Integrating diverse data for structure determination of macromolecular assemblies

Predicting ion mobility collision cross sections using projection approximation with ROSIE-PARCS webserver

Ion mobility coupled to mass spectrometry informs on the shape and size of protein structures in the form of a collision cross section (CCSIM). Although there are several computational methods for predicting CCSIM based on protein structures, including our previously developed projection approximation using rough circular shapes (PARCS), the process usually requires prior experience with the command-line interface. To overcome this challenge, here we present a web application on the Rosetta Online Server that Includes Everyone (ROSIE) webserver to predict CCSIM from protein structure using projection approximation with PARCS. In this web interface, the user is only required to provide one or more PDB files as input. Results from our case studies suggest that CCSIM predictions (with ROSIE-PARCS) are highly accurate with an average error of 6.12%. Furthermore, the absolute difference between CCSIM and CCSPARCS can help in distinguishing accurate from inaccurate AlphaFold2 protein structure predictions. ROSIE-PARCS is designed with a user-friendly interface, is available publicly and is free to use. The ROSIE-PARCS web interface is supported by all major web browsers and can be accessed via this link (https://rosie.graylab.jhu.edu).

Mesoscience in cell biology and cancer research

Mesoscale characteristics and their interdimensional correlation are the focus of contemporary interdisciplinary research. Mesoscience is a discipline that has the potential to radically update the existing knowledge structure, which differs from the conventional unit-scale and system-scale research models, revealing a previously untouchable area for scientific research. Integrative biology research aims to dissect the complex problems of life systems by conducting comprehensive research and integrating various disciplines from all biological levels of the living organism. However, the mesoscientific issues between different research units are neglected and challenging. Mesoscale research in biology requires the integration of research theories and methods from other disciplines (mathematics, physics, engineering, and even visual imaging) to investigate theoretical and frontier questions of biological processes through experiments, computations, and modeling. We reviewed  integrative paradigms and methods for the biological mesoscale problems (focusing on oncology research) and prospected the potential of their multiple dimensions and upcoming challenges. We expect to establish an interactive and collaborative theoretical platform for further expanding the depth and width of our understanding on the nature of biology.

A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data

X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.

Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction

Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCSIM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCSIM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.

Dynamic Interactions of Post Cleaved NS2B Cofactor and NS3 Protease Identified by Integrative Structural Approaches

Diseases caused by flaviviruses such as dengue virus (DENV) and West Nile Virus (WNV), are a serious threat to public health. The flavivirus single-stranded RNA genome is translated into a polyprotein which is cleaved into three structural proteins and seven non-structural proteins by the viral and cellular proteases. Non-structural (NS) protein 3 is a multifunctional protein that has N-terminal protease and C-terminal helicase domains. The NS3 protease requires co-factor NS2B for enzymatic activity and folding. Due to its essential role in viral replication, NS2B-NS3 protease is an attractive target for antiviral drugs. Despite the availability of crystal structures, dynamic interactions of the N- and C-termini of NS2B co-factor have been elusive due to their flexible fold. In this study, we employ integrative structural approaches combined with biochemical assays to elucidate the dynamic interactions of the flexible DENV4 NS2B and NS3 N- and C-termini. We captured the crystal structure of self-cleaved DENV4 NS2B₄₇NS3 protease in post cleavage state. The intermediate conformation adopted in the reported structure can be targeted by allosteric inhibitors. Comparison of our new findings from DENV4 against previously studied ZIKV NS2B-NS3 proteins reveals differences in NS2B-NS3 function between the two viruses. No inhibition of protease activity was observed for unlinked DENV NS2B-NS3 in presence of the cleavage site while ZIKV NS2B-NS3 cleavage inhibits protease activity. Another difference is that binding of the NS2B C-terminus to DENV4 eNS2B₄₇NS3Pro active site is mediated via interactions with P4-P6 residues while for ZIKV, the binding of NS2B C-terminus to active site is mediated by P1-P3 residues. The mapping of NS2B N- and C-termini with NS3 indicates that these intermolecular interactions occur mainly on the beta-barrel 2 of the NS3 protease domain. Our integrative approach enables a comprehensive understanding of the folding and dynamic interactions of DENV NS3 protease and its cofactor NS2B.

