Outcome of a workshop on archiving structural models of biological macromolecules

Avian influenza A H5N1 hemagglutinin protein models have distinct structural patterns re-occurring across the 1959-2023 strains

Influenza A H5N1 hemagglutinin (HA) plays a crucial role in viral pathogenesis and changes in the HA receptor binding domain (RBD) have been attributed to alterations in viral pathogenesis. Mutations often occur within the HA which in-turn results in HA structural changes that consequently contribute to protein evolution. However, the possible occurrence of mutations that results to reversion of the HA protein (going back to an ancestral protein conformation) which in-turn creates distinct HA structural patterns across the 1959-2023 H5N1 viral evolution has never been investigated. Here, we generated and verified the quality of the HA models, identified similar HA structural patterns, and elucidated the possible variations in HA RBD structural dynamics. Our results show that there are 7 distinct structural patterns occurring among the 1959-2023 H5N1 HA models which suggests that reversion of the HA protein putatively occurs during viral evolution. Similarly, we found that the HA RBD structural dynamics vary among the 7 distinct structural patterns possibly affecting viral pathogenesis.

ModelCIF: An Extension of PDBx/mmCIF Data Representation for Computed Structure Models

ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery of Findable, Accessible, Interoperable, and Reusable (FAIR) data to users worldwide. ModelCIF describes the specific set of attributes and metadata associated with macromolecular structures modeled by solely computational methods and provides an extensible data representation for deposition, archiving, and public dissemination of predicted three-dimensional (3D) models of macromolecules. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined 3D structures of macromolecules and associated metadata. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described.

Network analysis of the autophagy biochemical network in relation to various autophagy-targeted proteins found among SARS-CoV-2 variants of concern

Autophagy is an important cellular process that triggers a coordinated action involving multiple individual proteins and protein complexes while SARS-CoV-2 (SARS2) was found to both hinder autophagy to evade host defense and utilize autophagy for viral replication. Interestingly, the possible significant stages of the autophagy biochemical network in relation to the corresponding autophagy-targeted SARS2 proteins from the different variants of concern (VOC) were never established. In this study, we performed the following: autophagy biochemical network design and centrality analyses; generated autophagy-targeted SARS2 protein models; and superimposed protein models for structural comparison. We identified 2 significant biochemical pathways (one starts from the ULK complex and the other starts from the PI3P complex) within the autophagy biochemical network. Similarly, we determined that the autophagy-targeted SARS2 proteins (Nsp15, M, ORF7a, ORF3a, and E) are structurally conserved throughout the different SARS2 VOC suggesting that the function of each protein is preserved during SARS2 evolution. Interestingly, among the autophagy-targeted SARS2 proteins, the M protein coincides with the 2 significant biochemical pathways we identified within the autophagy biochemical network. In this regard, we propose that the SARS2 M protein is the main determinant that would influence autophagy outcome in regard to SARS2 infection.

Structural Insights on the SARS-CoV-2 Variants of Concern Spike Glycoprotein: A Computational Study With Possible Clinical Implications

Coronavirus disease 2019 (COVID-19) pandemic has been attributed to SARS-CoV-2 (SARS2) and, consequently, SARS2 has evolved into multiple SARS2 variants driving subsequent waves of infections. In particular, variants of concern (VOC) were identified to have both increased transmissibility and virulence ascribable to mutational changes occurring within the spike protein resulting to modifications in the protein structural orientation which in-turn may affect viral pathogenesis. However, this was never fully elucidated. Here, we generated spike models of endemic HCoVs (HCoV 229E, HCoV OC43, HCoV NL63, HCoV HKU1, SARS CoV, MERS CoV), original SARS2, and VOC (alpha, beta, gamma, delta). Model quality check, structural superimposition, and structural comparison based on RMSD values, TM scores, and contact mapping were all performed. We found that: 1) structural comparison between the original SARS2 and VOC whole spike protein model have minor structural differences (TM > 0.98); 2) the whole VOC spike models putatively have higher structural similarity (TM > 0.70) to spike models from endemic HCoVs coming from the same phylogenetic cluster; 3) original SARS2 S1-CTD and S1-NTD models are structurally comparable to VOC S1-CTD (TM = 1.0) and S1-NTD (TM > 0.96); and 4) endemic HCoV S1-CTD and S1-NTD models are structurally comparable to VOC S1-CTD (TM > 0.70) and S1-NTD (TM > 0.70) models belonging to the same phylogenetic cluster. Overall, we propose that structural similarities (possibly ascribable to similar conformational epitopes) may help determine immune cross-reactivity, whereas, structural differences (possibly associated with varying conformational epitopes) may lead to viral infection (either reinfection or breakthrough infection).

