful approach to modeling the structures of biological systems based on data produced by multiple experimental and theoretical methods, with implications for our understanding of cellular biology and drug discovery. This Primer introduces the theory and methods of integrative approaches, emphasizing the kinds of data that can be effectively included in developing models and using the nuclear pore complex as an example to illustrate the practice and challenges involved. These guidelines are intended to aid the researcher in understanding and applying integrative structural methods to systems of their interest and thus take advantage of this rapidly evolving field.

A Practical Guide to the Simultaneous Determination of Protein Structure and Dynamics Using Metainference

Accurate protein structural ensembles can be determined with metainference, a Bayesian inference method that integrates experimental information with prior knowledge of the system and deals with all sources of uncertainty and errors as well as with system heterogeneity. Furthermore, metainference can be implemented using the metadynamics approach, which enables the computational study of complex biological systems requiring extensive conformational sampling. In this chapter, we provide a step-by-step guide to perform and analyse metadynamic metainference simulations using the ISDB module of the open-source PLUMED library, as well as a series of practical tips to avoid common mistakes. Specifically, we will guide the reader in the process of learning how to model the structural ensemble of a small disordered peptide by combining state-of-the-art molecular mechanics force fields with nuclear magnetic resonance data, including chemical shifts, scalar couplings and residual dipolar couplings.

Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers

For years, immersive interfaces using virtual and augmented reality (AR) for molecular visualization and modeling have promised a revolution in the way how we teach, learn, communicate and work in chemistry, structural biology and related areas. However, most tools available today for immersive modeling require specialized hardware and software, and are costly and cumbersome to set up. These limitations prevent wide use of immersive technologies in education and research centers in a standardized form, which in turn prevents large-scale testing of the actual effects of such technologies on learning and thinking processes. Here, I discuss building blocks for creating marker-based AR applications that run as web pages on regular computers, and explore how they can be exploited to develop web content for handling virtual molecular systems in commodity AR with no more than a webcam- and internet-enabled computer. Examples span from displaying molecules, electron microscopy maps and molecular orbitals with minimal amounts of HTML code, to incorporation of molecular mechanics, real-time estimation of experimental observables and other interactive resources using JavaScript. These web apps provide virtual alternatives to physical, plastic-made molecular modeling kits, where the computer augments the experience with information about spatial interactions, reactivity, energetics, etc. The ideas and prototypes introduced here should serve as starting points for building active content that everybody can utilize online at minimal cost, providing novel interactive pedagogic material in such an open way that it could enable mass-testing of the effect of immersive technologies on chemistry education.

Structural dynamics of the human COP9 signalosome revealed by cross-linking mass spectrometry and integrative modeling

The COP9 signalosome (CSN) is an evolutionarily conserved eight-subunit (CSN1-8) protein complex that controls protein ubiquitination by deneddylating Cullin-RING E3 ligases (CRLs). The activation and function of CSN hinges on its structural dynamics, which has been challenging to decipher by conventional tools. Here, we have developed a multichemistry cross-linking mass spectrometry approach enabled by three mass spectometry-cleavable cross-linkers to generate highly reliable cross-link data. We applied this approach with integrative structure modeling to determine the interaction and structural dynamics of CSN with the recently discovered ninth subunit, CSN9, in solution. Our results determined the localization of CSN9 binding sites and revealed CSN9-dependent structural changes of CSN. Together with biochemical analysis, we propose a structural model in which CSN9 binding triggers CSN to adopt a configuration that facilitates CSN-CRL interactions, thereby augmenting CSN deneddylase activity. Our integrative structure analysis workflow can be generalized to define in-solution architectures of dynamic protein complexes that remain inaccessible to other approaches.

Integrating cryo-EM and NMR data

Single-particle cryo-electron microscopy (cryo-EM) is increasingly used as a technique to determine the atomic structure of challenging biological systems. Recent advances in microscope engineering, electron detection, and image processing have allowed the structural determination of bigger and more flexible targets than possible with the complementary techniques X-ray crystallography and NMR spectroscopy. However, there exist many biological targets for which atomic resolution cannot be currently achieved with cryo-EM, making unambiguous determination of the protein structure impossible. Although determining the structure of large biological systems using solely NMR is often difficult, highly complementary experimental atomic-level data for each molecule can be derived from the spectra, and used in combination with cryo-EM data. We review here strategies with which both techniques can be synergistically combined, in order to reach detail and understanding unattainable by each technique acting alone; and the types of biological systems for which such an approach would be desirable.

