Characterization of an A3G-VifHIV-1-CRL5-CBFβ Structure Using a Cross-linking Mass Spectrometry Pipeline for Integrative Modeling of Host-Pathogen Complexes

Structural analysis of host-pathogen protein complexes remains challenging, largely due to their structural heterogeneity. Here, we describe a pipeline for the structural characterization of these complexes using integrative structure modeling based on chemical cross-links and residue-protein contacts inferred from mutagenesis studies. We used this approach on the HIV-1 Vif protein bound to restriction factor APOBEC3G (A3G), the Cullin-5 E3 ring ligase (CRL5), and the cellular transcription factor Core Binding Factor Beta (CBFβ) to determine the structure of the (A3G-Vif-CRL5-CBFβ) complex. Using the MS-cleavable DSSO cross-linker to obtain a set of 132 cross-links within this reconstituted complex along with the atomic structures of the subunits and mutagenesis data, we computed an integrative structure model of the heptameric A3G-Vif-CRL5-CBFβ complex. The structure, which was validated using a series of tests, reveals that A3G is bound to Vif mostly through its N-terminal domain. Moreover, the model ensemble quantifies the dynamic heterogeneity of the A3G C-terminal domain and Cul5 positions. Finally, the model was used to rationalize previous structural, mutagenesis and functional data not used for modeling, including information related to the A3G-bound and unbound structures as well as mapping functional mutations to the A3G-Vif interface. The experimental and computational approach described here is generally applicable to other challenging host-pathogen protein complexes.

From integrative structural biology to cell biology

Integrative modeling is an increasingly important tool in structural biology, providing structures by combining data from varied experimental methods and prior information. As a result, molecular architectures of large, heterogeneous, and dynamic systems, such as the ∼52-MDa Nuclear Pore Complex, can be mapped with useful accuracy, precision, and completeness. Key challenges in improving integrative modeling include expanding model representations, increasing the variety of input data and prior information, quantifying a match between input information and a model in a Bayesian fashion, inventing more efficient structural sampling, as well as developing better model validation, analysis, and visualization. In addition, two community-level challenges in integrative modeling are being addressed under the auspices of the Worldwide Protein Data Bank (wwPDB). First, the impact of integrative structures is maximized by PDB-Development, a prototype wwPDB repository for archiving, validating, visualizing, and disseminating integrative structures. Second, the scope of structural biology is expanded by linking the wwPDB resource for integrative structures with archives of data that have not been generally used for structure determination but are increasingly important for computing integrative structures, such as data from various types of mass spectrometry, spectroscopy, optical microscopy, proteomics, and genetics. To address the largest of modeling problems, a type of integrative modeling called metamodeling is being developed; metamodeling combines different types of input models as opposed to different types of data to compute an output model. Collectively, these developments will facilitate the structural biology mindset in cell biology and underpin spatiotemporal mapping of the entire cell.

Using Integrative Modeling Platform to compute, validate, and archive a model of a protein complex structure

Biology is advanced by producing structural models of biological systems, such as protein complexes. Some systems are recalcitrant to traditional structure determination methods. In such cases, it may still be possible to produce useful models by integrative structure determination that depends on simultaneous use of multiple types of data. An ensemble of models that are sufficiently consistent with the data is produced by a structural sampling method guided by a data-dependent scoring function. The variation in the ensemble of models quantified the uncertainty of the structure, generally resulting from the uncertainty in the input information and actual structural heterogeneity in the samples used to produce the data. Here, we describe how to generate, assess, and interpret ensembles of integrative structural models using our open source Integrative Modeling Platform program (https://integrativemodeling.org).

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.