Cryo-EM of the injectisome and type III secretion systems

Double-membrane-spanning protein complexes, such as the T3SS, had long presented an intractable challenge for structural biology. As a consequence, until a few years ago, our molecular understanding of this fascinating complex was limited to composite models, consisting of structures of isolated domains, positioned within the overall complex. Most of the membrane-embedded components remained completely uncharacterized. In recent years, the emergence of cryo-electron microscopy (cryo-EM) as a method for determining protein structures to high resolution, has be transformative to our capacity to understand the architecture of this complex, and its mechanism of substrate transport. In this review, we summarize the recent structures of the various T3SS components, determined by cryo-EM, and highlight the regions of the complex that remain to be characterized. We also discuss the recent structural insights into the mechanism of effector transport through the T3SS. Finally, we highlight some of the challenges that remain to be tackled.

Combining Electron Microscopy (EM) and Cross-Linking Mass Spectrometry (XL-MS) for Structural Characterization of Protein Complexes

Structural biology has recently witnessed the benefits of the combined use of two complementary techniques: electron microscopy (EM) and cross-linking mass spectrometry (XL-MS). EM (especially its cryogenic variant cryo-EM) has proven to be a very powerful tool for the structural determination of proteins and protein complexes, even at an atomic level. In a complementary way, XL-MS allows the precise characterization of particular interactions when residues are located in close proximity. When working from low-resolution, negative-staining images and less-defined regions of flexible domains (whose mapping is made possible by cryo-EM), XL-MS can provide critical information on specific amino acids, thus identifying interacting regions and helping to deduce the overall protein structure. The protocol described here is particularly well suited for the study of protein complexes whose intrinsically flexible or transient nature prevents their high-resolution characterization by any structural technique itself.

Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning

Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.

Native or Non-Native Protein-Protein Docking Models? Molecular Dynamics to the Rescue

Molecular docking excels at creating a plethora of potential models of protein-protein complexes. To correctly distinguish the favorable, native-like models from the remaining ones remains, however, a challenge. We assessed here if a protocol based on molecular dynamics (MD) simulations would allow distinguishing native from non-native models to complement scoring functions used in docking. To this end, the first models for 25 protein-protein complexes were generated using HADDOCK. Next, MD simulations complemented with machine learning were used to discriminate between native and non-native complexes based on a combination of metrics reporting on the stability of the initial models. Native models showed higher stability in almost all measured properties, including the key ones used for scoring in the Critical Assessment of PRedicted Interaction (CAPRI) competition, namely the positional root mean square deviations and fraction of native contacts from the initial docked model. A random forest classifier was trained, reaching a 0.85 accuracy in correctly distinguishing native from non-native complexes. Reasonably modest simulation lengths of the order of 50-100 ns are sufficient to reach this accuracy, which makes this approach applicable in practice.

Mapping the multiscale structure of biological systems

Biological systems are by nature multiscale, consisting of subsystems that factor into progressively smaller units in a deeply hierarchical structure. At any level of the hierarchy, an ever-increasing diversity of technologies can be applied to characterize the corresponding biological units and their relations, resulting in large networks of physical or functional proximities-e.g., proximities of amino acids within a protein, of proteins within a complex, or of cell types within a tissue. Here, we review general concepts and progress in using network proximity measures as a basis for creation of multiscale hierarchical maps of biological systems. We discuss the functionalization of these maps to create predictive models, including those useful in translation of genotype to phenotype, along with strategies for model visualization and challenges faced by multiscale modeling in the near future. Collectively, these approaches enable a unified hierarchical approach to biological data, with application from the molecular to the macroscopic.

Beyond history and "on a roll": The list of the most well-studied human protein structures and overall trends in the protein data bank

Of the roughly 20,000 canonical human protein sequences, as of January 20, 2021, 7,077 proteins have had their full or partial, medium- to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the protein data bank (the PDB) and why? In this paper, we list the 273 top human protein structures based on the number of their PDB entries. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trends as well as current status for protein structural biology. We briefly discuss the relationship which some of the prominent protein structures have with protein research as a whole and mention their relevance to human diseases. The top-10 soluble and membrane proteins are all well-known (most of their first structures being deposited more than 30 years ago). Overall, there is no dramatic change in recent trends in the PDB. Remarkably, the number of structure depositions has grown nearly exponentially over the last 10 or more years (with a doubling time of 7 years for proteins, obtained from any organism). Growth in human protein structures is slightly faster (at 5.9 years). The information in this paper may be informative to senior scientists but also inspire researchers who are new to protein science, providing the year 2021 snap-shot for the state of protein structural biology.