Cross-linking Mass Spectrometry Analysis of the Yeast Nucleus Reveals Extensive Protein-Protein Interactions Not Detected by Systematic Two-Hybrid or Affinity Purification-Mass Spectrometry

Saccharomyces cerevisiae has the most comprehensively characterized protein-protein interaction network, or interactome, of any eukaryote. This has predominantly been generated through multiple, systematic studies of protein-protein interactions by two-hybrid techniques and of affinity-purified protein complexes. A pressing question is to understand how large-scale cross-linking mass spectrometry (XL-MS) can confirm and extend this interactome. Here, intact yeast nuclei were subject to cross-linking with disuccinimidyl sulfoxide (DSSO) and analyzed using hybrid MS2-MS3 methods. XlinkX identified a total of 2,052 unique residue pair cross-links at 1% FDR. Intraprotein cross-links were found to provide extensive structural constraint data, with almost all intralinks that mapped to known structures and slightly fewer of those mapping to homology models being within 30 Å. Intralinks provided structural information for a further 366 proteins. A method for optimizing interprotein cross-link score cut-offs was developed, through use of extensive known yeast interactions. Its application led to a high confidence, yeast nuclear interactome. Strikingly, almost half of the interactions were not previously detected by two-hybrid or AP-MS techniques. Multiple lines of evidence existed for many such interactions, whether through literature or ortholog interaction data, through multiple unique interlinks between proteins, and/or through replicates. We conclude that XL-MS is a powerful means to measure interactions, that complements two-hybrid and affinity-purification techniques.

A Guide for Protein-Protein Docking Using SwarmDock

Many of the biological functions of the cell are driven by protein-protein interactions. However, determining which proteins interact and exactly how they do so to enable their functions, remain major research questions. Functional interactions are dependent on a number of complicated factors; therefore, modeling the three-dimensional structure of protein-protein complexes is still considered a complex endeavor. Nevertheless, the rewards for modeling protein interactions to atomic level detail are substantial, and there are numerous examples of how models can provide useful information for drug design, protein engineering, systems biology, and understanding of the immune system. Here, we provide practical guidelines for docking proteins using the web-server, SwarmDock, a flexible protein-protein docking method. Moreover, we provide an overview of the factors that need to be considered when deciding whether docking is likely to be successful.

Modeling of Multimolecular Complexes

Macromolecular complexes play a key role in cellular function. Predicting the structure and dynamics of these complexes is one of the key challenges in structural biology. Docking applications have traditionally been used to predict pairwise interactions between proteins. However, few methods exist for modeling multi-protein assemblies. Here we present two methods, CombDock and DockStar, that can predict multi-protein assemblies starting from subunit structural models. CombDock can assemble subunits without any assumptions about the pairwise interactions between subunits, while DockStar relies on the interaction graph or, alternatively, a homology model or a cryo-electron microscopy (EM) density map of the entire complex. We demonstrate the two methods using RNA polymerase II with 12 subunits and TRiC/CCT chaperonin with 16 subunits.

Reporting on the future of integrative structural biology ORAU workshop

Integrative and hybrid methods have the potential to bridge long-standing knowledge gaps in structural biology. These methods will have a prominent role in the future of the field as we make advances toward a complete, unified representation of biology that spans the molecular and cellular scales. The Department of Physics and Astronomy at Clemson University hosted The Future of Integrative Structural Biology workshop on April 29, 2017 and partially sponsored by partially sponsored by a program of the Oak Ridge Associated Universities (ORAU). The workshop brought experts from multiple structural biology disciplines together to discuss near-term steps toward the goal of a molecular atlas of the cell. The discussion focused on the types of structural data that should be represented, how this data should be represented, and how the time domain might be incorporated into such an atlas. The consensus was that an explorable, map-like Virtual Cell, containing both spatial and temporal data bridging the atomic and cellular length scales obtained by multiple experimental methods, represents the best path toward a complete atlas of the cell.