Insights on the Structural Variations of the Furin-Like Cleavage Site Found Among the December 2019-July 2020 SARS-CoV-2 Spike Glycoprotein: A Computational Study Linking Viral Evolution and Infection

The SARS-CoV-2 (SARS2) is the cause of the coronavirus disease 2019 (COVID-19) pandemic. One unique structural feature of the SARS2 spike protein is the presence of a furin-like cleavage site (FLC) which is associated with both viral pathogenesis and host tropism. Specifically, SARS2 spike protein binds to the host ACE-2 receptor which in-turn is cleaved by furin proteases at the FLC site, suggesting that SARS2 FLC structural variations may have an impact on viral infectivity. However, this has not yet been fully elucidated. This study designed and analyzed a COVID-19 genomic epidemiology network for December 2019 to July 2020, and subsequently generated and analyzed representative SARS2 spike protein models from significant node clusters within the network. To distinguish possible structural variations, a model quality assessment was performed before further protein model analyses and superimposition of the protein models, particularly in both the receptor-binding domain (RBD) and FLC. Mutant spike models were generated with the unique ⁶⁸¹PRRA⁶⁸⁴ amino acid sequence found within the deleted FLC. We found 9 SARS2 FLC structural patterns that could potentially correspond to nine node clusters encompassing various countries found within the COVID-19 genomic epidemiology network. Similarly, we associated this with the rapid evolution of the SARS2 genome. Furthermore, we observed that either in the presence or absence of the unique ⁶⁸¹PRRA⁶⁸⁴ amino acid sequence no structural changes occurred within the SARS2 RBD, which we believe would mean that the SARS2 FLC has no structural influence on SARS2 RBD and may explain why host tropism was maintained.

Structural Comparison of the SARS CoV 2 Spike Protein Relative to Other Human-Infecting Coronaviruses

Coronaviruses (CoV) are enveloped positive-stranded RNA viruses and, historically, there are seven known human-infecting CoVs with varying degrees of virulence. CoV attachment to the host is the first step of viral pathogenesis and mainly relies on the spike glycoprotein located on the viral surface. Among the human-infecting CoVs, only the infection of SARS CoV 2 (SARS2) among humans resulted to a pandemic which would suggest that the protein structural conformation of SARS2 spike protein is distinct as compared to other human-infecting CoVs. Surprisingly, the possible differences and similarities in the protein structural conformation between the various human-infecting CoV spike proteins have not been fully elucidated. In this study, we utilized a computational approach to generate models and analyze the seven human-infecting CoV spike proteins, namely: HCoV 229E, HCoV OC43, HCoV NL63, HCoV HKU1, SARS CoV, MERS CoV, and SARS2. Model quality assessment of all CoV models generated, structural superimposition of the whole protein model and selected S1 domains (S1-CTD and S1-NTD), and structural comparison based on RMSD values, Tm scores, and contact mapping were all performed. We found that the structural orientation of S1-CTD is a potential structural feature associated to both the CoV phylogenetic cluster and lineage. Moreover, we observed that spike models in the same phylogenetic cluster or lineage could potentially have similar protein structure. Additionally, we established that there are potentially three distinct S1-CTD orientation (Pattern I, Pattern II, Pattern III) among the human-infecting CoVs. Furthermore, we postulate that human-infecting CoVs in the same phylogenetic cluster may have similar S1-CTD and S1-NTD structural orientation. Taken together, we propose that the SARS2 spike S1-CTD follows a Pattern III orientation which has a higher degree of similarity with SARS1 and some degree of similarity with both OC43 and HKU1 which coincidentally are in the same phylogenetic cluster and lineage, whereas, the SARS2 spike S1-NTD has some degree of similarity among human-infecting CoVs that are either in the same phylogenetic cluster or lineage.

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).

Toward Increased Reliability, Transparency, and Accessibility in Cross-linking Mass Spectrometry

Cross-linking mass spectrometry (MS) has substantially matured as a method over the past 2 decades through parallel development in multiple labs, demonstrating its applicability to protein structure determination, conformation analysis, and mapping protein interactions in complex mixtures. Cross-linking MS has become a much-appreciated and routinely applied tool, especially in structural biology. Therefore, it is timely that the community commits to the development of methodological and reporting standards. This white paper builds on an open process comprising a number of events at community conferences since 2015 and identifies aspects of Cross-linking MS for which guidelines should be developed as part of a Cross-linking MS standards initiative.