Protein Structure Modeling with MODELLER

Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized at atomic resolution using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. In the following chapter, we present an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of a similar protocol has resulted in models of useful accuracy for domains in more than half of all known protein sequences.

Methods for Molecular Modelling of Protein Complexes

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular 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.

Genetic interaction mapping informs integrative structure determination of protein complexes

Determining structures of protein complexes is crucial for understanding cellular functions. Here, we describe an integrative structure determination approach that relies on in vivo measurements of genetic interactions. We construct phenotypic profiles for point mutations crossed against gene deletions or exposed to environmental perturbations, followed by converting similarities between two profiles into an upper bound on the distance between the mutated residues. We determine the structure of the yeast histone H3-H4 complex based on ~500,000 genetic interactions of 350 mutants. We then apply the method to subunits Rpb1-Rpb2 of yeast RNA polymerase II and subunits RpoB-RpoC of bacterial RNA polymerase. The accuracy is comparable to that based on chemical cross-links; using restraints from both genetic interactions and cross-links further improves model accuracy and precision. The approach provides an efficient means to augment integrative structure determination with in vivo observations.

Art and Science of the Cellular Mesoscale

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.

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.

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.

DR-SIP: protocols for higher order structure modeling with distance restraints- and cyclic symmetry-imposed packing

MOTIVATION

Quaternary structure determination for transmembrane/soluble proteins requires a reliable computational protocol that leverages observed distance restraints and/or cyclic symmetry (Cn symmetry) found in most homo-oligomeric transmembrane proteins.

RESULTS

We survey 118 X-ray crystallographically solved structures of homo-oligomeric transmembrane proteins (HoTPs) and find that ∼97% are Cn symmetric. Given the prevalence of Cn symmetric HoTPs and the benefits of incorporating geometry restraints in aiding quaternary structure determination, we introduce two new filters, the distance-restraints (DR) and the Symmetry-Imposed Packing (SIP) filters. SIP relies on a new method that can rebuild the closest ideal Cn symmetric complex from docking poses containing a homo-dimer without prior knowledge of the number (n) of monomers. Using only the geometrical filter, SIP, near-native poses of 7 HoTPs in their monomeric states can be correctly identified in the top-10 for 71% of all cases, or 29% among 31 HoTP structures obtained through homology modeling, while ZDOCK alone returns 14 and 3%, respectively. When the n is given, the optional n-mer filter is applied with SIP and returns the near-native poses for 76% of the test set within the top-10, outperforming M-ZDOCK's 55% and Sam's 47%. While applying only SIP to three HoTPs that comes with distance restraints, we found the near-native poses were ranked 1st, 1st and 10th among 54 000 possible decoys. The results are further improved to 1st, 1st and 3rd when both DR and SIP filters are used. By applying only DR, a soluble system with distance restraints is recovered at the 1st-ranked pose.

AVAILABILITY AND IMPLEMENTATION

https://github.com/capslockwizard/drsip.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Native Mass Spectrometry Analysis of Affinity-Captured Endogenous Yeast RNA Exosome Complexes

Native mass spectrometry (MS) enables direct mass measurement of intact protein assemblies generating relevant subunit composition and stoichiometry information. Combined with cross-linking and structural data, native MS-derived information is crucial for elucidating the architecture of macromolecular assemblies by integrative structural methods. The exosome complex from budding yeast was among the first endogenous protein complexes to be affinity isolated and subsequently characterized by this technique, providing improved understanding of its composition and structure. We present a protocol that couples efficient affinity capture of yeast exosome complexes and sensitive native MS analysis, including rapid affinity isolation of the endogenous exosome complex from cryolysed yeast cells, elution in nondenaturing conditions by protease cleavage, depletion of the protease, buffer exchange, and native MS measurements using an Orbitrap-based instrument (Exactive Plus EMR).

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.

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.

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.