Chemical Cross-Linking and Mass Spectrometric Analysis of the Endogenous Yeast Exosome Complexes

Chemical cross-linking and mass spectrometric readout (CX-MS) has become a useful toolkit for structural analysis of protein complexes. CX-MS enables rapid detection of a larger number of cross-link peptides from the chemically cross-linked protein assembly, providing invaluable cross-link spatial restraints to understand the architecture of the complex. Since CX-MS is complementary with other structural and computational modeling tools, it can be used for integrative structural determination of large native protein assemblies. However, due to technical limitations, current CX-MS applications have still been predominantly confined to complexes reconstituted from recombinant proteins where large amount of purified materials are available. Cross-linking and hybrid structural proteomic analysis of endogenous protein complexes remains a challenge. In this chapter, we present a protocol that efficiently couples affinity capture of endogenous complexes with sensitive CX-MS analysis, with particular application to the yeast RNA processing exosome complexes.

Integrating Molecular Simulation and Experimental Data: A Bayesian/Maximum Entropy Reweighting Approach

We describe a Bayesian/Maximum entropy (BME) procedure and software to construct a conformational ensemble of a biomolecular system by integrating molecular simulations and experimental data. First, an initial conformational ensemble is constructed using, for example, Molecular Dynamics or Monte Carlo simulations. Due to potential inaccuracies in the model and finite sampling effects, properties predicted from simulations may not agree with experimental data. In BME we use the experimental data to refine the simulation so that the new conformational ensemble has the following properties: (1) the calculated averages are close to the experimental values taking uncertainty into account and (2) it maximizes the relative Shannon entropy with respect to the original simulation ensemble. The output of this procedure is a set of optimized weights that can be used to calculate other properties and distributions of these. Here, we provide a practical guide on how to obtain and use such weights, how to choose adjustable parameters and discuss shortcomings of the method.

Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.

Auto-regulation of Rab5 GEF activity in Rabex5 by allosteric structural changes, catalytic core dynamics and ubiquitin binding

Intracellular trafficking depends on the function of Rab GTPases, whose activation is regulated by guanine exchange factors (GEFs). The Rab5 GEF, Rabex5, was previously proposed to be auto-inhibited by its C-terminus. Here, we studied full-length Rabex5 and Rabaptin5 proteins as well as domain deletion Rabex5 mutants using hydrogen deuterium exchange mass spectrometry. We generated a structural model of Rabex5, using chemical cross-linking mass spectrometry and integrative modeling techniques. By correlating structural changes with nucleotide exchange activity for each construct, we uncovered new auto-regulatory roles for the ubiquitin binding domains and the Linker connecting those domains to the catalytic core of Rabex5. We further provide evidence that enhanced dynamics in the catalytic core are linked to catalysis. Our results suggest a more complex auto-regulation mechanism than previously thought and imply that ubiquitin binding serves not only to position Rabex5 but to also control its Rab5 GEF activity through allosteric structural alterations.

EVR: reconstruction of bacterial chromosome 3D structure models using error-vector resultant algorithm

BACKGROUND

More and more 3C/Hi-C experiments on prokaryotes have been published. However, most of the published modeling tools for chromosome 3D structures are targeting at eukaryotes. How to transform prokaryotic experimental chromosome interaction data into spatial structure models is an important task and in great need.

RESULTS

We have developed a new reconstruction program for bacterial chromosome 3D structure models called EVR that exploits a simple Error-Vector Resultant (EVR) algorithm. This software tool is particularly optimized for the closed-loop structural features of prokaryotic chromosomes. The parallel implementation of the program can utilize the computing power of both multi-core CPUs and GPUs.

CONCLUSIONS

EVR can be used to reconstruct the bacterial 3D chromosome structure based on the contact frequency matrix derived from 3C/Hi-C experimental data quickly and precisely.

Structural Organization and Dynamics of Homodimeric Cytohesin Family Arf GTPase Exchange Factors in Solution and on Membranes

Membrane dynamic processes require Arf GTPase activation by guanine nucleotide exchange factors (GEFs) with a Sec7 domain. Cytohesin family Arf GEFs function in signaling and cell migration through Arf GTPase activation on the plasma membrane and endosomes. In this study, the structural organization of two cytohesins (Grp1 and ARNO) was investigated in solution by size exclusion-small angle X-ray scattering and negative stain-electron microscopy and on membranes by dynamic light scattering, hydrogen-deuterium exchange-mass spectrometry and guanosine diphosphate (GDP)/guanosine triphosphate (GTP) exchange assays. The results suggest that cytohesins form elongated dimers with a central coiled coil and membrane-binding pleckstrin-homology (PH) domains at opposite ends. The dimers display significant conformational heterogeneity, with a preference for compact to intermediate conformations. Phosphoinositide-dependent membrane recruitment is mediated by one PH domain at a time and alters the conformational dynamics to prime allosteric activation by Arf-GTP. A structural model for membrane targeting and allosteric activation of full-length cytohesin dimers is discussed.