Structural insights into the potential changes in receptor binding site found in the 1998-2018 influenza B/Yamagata hemagglutinin: A putative correlation between receptor binding site structural variability and seasonal infection

Influenza B virus has two distinct lineages (Victoria and Yamagata) and are associated with seasonal influenza epidemics that cause respiratory illness. Influenza B hemagglutinin (HA) is a major surface glycoprotein with the receptor-binding site (RBS) primarily involved in viral pathogenesis. Generally, influenza B exclusively infects the human population which would insinuate that the structural variability of the influenza B HA RBS rarely changes. However, to our knowledge, the potential impact of variations in the influenza B HA RBS structural variability was not fully elucidated. Throughout this study, we generated models from the transitioning (evolving viral lineage) 1998-2018 influenza B/Yamagata HA, verified the quality of each HA model, performed HA RBS structural variability measurements, superimposed varying HA models for comparison, and designed a phylogenetic tree network for further analyses. We found that measurements of the transitioning HA RBS structural variability were generally maintained and, similarly, measurements of the altered (years that differed from the evolving viral lineage, specifically 2003, 2007, 2017) HA RBS structural variability differed from the transitioning HA RBS. Moreover, we observed that the altered HA RBS structural variability favored the formation of a putative Y202-H191 hydrogen bond which we postulate may increase structural stability, thereby, allowing for a winter infection of the virus. Furthermore, we established that changes in HA RBS structural variability does not influence viral evolution, but putatively seasonal infection.

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.

ETDB-Caltech: A blockchain-based distributed public database for electron tomography

Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets.

Structural significance of residues 158-160 in the H3N2 hemagglutnin globular head: A computational study with implications in viral evolution and infection

Influenza A H3N2 has been linked to annual outbreaks within the human population attributable to continuous structural changes. H3N2 HA contains well identified antigenic sites and receptor-binding sites (RBS) that are possibly correlated to viral evolution and infection. However, the structural significance of amino acid residues associated with both viral evolution and infection were not fully demonstrated. Throughout this study, we generated and analyzed H3N2 HA models that represented the clade 3C.2 population (comprised of clades 3C.2, 3C.2a, and 3C.21 from the transitioning 2014-2018 H3N2 strains) and 3C.3a (from the 2016 H3N2 strain). Model quality estimation, structural analyses and superimposition, and network analytics of H3N2 HA1 evolution were performed. We found that the structural properties of residues 158-160 could influence the overall HA backbone. More specifically, amino acid substitutions at residues 159-160 affected the amino acid orientation at residue 158, thereby, causing the overall HA backbone structure to vary. Our results were consistent with 1968-2018 HA1 evolution. Taken together, we propose that our results would highlight the structural significance of residues 158-160 in HA1 for both antigenic drift and RBS.

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.

Structural comparison among the 2013-2017 avian influenza A H5N6 hemagglutinin proteins: A computational study with epidemiological implications

Avian influenza viruses easily spread allowing viral re-assortment to simply occur which in-turn increases the potential for a pandemic. A novel 2013 H5N6 influenza strain was detected among the avian population and was reported to continuously evolve, however, this was never structurally demonstrated. Here, we elucidated the putative structural evolution of the novel H5N6 influenza strain. Throughout this study, we analyzed 2013-2017 H5N6 HA protein models. Model quality was first verified before further analyses and structural comparison was made using superimposition. We found that Leu was inserted at position 129₁ among the 2013-2015 models while Leu was not inserted among the 2016-2017 models. Moreover, presence of Leu at position 129₁ shifts residue E126₁ by 159.6° affecting nearby residues which may explain the difference between the 2013-2015 and 2016-2017 HA structural groups. Similarly, we believe that our results would support the hypothesis that the current H5N6 strain is still continuously evolving.

A data-driven structural model of hSSB1 (NABP2/OBFC2B) self-oligomerization

The maintenance of genome stability depends on the ability of the cell to repair DNA efficiently. Single-stranded DNA binding proteins (SSBs) play an important role in DNA processing events such as replication, recombination and repair. While the role of human single-stranded DNA binding protein 1 (hSSB1/NABP2/OBFC2B) in the repair of double-stranded breaks has been well established, we have recently shown that it is also essential for the base excision repair (BER) pathway following oxidative DNA damage. However, unlike in DSB repair, the formation of stable hSSB1 oligomers under oxidizing conditions is an important prerequisite for its proper function in BER. In this study, we have used solution-state NMR in combination with biophysical and functional experiments to obtain a structural model of hSSB1 self-oligomerization. We reveal that hSSB1 forms a tetramer that is structurally similar to the SSB from Escherichia coli and is stabilized by two cysteines (C81 and C99) as well as a subset of charged and hydrophobic residues. Our structural and functional data also show that hSSB1 oligomerization does not preclude its function in DSB repair, where it can interact with Ints3, a component of the SOSS1 complex, further establishing the versatility that hSSB1 displays in maintaining genome integrity.