Mycobacterium tuberculosis nucleoside diphosphate kinase shows interaction with putative ATP binding cassette (ABC) transporter, Rv1273c

Protein-protein interactions are crucial for all biological processes. Compiling this network provides many new insights into protein function and gives directions for the development of new drugs targeted to the pathogen. Mycobacterium tuberculosis Nucleoside diphosphate kinase (Mtb Ndk) has been reported to promote survival of mycobacterium within the macrophage and contribute significantly to mycobacterium virulence. Hence, the present study was aimed to identify and characterize the interacting partner for Ndk. The in vitro experiments, pull down and far western blotting have demonstrated that Mtb Ndk interacts with Rv1273c, a probable drug ABC transporter ATP-binding protein annotated to export drugs across the membrane. This observation was further confirmed by molecular docking and dynamic simulations studies. The homology model of Rv1273c was constructed and docked with Mtb Ndk for protein-protein interaction analysis. The critical residues involved at interface of Rv1273c-Ndk interaction were identified. MDS and Principal Component analysis carried out for conformational feasibility and stability concluded that the complex between the two proteins is more stable as compared to apo proteins. Our findings would be expected to improve the dissection of protein-protein interaction network and significantly advance our understanding of tuberculosis infection.Communicated by Ramaswamy H. Sarma.

Structures of Type III Secretion System Needle Filaments

Among the Gram-negative bacterial secretion systems, type III secretion systems (T3SS) possess a unique extracellular molecular apparatus called the needle. This macromolecular protein assembly is a nanometre-size filament formed by the helical arrangement of hundreds of copies of a single, small protein, which is highly conserved between T3SSs from animal to plant bacterial pathogens. The needle filament forms a hollow tube with a channel ~20 Å in diameter that serves as a conduit for proteins secreted into the targeted host cell. In the past ten years, technical breakthroughs in biophysical techniques such as cryo-electron microscopy (cryo-EM) and solid-state NMR (SSNMR) spectroscopy have uncovered atomic resolution details about the T3SS needle assembly. Several high-resolution structures of Salmonella typhimurium and Shigella flexneri T3SS needles have been reported demonstrating a common structural fold. These structural models have been used to explain the active role of the needle in transmitting the host-cell contact signal from the tip to the base of the T3SS through conformational changes as well as during the injection of effector proteins. In this chapter, we summarize the current knowledge about the structure and the role of the T3SS needle during T3SS assembly and effector secretion.

From Atoms to Cells: Using Mesoscale Landscapes to Construct Visual Narratives

Modeling and visualization of the cellular mesoscale, bridging the nanometer scale of molecules to the micrometer scale of cells, is being studied by an integrative approach. Data from structural biology, proteomics, and microscopy are combined to simulate the molecular structure of living cells. These cellular landscapes are used as research tools for hypothesis generation and testing, and to present visual narratives of the cellular context of molecular biology for dissemination, education, and outreach.

Challenges and guidelines toward 4D nucleome data and model standards

Due to recent advances in experimental and theoretical approaches, the dynamic three-dimensional organization (3D) of the nucleus has become a very active area of research in life sciences. We now understand that the linear genome is folded in ways that may modulate how genes are expressed during the basic functioning of cells. Importantly, it is now possible to build 3D models of how the genome folds within the nucleus and changes over time (4D). Because genome folding influences its function, this opens exciting new possibilities to broaden our understanding of the mechanisms that determine cell fate. However, the rapid evolution of methods and the increasing complexity of data can result in ambiguity and reproducibility challenges, which may hamper the progress of this field. Here, we describe such challenges ahead and provide guidelines to think about strategies for shared standardized validation of experimental 4D nucleome data sets and models.

Integrating Cross-Linking Experiments with Ab Initio Protein-Protein Docking

Ab initio protein-protein docking algorithms often rely on experimental data to identify the most likely complex structure. We integrated protein-protein docking with the experimental data of chemical cross-linking followed by mass spectrometry. We tested our approach using 19 cases that resulted from an exhaustive search of the Protein Data Bank for protein complexes with cross-links identified in our experiments. We implemented cross-links as constraints based on Euclidean distance or void-volume distance. For most test cases, the rank of the top-scoring near-native prediction was improved by at least twofold compared with docking without the cross-link information, and the success rate for the top 5 predictions nearly tripled. Our results demonstrate the delicate balance between retaining correct predictions and eliminating false positives. Several test cases had multiple components with distinct interfaces, and we present an approach for assigning cross-links to the interfaces. Employing the symmetry information for these cases further improved the performance of complex structure prediction.