Evolving SAXS versatility: solution X-ray scattering for macromolecular architecture, functional landscapes, and integrative structural biology

Small-angle X-ray scattering (SAXS) has emerged as an enabling integrative technique for comprehensive analyses of macromolecular structures and interactions in solution. Over the past two decades, SAXS has become a mainstay of the structural biologist's toolbox, supplying multiplexed measurements of molecular shape and dynamics that unveil biological function. Here, we discuss evolving SAXS theory, methods, and applications that extend the field of small-angle scattering beyond simple shape characterization. SAXS, coupled with size-exclusion chromatography (SEC-SAXS) and time-resolved (TR-SAXS) methods, is now providing high-resolution insight into macromolecular flexibility and ensembles, delineating biophysical landscapes, and facilitating high-throughput library screening to assess macromolecular properties and to create opportunities for drug discovery. Looking forward, we consider SAXS in the integrative era of hybrid structural biology methods, its potential for illuminating cellular supramolecular and mesoscale structures, and its capacity to complement high-throughput bioinformatics sequencing data. As advances in the field continue, we look forward to proliferating uses of SAXS based upon its abilities to robustly produce mechanistic insights for biology and medicine.

Modelling structures in cryo-EM maps

Recent advances in structure determination of sub-cellular structures using cryo-electron microscopy and tomography have enabled us to understand their architecture in a more detailed manner and gain insight into their function. The choice of approach to use for atomic model building, fitting, refinement and validation in the 3D map resulting from these experiments depends primarily on the resolution of the map and the prior information on the corresponding model. Here, we survey some of such methods and approaches and highlight their uses in specific recent examples.

MARTINI-Based Protein-DNA Coarse-Grained HADDOCKing

Modeling biomolecular assemblies is an important field in computational structural biology. The inherent complexity of their energy landscape and the computational cost associated with modeling large and complex assemblies are major drawbacks for integrative modeling approaches. The so-called coarse-graining approaches, which reduce the degrees of freedom of the system by grouping several atoms into larger “pseudo-atoms,” have been shown to alleviate some of those limitations, facilitating the identification of the global energy minima assumed to correspond to the native state of the complex, while making the calculations more efficient. Here, we describe and assess the implementation of the MARTINI force field for DNA into HADDOCK, our integrative modeling platform. We combine it with our previous implementation for protein-protein coarse-grained docking, enabling coarse-grained modeling of protein-nucleic acid complexes. The system is modeled using MARTINI topologies and interaction parameters during the rigid body docking and semi-flexible refinement stages of HADDOCK, and the resulting models are then converted back to atomistic resolution by an atom-to-bead distance restraints-guided protocol. We first demonstrate the performance of this protocol using 44 complexes from the protein-DNA docking benchmark, which shows an overall ~6-fold speed increase and maintains similar accuracy as compared to standard atomistic calculations. As a proof of concept, we then model the interaction between the PRC1 and the nucleosome (a former CAPRI target in round 31), using the same information available at the time the target was offered, and compare all-atom and coarse-grained models.

SSEThread: Integrative threading of the DNA-PKcs sequence based on data from chemical cross-linking and hydrogen deuterium exchange

X-ray crystallography and electron microscopy maps resolved to 3-8 Å are generally sufficient for tracing the path of the polypeptide chain in space, while often insufficient for unambiguously registering the sequence on the path (i.e., threading). Frequently, however, additional information is available from other biophysical experiments, physical principles, statistical analyses, and other prior models. Here, we formulate an integrative approach for sequence assignment to a partial backbone model as an optimization problem, which requires three main components: the representation of the system, the scoring function, and the optimization method. The method is implemented in the open source Integrative Modeling Platform (IMP) (https://integrativemodeling.org), allowing a number of different terms in the scoring function. We apply this method to localizing the sequence assignment within a 199-residue disordered region of three structured and sequence unassigned helices in the DNA-PKcs crystallographic structure, using chemical crosslinks, hydrogen deuterium exchange, and sequence connectivity. The resulting ensemble of threading models provides two major solutions, one of which suggests that the crucial ABCDE cluster of phosphorylation sites cannot undergo intra-molecular autophosphorylation without a conformational rearrangement. The ensemble of solutions embodies the most accurate and precise sequence threading given the available information.