Protein Data Bank (PDB): The Single Global Macromolecular Structure Archive

The Protein Data Bank (PDB)--the single global repository of experimentally determined 3D structures of biological macromolecules and their complexes--was established in 1971, becoming the first open-access digital resource in the biological sciences. The PDB archive currently houses ~130,000 entries (May 2017). It is managed by the Worldwide Protein Data Bank organization (wwPDB; wwpdb.org), which includes the RCSB Protein Data Bank (RCSB PDB; rcsb.org), the Protein Data Bank Japan (PDBj; pdbj.org), the Protein Data Bank in Europe (PDBe; pdbe.org), and BioMagResBank (BMRB; www.bmrb.wisc.edu). The four wwPDB partners operate a unified global software system that enforces community-agreed data standards and supports data Deposition, Biocuration, and Validation of ~11,000 new PDB entries annually (deposit.wwpdb.org). The RCSB PDB currently acts as the archive keeper, ensuring disaster recovery of PDB data and coordinating weekly updates. wwPDB partners disseminate the same archival data from multiple FTP sites, while operating complementary websites that provide their own views of PDB data with selected value-added information and links to related data resources. At present, the PDB archives experimental data, associated metadata, and 3D-atomic level structural models derived from three well-established methods: crystallography, nuclear magnetic resonance spectroscopy (NMR), and electron microscopy (3DEM). wwPDB partners are working closely with experts in related experimental areas (small-angle scattering, chemical cross-linking/mass spectrometry, Forster energy resonance transfer or FRET, etc.) to establish a federation of data resources that will support sustainable archiving and validation of 3D structural models and experimental data derived from integrative or hybrid methods.

The SWISS-MODEL Repository-new features and functionality

SWISS-MODEL Repository (SMR) is a database of annotated 3D protein structure models generated by the automated SWISS-MODEL homology modeling pipeline. It currently holds >400 000 high quality models covering almost 20% of Swiss-Prot/UniProtKB entries. In this manuscript, we provide an update of features and functionalities which have been implemented recently. We address improvements in target coverage, model quality estimates, functional annotations and improved in-page visualization. We also introduce a new update concept which includes regular updates of an expanded set of core organism models and UniProtKB-based targets, complemented by user-driven on-demand update of individual models. With the new release of the modeling pipeline, SMR has implemented a REST-API and adopted an open licencing model for accessing model coordinates, thus enabling bulk download for groups of targets fostering re-use of models in other contexts. SMR can be accessed at https://swissmodel.expasy.org/repository.

A public database of macromolecular diffraction experiments

The low reproducibility of published experimental results in many scientific disciplines has recently garnered negative attention in scientific journals and the general media. Public transparency, including the availability of `raw' experimental data, will help to address growing concerns regarding scientific integrity. Macromolecular X-ray crystallography has led the way in requiring the public dissemination of atomic coordinates and a wealth of experimental data, making the field one of the most reproducible in the biological sciences. However, there remains no mandate for public disclosure of the original diffraction data. The Integrated Resource for Reproducibility in Macromolecular Crystallography (IRRMC) has been developed to archive raw data from diffraction experiments and, equally importantly, to provide related metadata. Currently, the database of our resource contains data from 2920 macromolecular diffraction experiments (5767 data sets), accounting for around 3% of all depositions in the Protein Data Bank (PDB), with their corresponding partially curated metadata. IRRMC utilizes distributed storage implemented using a federated architecture of many independent storage servers, which provides both scalability and sustainability. The resource, which is accessible via the web portal at http://www.proteindiffraction.org, can be searched using various criteria. All data are available for unrestricted access and download. The resource serves as a proof of concept and demonstrates the feasibility of archiving raw diffraction data and associated metadata from X-ray crystallographic studies of biological macromolecules. The goal is to expand this resource and include data sets that failed to yield X-ray structures in order to facilitate collaborative efforts that will improve protein structure-determination methods and to ensure the availability of `orphan' data left behind for various reasons by individual investigators and/or extinct structural genomics projects.