Development of a Prototype System for Archiving Integrative/Hybrid Structure Models of Biological Macromolecules

Essential processes in biology are carried out by large macromolecular assemblies, whose structures are often difficult to determine by traditional methods. Increasingly, researchers combine measured data and computed information from several complementary methods to obtain "hybrid" or "integrative" structural models of macromolecules and their assemblies. These integrative/hybrid (I/H) models are not archived in the PDB because of the absence of standard data representations and processing mechanisms. Here we present the development of data standards and a prototype system for archiving I/H models. The data standards provide the definitions required for representing I/H models that span multiple spatiotemporal scales and conformational states, as well as spatial restraints derived from different experimental techniques. Based on these data definitions, we have built a prototype system called PDB-Dev, which provides the infrastructure necessary to archive I/H structural models. PDB-Dev is now accepting structures and is open to the community for new submissions.

Integrative structure and functional anatomy of a nuclear pore complex

Despite the central role of Nuclear Pore Complexes (NPCs) as gatekeepers of RNA and protein transport between the cytoplasm and nucleoplasm, their large size and dynamic nature have impeded a full structural and functional elucidation. Here, we have determined a subnanometer precision structure for the entire 552-protein yeast NPC by satisfying diverse data including stoichiometry, a cryo-electron tomography map, and chemical cross-links. The structure reveals the NPC’s functional elements in unprecedented detail. The NPC is built of sturdy diagonal columns to which are attached connector cables, imbuing both strength and flexibility, while tying together all other elements of the NPC, including membrane-interacting regions and RNA processing platforms. Inwardly-directed anchors create a high density of transport factor-docking Phe-Gly repeats in the central channel, organized in distinct functional units. Taken together, this integrative structure allows us to rationalize the architecture, transport mechanism, and evolutionary origins of the NPC.

Structures of Dynamic Protein Complexes: Hybrid Techniques to Study MAP Kinase Complexes and the ESCRT System

The integration of complementary molecular methods (including X-ray crystallography, NMR spectroscopy, small angle X-ray/neutron scattering, and computational techniques) is frequently required to obtain a comprehensive understanding of dynamic macromolecular complexes. In particular, these techniques are critical for studying intrinsically disordered protein regions (IDRs) or intrinsically disordered proteins (IDPs) that are part of large protein:protein complexes. Here, we explain how to prepare IDP samples suitable for study using NMR spectroscopy, and describe a novel SAXS modeling method (ensemble refinement of SAXS; EROS) that integrates the results from complementary methods, including crystal structures and NMR chemical shift perturbations, among others, to accurately model SAXS data and describe ensemble structures of dynamic macromolecular complexes.

Rigid-Body Fitting of Atomic Models on 3D Density Maps of Electron Microscopy

Cryo electron microscopy has revolutionarily evolved for the determination of the 3D structure of macromolecular complexes. The modeling procedures on the 3D density maps of electron microscopy are roughly classified into three categories: fitting, de novo modeling and refinement. The registered atomic models from the maps have mostly been hand-built and auto-refined. Several programs aiming at automatic modeling have also been developed using various kinds of molecular representations. Among these three classes of the modeling procedures, the rigid body fitting is reviewed here, because it is the most basic modeling process applied before the other steps. The fitting problems are classified as the fittings of single subunit or multiple subunits, and the fittings on global or local parts of maps. A higher resolution map enables more local fitting. Various molecular representations have been employed in the fitting programs. A point and digital image models are generally used to represent molecules, but new representations, such as the Gaussian mixture model, have been applied recently.

RAZA: A Rapid 3D z-crossings algorithm to segment electron tomograms and extract organelles and macromolecules