Molecular architecture of the Bardet-Biedl syndrome protein 2-7-9 subcomplex

Bardet-Biedl syndrome (BBS) is a genetic disorder characterized by malfunctions in primary cilia resulting from mutations that disrupt the function of the BBSome, an 8-subunit complex that plays an important role in protein transport in primary cilia. To better understand the molecular basis of BBS, here we used an integrative structural modeling approach consisting of EM and chemical cross-linking coupled with MS analyses, to analyze the structure of a BBSome 2-7-9 subcomplex consisting of three homologous BBS proteins, BBS2, BBS7, and BBS9. The resulting molecular model revealed an overall structure that resembles a flattened triangle. We found that within this structure, BBS2 and BBS7 form a tight dimer through a coiled-coil interaction and that BBS9 associates with the dimer via an interaction with the α-helical domain of BBS2. Interestingly, a BBS-associated mutation of BBS2 (R632P) is located in its α-helical domain at the interface between BBS2 and BBS9, and binding experiments indicated that this mutation disrupts the BBS2-BBS9 interaction. This finding suggests that BBSome assembly is disrupted by the R632P substitution, providing molecular insights that may explain the etiology of BBS in individuals harboring this mutation.

Integrative Protein Modeling in RosettaNMR from Sparse Paramagnetic Restraints

Computational methods to predict protein structure from nuclear magnetic resonance (NMR) restraints that only require assignment of backbone signals, hold great potential to study larger proteins. Ideally, computational methods designed to work with sparse data need to add atomic detail that is missing in the experimental restraints. We introduce a comprehensive framework into the Rosetta suite that uses NMR restraints derived from paramagnetic labeling. Specifically, RosettaNMR incorporates pseudocontact shifts, residual dipolar couplings, and paramagnetic relaxation enhancements. It continues to use backbone chemical shifts and nuclear Overhauser effect distance restraints. We assess RosettaNMR for protein structure prediction by folding 28 monomeric proteins and 8 homo-oligomeric proteins. Furthermore, the general applicability of RosettaNMR is demonstrated on two protein-protein and three protein-ligand docking examples. Paramagnetic restraints generated more accurate models for 85% of the benchmark proteins and, when combined with chemical shifts, sampled high-accuracy models (≤2Å) in 50% of the cases.

Reconstruction of low-resolution molecular structures from simulated atomic force microscopy images

BACKGROUND

Atomic Force Microscopy (AFM) is an experimental technique to study structure-function relationship of biomolecules. AFM provides images of biomolecules at nanometer resolution. High-speed AFM experiments produce a series of images following dynamics of biomolecules. To further understand biomolecular functions, information on three-dimensional (3D) structures is beneficial.

METHOD

We aim to recover 3D information from an AFM image by computational modeling. The AFM image includes only low-resolution representation of a molecule; therefore we represent the structures by a coarse grained model (Gaussian mixture model). Using Monte-Carlo sampling, candidate models are generated to increase similarity between AFM images simulated from the models and target AFM image.

RESULTS

The algorithm was tested on two proteins to model their conformational transitions. Using a simulated AFM image as reference, the algorithm can produce a low-resolution 3D model of the target molecule. Effect of molecular orientations captured in AFM images on the 3D modeling performance was also examined and it is shown that similar accuracy can be obtained for many orientations.

CONCLUSIONS

The proposed algorithm can generate 3D low-resolution protein models, from which conformational transitions observed in AFM images can be interpreted in more detail.

GENERAL SIGNIFICANCE

High-speed AFM experiments allow us to directly observe biomolecules in action, which provides insights on biomolecular function through dynamics. However, as only partial structural information can be obtained from AFM data, this new AFM based hybrid modeling method would be useful to retrieve 3D information of the entire biomolecule.

Predicting Protein Complex Structure from Surface-Induced Dissociation Mass Spectrometry Data