Biophysical Techniques in Structural Biology

Over the past six decades, steadily increasing progress in the application of the principles and techniques of the physical sciences to the study of biological systems has led to remarkable insights into the molecular basis of life. Of particular significance has been the way in which the determination of the structures and dynamical properties of proteins and nucleic acids has so often led directly to a profound understanding of the nature and mechanism of their functional roles. The increasing number and power of experimental and theoretical techniques that can be applied successfully to living systems is now ushering in a new era of structural biology that is leading to fundamentally new information about the maintenance of health, the origins of disease, and the development of effective strategies for therapeutic intervention. This article provides a brief overview of some of the most powerful biophysical methods in use today, along with references that provide more detailed information about recent applications of each of them. In addition, this article acts as an introduction to four authoritative reviews in this volume. The first shows the ways that a multiplicity of biophysical methods can be combined with computational techniques to define the architectures of complex biological systems, such as those involving weak interactions within ensembles of molecular components. The second illustrates one aspect of this general approach by describing how recent advances in mass spectrometry, particularly in combination with other techniques, can generate fundamentally new insights into the properties of membrane proteins and their functional interactions with lipid molecules. The third reviewdemonstrates the increasing power of rapidly evolving diffraction techniques, employing the very short bursts of X-rays of extremely high intensity that are now accessible as a result of the construction of free-electron lasers, in particular to carry out time-resolved studies of biochemical reactions. The fourth describes in detail the application of such approaches to probe the mechanism of the light-induced changes associated with bacteriorhodopsin's ability to convert light energy into chemical energy.

Optimizing model representation for integrative structure determination of macromolecular assemblies

Integrative structure determination of macromolecular assemblies requires specifying the representation of the modeled structure, a scoring function for ranking alternative models based on diverse types of data, and a sampling method for generating these models. Structures are often represented at atomic resolution, although ad hoc simplified representations based on generic guidelines and/or trial and error are also used. In contrast, we introduce here the concept of optimizing representation. To illustrate this concept, the optimal representation is selected from a set of candidate representations based on an objective criterion that depends on varying amounts of information available for different parts of the structure. Specifically, an optimal representation is defined as the highest-resolution representation for which sampling is exhaustive at a precision commensurate with the precision of the representation. Thus, the method does not require an input structure and is applicable to any input information. We consider a space of representations in which a representation is a set of nonoverlapping, variable-length segments (i.e., coarse-grained beads) for each component protein sequence. We also implement a method for efficiently finding an optimal representation in our open-source Integrative Modeling Platform (IMP) software (https://integrativemodeling.org/). The approach is illustrated by application to three complexes of two subunits and a large assembly of 10 subunits. The optimized representation facilitates exhaustive sampling and thus can produce a more accurate model and a more accurate estimate of its uncertainty for larger structures than were possible previously.

Structural and mechanistic insights into human splicing factor SF3b complex derived using an integrated approach guided by the cryo-EM density maps

Pre-mRNA splicing in eukaryotes is performed by the spliceosome, a highly complex macromolecular machine. SF3b is a multi-protein complex which recognizes the branch point adenosine of pre-mRNA as part of a larger U2 snRNP or U11/U12 di-snRNP in the dynamic spliceosome machinery. Although a cryo-EM map is available for human SF3b complex, the structure and relative spatial arrangement of all components in the complex are not yet known. We have recognized folds of domains in various proteins in the assembly and generated comparative models. Using an integrative approach involving structural and other experimental data, guided by the available cryo-EM density map, we deciphered a pseudo-atomic model of the closed form of SF3b which is found to be a "fuzzy complex" with highly flexible components and multiplicity of folds. Further, the model provides structural information for 5 proteins (SF3b10, SF3b155, SF3b145, SF3b130 and SF3b14b) and localization information for 4 proteins (SF3b10, SF3b145, SF3b130 and SF3b14b) in the assembly for the first time. Integration of this model with the available U11/U12 di-snRNP cryo-EM map enabled elucidation of an open form. This now provides new insights on the mechanistic features involved in the transition between closed and open forms pivoted by a hinge region in the SF3b155 protein that also harbors cancer causing mutations. Moreover, the open form guided model of the 5' end of U12 snRNA, which includes the branch point duplex, shows that the architecture of SF3b acts as a scaffold for U12 snRNA: pre-mRNA branch point duplex formation with potential implications for branch point adenosine recognition fidelity.