Resolving the 3D architecture of cells to atomic resolution is one of the most ambitious challenges of cellular and structural biology. Central to this process is the ability to automate tomogram segmentation to identify sub-cellular components, facilitate molecular docking and annotate detected objects with associated metadata. Here we demonstrate that RAZA (Rapid 3D z-crossings algorithm) provides a robust, accurate, intuitive, fast, and generally applicable segmentation algorithm capable of detecting organelles, membranes, macromolecular assemblies and extrinsic membrane protein domains. RAZA defines each continuous contour within a tomogram as a discrete object and extracts a set of 3D structural fingerprints (major, middle and minor axes, surface area and volume), enabling selective, semi-automated segmentation and object extraction. RAZA takes advantage of the fact that the underlying algorithm is a true 3D edge detector, allowing the axes of a detected object to be defined, independent of its random orientation within a cellular tomogram. The selectivity of object segmentation and extraction can be controlled by specifying a user-defined detection tolerance threshold for each fingerprint parameter, within which segmented objects must fall and/or by altering the number of search parameters, to define morphologically similar structures. We demonstrate the capability of RAZA to selectively extract subgroups of organelles (mitochondria) and macromolecular assemblies (ribosomes) from cellular tomograms. Furthermore, the ability of RAZA to define objects and their contours, provides a basis for molecular docking and rapid tomogram annotation.

Integrative structure modeling with the Integrative Modeling Platform

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use.

Iterative Molecular Dynamics-Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities

Knowing atomistic details of proteins is essential not only for the understanding of protein function but also for the development of drugs. Experimental methods such as X-ray crystallography, NMR, and cryo-electron microscopy (cryo-EM) are the preferred forms of protein structure determination and have achieved great success over the most recent decades. Computational methods may be an alternative when experimental techniques fail. However, computational methods are severely limited when it comes to predicting larger macromolecule structures with little sequence similarity to known structures. The incorporation of experimental restraints in computational methods is becoming increasingly important to more reliably predict protein structure. One such experimental input used in structure prediction and refinement is cryo-EM densities. Recent advances in cryo-EM have arguably revolutionized the field of structural biology. Our previously developed cryo-EM-guided Rosetta-MD protocol has shown great promise in the refinement of soluble protein structures. In this study, we extended cryo-EM density-guided iterative Rosetta-MD to membrane proteins. We also improved the methodology in general by picking models based on a combination of their score and fit-to-density during the Rosetta model selection. By doing so, we have been able to pick models superior to those with the previous selection based on Rosetta score only and we have been able to further improve our previously refined models of soluble proteins. The method was tested with five membrane spanning protein structures. By applying density-guided Rosetta-MD iteratively we were able to refine the predicted structures of these membrane proteins to atomic resolutions. We also showed that the resolution of the density maps determines the improvement and quality of the refined models. By incorporating high-resolution density maps (∼4 Å), we were able to more significantly improve the quality of the models than when medium-resolution maps (6.9 Å) were used. Beginning from an average starting structure root mean square deviation (RMSD) to native of 4.66 Å, our protocol was able to refine the structures to bring the average refined structure RMSD to 1.66 Å when 4 Å density maps were used. The protocol also successfully refined the HIV-1 CTD guided by an experimental 5 Å density map.

Strategies and perspectives of assembling multi-enzyme systems

Multi-enzyme complexes have the potential to achieve high catalytic efficiency for sequence reactions due to their advantages in eliminating product inhibition, facilitating intermediate transfer and in situ regenerating cofactors. Constructing functional multi-enzyme systems to mimic natural multi-enzyme complexes is of great interest for multi-enzymatic biosynthesis and cell-free synthetic biotransformation, but with many challenges. Currently, various assembly strategies have been developed based on the interaction of biomacromolecules such as DNA, peptide and scaffolding protein. On the other hand, chemical-induced assembly is based on the affinity of enzymes with small molecules including inhibitors, cofactors and metal ions has the advantage of simplicity, site-to-site oriented structure control and economy. This review summarizes advances and progresses employing these strategies. Furthermore, challenges and perspectives in designing multi-enzyme systems are highlighted.

Towards an efficient compression of 3D coordinates of macromolecular structures

The size and complexity of 3D macromolecular structures available in the Protein Data Bank is constantly growing. Current tools and file formats have reached limits of scalability. New compression approaches are required to support the visualization of large molecular complexes and enable new and scalable means for data analysis. We evaluated a series of compression techniques for coordinates of 3D macromolecular structures and identified the best performing approaches. By balancing compression efficiency in terms of the decompression speed and compression ratio, and code complexity, our results provide the foundation for a novel standard to represent macromolecular coordinates in a compact and useful file format.

Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase

The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helix–helix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.

Protein Structure Modeling with MODELLER

Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized at atomic resolution using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. In the following chapter, we present an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of a similar protocol has resulted in models of useful accuracy for domains in more than half of all known protein sequences.