Recently, mass spectrometry (MS) has become a viable method for elucidation of protein structure. Surface-induced dissociation (SID), colliding multiply charged protein complexes or other ions with a surface, has been paired with native MS to provide useful structural information such as connectivity and topology for many different protein complexes. We recently showed that SID gives information not only on connectivity and topology but also on relative interface strengths. However, SID has not yet been coupled with computational structure prediction methods that could use the sparse information from SID to improve the prediction of quaternary structures, i.e., how protein subunits interact with each other to form complexes. Protein-protein docking, a computational method to predict the quaternary structure of protein complexes, can be used in combination with subunit structures from X-ray crystallography and NMR in situations where it is difficult to obtain an experimental structure of an entire complex. While de novo structure prediction can be successful, many studies have shown that inclusion of experimental data can greatly increase prediction accuracy. In this study, we show that the appearance energy (AE, defined as 10% fragmentation) extracted from SID can be used in combination with Rosetta to successfully evaluate protein-protein docking poses. We developed an improved model to predict measured SID AEs and incorporated this model into a scoring function that combines the RosettaDock scoring function with a novel SID scoring term, which quantifies agreement between experiments and structures generated from RosettaDock. As a proof of principle, we tested the effectiveness of these restraints on 57 systems using ideal SID AE data (AE determined from crystal structures using the predictive model). When theoretical AEs were used, the RMSD of the selected structure improved or stayed the same in 95% of cases. When experimental SID data were incorporated on a different set of systems, the method predicted near-native structures (less than 2 Å root-mean-square deviation, RMSD, from native) for 6/9 tested cases, while unrestrained RosettaDock (without SID data) only predicted 3/9 such cases. Score versus RMSD funnel profiles were also improved when SID data were included. Additionally, we developed a confidence measure to evaluate predicted model quality in the absence of a crystal structure.

Structural mass spectrometry goes viral

Over the last 20 years, mass spectrometry (MS), with its ability to analyze small sample amounts with high speed and sensitivity, has more and more entered the field of structural virology, aiming to investigate the structure and dynamics of viral proteins as close to their native environment as possible. The use of non-perturbing labels in hydrogen-deuterium exchange MS allows for the analysis of interactions between viral proteins and host cell factors as well as their dynamic responses to the environment. Cross-linking MS, on the other hand, can analyze interactions in viral protein complexes and identify virus-host interactions in cells. Native MS allows transferring viral proteins, complexes and capsids into the gas phase and has broken boundaries to overcome size limitations, so that now even the analysis of intact virions is possible. Different MS approaches not only inform about size, stability, interactions and dynamics of virus assemblies, but also bridge the gap to other biophysical techniques, providing valuable constraints for integrative structural modeling of viral complex assemblies that are often inaccessible by single technique approaches. In this review, recent advances are highlighted, clearly showing that structural MS approaches in virology are moving towards systems biology and ever more experiments are performed on cellular level.

Structural basis of Cullin 2 RING E3 ligase regulation by the COP9 signalosome

Cullin-Ring E3 Ligases (CRLs) regulate a multitude of cellular pathways through specific substrate receptors. The COP9 signalosome (CSN) deactivates CRLs by removing NEDD8 from activated Cullins. Here we present structures of the neddylated and deneddylated CSN-CRL2 complexes by combining single-particle cryo-electron microscopy (cryo-EM) with chemical cross-linking mass spectrometry (XL-MS). These structures suggest a conserved mechanism of CSN activation, consisting of conformational clamping of the CRL2 substrate by CSN2/CSN4, release of the catalytic CSN5/CSN6 heterodimer and finally activation of the CSN5 deneddylation machinery. Using hydrogen-deuterium exchange (HDX)-MS we show that CRL2 activates CSN5/CSN6 in a neddylation-independent manner. The presence of NEDD8 is required to activate the CSN5 active site. Overall, by synergising cryo-EM with MS, we identify sensory regions of the CSN that mediate its stepwise activation and provide a framework for understanding the regulatory mechanism of other Cullin family members.

Protein Docking Using a Single Representation for Protein Surface, Electrostatics, and Local Dynamics

Predicting the assembly of multiple proteins into specific complexes is critical to understanding their biological function in an organism and thus the design of drugs to address their malfunction. Proteins are flexible molecules, which inherently pose a problem to any protein docking computational method, where even a simple rearrangement of the side chain and backbone atoms at the interface of binding partners complicates the successful determination of the correct docked pose. Herein, we present a means of representing protein surface, electrostatics, and local dynamics within a single volumetric descriptor. We show that our representations can be physically related to the surface-accessible solvent area and mass of the protein. We then demonstrate that the application of this representation into a protein-protein docking scenario bypasses the need to compensate for, and predict, specific side chain packing at the interface of binding partners. This representation is leveraged in our de novo protein docking software, JabberDock, which can accurately and robustly predict difficult target complexes with an average success rate of >54%, which is comparable to or greater than the currently available methods.

HotSpot Wizard 3.0: web server for automated design of mutations and smart libraries based on sequence input information

HotSpot Wizard is a web server used for the automated identification of hotspots in semi-rational protein design to give improved protein stability, catalytic activity, substrate specificity and enantioselectivity. Since there are three orders of magnitude fewer protein structures than sequences in bioinformatic databases, the major limitation to the usability of previous versions was the requirement for the protein structure to be a compulsory input for the calculation. HotSpot Wizard 3.0 now accepts the protein sequence as input data. The protein structure for the query sequence is obtained either from eight repositories of homology models or is modeled using Modeller and I-Tasser. The quality of the models is then evaluated using three quality assessment tools—WHAT_CHECK, PROCHECK and MolProbity. During follow-up analyses, the system automatically warns the users whenever they attempt to redesign poorly predicted parts of their homology models. The second main limitation of HotSpot Wizard’s predictions is that it identifies suitable positions for mutagenesis, but does not provide any reliable advice on particular substitutions. A new module for the estimation of thermodynamic stabilities using the Rosetta and FoldX suites has been introduced which prevents destabilizing mutations among pre-selected variants entering experimental testing. HotSpot Wizard is freely available at http://loschmidt.chemi.muni.cz/hotspotwizard.

Assembling multidomain protein structures through analogous global structural alignments

Most proteins exist with multiple domains in cells for cooperative functionality. However, structural biology and protein folding methods are often optimized for single-domain structures, resulting in a rapidly growing gap between the improved capability for tertiary structure determination and high demand for multidomain structure models. We have developed a pipeline, termed DEMO, for constructing multidomain protein structures by docking-based domain assembly simulations, with interdomain orientations determined by the distance profiles from analogous templates as detected through domain-level structure alignments. The pipeline was tested on a comprehensive benchmark set of 356 proteins consisting of 2-7 continuous and discontinuous domains, for which DEMO generated models with correct global fold (TM-score > 0.5) for 86% of cases with continuous domains and for 100% of cases with discontinuous domain structures, starting from randomly oriented target-domain structures. DEMO was also applied to reassemble multidomain targets in the CASP12 and CASP13 experiments using domain structures excised from the top server predictions, where the full-length DEMO models showed a significantly improved quality over the original server models. Finally, sparse restraints of mass spectrometry-generated cross-linking data and cryo-EM density maps are incorporated into DEMO, resulting in improvements in the average TM-score by 6.3% and 12.5%, respectively. The results demonstrate an efficient approach to assembling multidomain structures, which can be easily used for automated, genome-scale multidomain protein structure assembly.

Archiving and disseminating integrative structure models

Limitations in the applicability, accuracy, and precision of individual structure characterization methods can sometimes be overcome via an integrative modeling approach that relies on information from all available sources, including all available experimental data and prior models. The open-source Integrative Modeling Platform (IMP) is one piece of software that implements all computational aspects of integrative modeling. To maximize the impact of integrative structures, the coordinates should be made publicly available, as is already the case for structures based on X-ray crystallography, NMR spectroscopy, and electron microscopy. Moreover, the associated experimental data and modeling protocols should also be archived, such that the original results can easily be reproduced. Finally, it is essential that the integrative structures are validated as part of their publication and deposition. A number of research groups have already developed software to implement integrative modeling and have generated a number of structures, prompting the formation of an Integrative/Hybrid Methods Task Force. Following the recommendations of this task force, the existing PDBx/mmCIF data representation used for atomic PDB structures has been extended to address the requirements for archiving integrative structural models. This IHM-dictionary adds a flexible model representation, including coarse graining, models in multiple states and/or related by time or other order, and multiple input experimental information sources. A prototype archiving system called PDB-Dev ( https://pdb-dev.wwpdb.org ) has also been created to archive integrative structural models, together with a Python library to facilitate handling of integrative models in PDBx/mmCIF format.

Finding Friends in the Crowd: Three-Dimensional Cliques of Topological Genomic Domains

The mammalian genome is intricately folded in a three-dimensional topology believed to be important for the orchestration of gene expression regulating development, differentiation and tissue homeostasis. Important features of spatial genome conformation in the nucleus are promoter-enhancer contacts regulating gene expression within topologically-associated domains (TADs), short- and long-range interactions between TADs and associations of chromatin with nucleoli and nuclear speckles. In addition, anchoring of chromosomes to the nuclear lamina via lamina-associated domains (LADs) at the nuclear periphery is a key regulator of the radial distribution of chromatin. To what extent TADs and LADs act in concert as genomic organizers to shape the three-dimensional topology of chromatin has long remained unknown. A new study addressing this key question provides evidence of (i) preferred long-range associations between TADs forming TAD “cliques” which organize large heterochromatin domains, and (ii) stabilization of TAD cliques by LADs at the nuclear periphery after induction of terminal differentiation. Here, we review these findings, address the issue of whether TAD cliques exist in single cells and discuss the extent of cell-to-cell heterogeneity in higher-order chromatin conformation. The recent observations provide a first appreciation of changes in 4-dimensional higher-order genome topologies during differentiation.

High Accuracy Protein Structures from Minimal Sparse Paramagnetic Solid-State NMR Restraints

There is a pressing need for new computational tools to integrate data from diverse experimental approaches in structural biology. We present a strategy that combines sparse paramagnetic solid-state NMR restraints with physics-based atomistic simulations. Our approach explicitly accounts for uncertainty in the interpretation of experimental data through the use of a semi-quantitative mapping between the data and the restraint energy that is calibrated by extensive simulations. We apply our approach to solid-state NMR data for the model protein GB1 labeled with Cu²⁺ -EDTA at six different sites. We are able to determine the structure to 0.9 Å accuracy within a single day of computation on a GPU cluster. We further show that in some cases, the data from only a single paramagnetic tag are sufficient for accurate folding.

Computational approaches to macromolecular interactions in the cell

Structural modeling of a cell is an evolving strategic direction in computational structural biology. It takes advantage of new powerful modeling techniques, deeper understanding of fundamental principles of molecular structure and assembly, and rapid growth of the amount of structural data generated by experimental techniques. Key modeling approaches to principal types of macromolecular assemblies in a cell already exist. The main challenge, along with the further development of these modeling approaches, is putting them together in a consistent, unified whole cell model. This opinion piece addresses the fundamental aspects of modeling macromolecular assemblies in a cell, and the state-of-the-art in modeling of the principal types of such assemblies.

Role of integrative structural biology in understanding transcriptional initiation

Integrative structural biology combines data from multiple experimental techniques to generate complete structural models for the biological system of interest. Most commonly cross-linking data sets are employed alongside electron microscopy maps, crystallographic structures, and other data by computational methods that integrate all known information and produce structural models at a level of resolution that is appropriate to the input data. The precision of these modelled solutions is limited by the sparseness of cross-links observed, the length of the cross-linking reagent, the ambiguity arisen from the presence of multiple copies of the same protein, and structural and compositional heterogeneity. In recent years integrative structural biology approaches have been successfully applied to a range of RNA polymerase II complexes. Here we will provide a general background to integrative structural biology, a description of how it should be practically implemented and how it has furthered our understanding of the biology of large transcriptional assemblies. Finally, in the context of recent breakthroughs in microscope and direct electron detector technology, where increasingly EM is capable of resolving structural features directly without the aid of other structural techniques, we will discuss the future role of integrative structural techniques.

Principles and characteristics of biological assemblies in experimentally determined protein structures

More than half of all structures in the PDB are assemblies of two or more proteins, including both homooligomers and heterooligomers. Structural information on these assemblies comes from X-ray crystallography, NMR, and cryo-EM spectroscopy. The correct assembly in an X-ray structure is often ambiguous, and computational methods have been developed to identify the most likely biologically relevant assembly based on physical properties of assemblies and sequence conservation in interfaces. Taking advantage of the large number of structures now available, some of the most recent methods have relied on similarity of interfaces and assemblies across structures of homologous proteins.

Simultaneous Determination of Protein Structure and Dynamics Using Cryo-Electron Microscopy

Cryo-electron microscopy is rapidly emerging as a powerful technique to determine the structures of complex macromolecular systems elusive to other techniques. Because many of these systems are highly dynamical, characterizing their movements is also a crucial step to unravel their biological functions. To achieve this goal, we report an integrative modeling approach to simultaneously determine structure and dynamics of macromolecular systems from cryo-electron microscopy density maps. By quantifying the level of noise in the data and dealing with their ensemble-averaged nature, this approach enables the integration of multiple sources of information to model ensembles of structures and infer their populations. We illustrate the method by characterizing structure and dynamics of the integral membrane receptor STRA6, thus providing insights into the mechanisms by which it interacts with retinol binding protein and translocates retinol across the membrane.

Integrative Structure Modeling: Overview and Assessment

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo-electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.