The archiving and dissemination of biological structure data

The global Protein Data Bank (PDB) was the first open-access digital archive in biology. The history and evolution of the PDB are described, together with the ways in which molecular structural biology data and information are collected, curated, validated, archived, and disseminated by the members of the Worldwide Protein Data Bank organization (wwPDB; http://wwpdb.org). Particular emphasis is placed on the role of community in establishing the standards and policies by which the PDB archive is managed day-to-day.

A structural analysis of DNA binding by hSSB1 (NABP2/OBFC2B) in solution

Single-stranded DNA binding proteins (SSBs) play an important role in DNA processing events such as replication, recombination and repair. Human single-stranded DNA binding protein 1 (hSSB1/NABP2/OBFC2B) contains a single oligosaccharide/oligonucleotide binding (OB) domain followed by a charged C-terminus and is structurally homologous to the SSB from the hyperthermophilic crenarchaeote Sulfolobus solfataricus. Recent work has revealed that hSSB1 is critical to homologous recombination and numerous other important biological processes such as the regulation of telomeres, the maintenance of DNA replication forks and oxidative damage repair. Since the ability of hSSB1 to directly interact with single-stranded DNA (ssDNA) is paramount for all of these processes, understanding the molecular details of ssDNA recognition is essential. In this study, we have used solution-state nuclear magnetic resonance in combination with biophysical and functional experiments to structurally analyse ssDNA binding by hSSB1. We reveal that ssDNA recognition in solution is modulated by base-stacking of four key aromatic residues within the OB domain. This DNA binding mode differs significantly from the recently determined crystal structure of the SOSS1 complex containing hSSB1 and ssDNA. Our findings elucidate the detailed molecular mechanism in solution of ssDNA binding by hSSB1, a major player in the maintenance of genomic stability.

Toolbox for Protein Structure Prediction

Protein tertiary structure prediction algorithms aim to predict, from amino acid sequence, the tertiary structure of a protein. In silico protein structure prediction methods have become extremely important, as in vitro-based structural elucidation is unable to keep pace with the current growth of sequence databases due to high-throughput next-generation sequencing, which has exacerbated the gaps in our knowledge between sequences and structures.Here we briefly discuss protein tertiary structure prediction, the biennial competition for the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and its role in shaping the field. We also discuss, in detail, our cutting-edge web-server method IntFOLD2-TS for tertiary structure prediction. Furthermore, we provide a step-by-step guide on using the IntFOLD2-TS web server, along with some real world examples, where the IntFOLD server can and has been used to improve protein tertiary structure prediction and aid in functional elucidation.

Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop

Structures of biomolecular systems are increasingly computed by integrative modeling that relies on varied types of experimental data and theoretical information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, on October 6 and 7, 2014. At the workshop, experts in various experimental fields of structural biology, experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biology. How should integrative models be represented? How should the data and integrative models be validated? What data should be archived? How should the data and models be archived? What information should accompany the publication of integrative models?

Towards understanding nuclear pore complex architecture and dynamics in the age of integrative structural analysis

Determining the functional architecture of the nuclear pore complex, that remains only partially understood, requires bridging across different length scales. Recent technological advances in quantitative and cross-linking mass spectrometry, super-resolution fluorescence microscopy and electron microscopy have enormously accelerated the integration of different types of data into coherent structural models. Moreover, high-resolution structural analysis of nucleoporins and their in vitro reconstitution into complexes is now facilitated by the use of thermostable orthologs. In this review we highlight how the application of such technologies has led to novel insights into nuclear pore architecture and to a paradigm shift. Today nuclear pores are not anymore seen as static facilitators of nucleocytoplasmic transport but ensembles of multiple overlaying functional states that are involved in various cellular processes.

Protein modeling: what happened to the "protein structure gap"?

Computational modeling of three-dimensional macromolecular structures and complexes from their sequence has been a long-standing vision in structural biology. Over the last 2 decades, a paradigm shift has occurred: starting from a large "structure knowledge gap" between the huge number of protein sequences and small number of known structures, today, some form of structural information, either experimental or template-based models, is available for the majority of amino acids encoded by common model organism genomes. With the scientific focus of interest moving toward larger macromolecular complexes and dynamic networks of interactions, the integration of computational modeling methods with low-resolution experimental techniques allows the study of large and complex molecular machines. One of the open challenges for computational modeling and prediction techniques is to convey the underlying assumptions, as well as the expected accuracy and structural variability of a specific model, which is crucial to understanding its limitations.

How community has shaped the Protein Data Bank

Following several years of community discussion, the Protein Data Bank (PDB) was established in 1971 as a public repository for the coordinates of three-dimensional models of biological macromolecules. Since then, the number, size, and complexity of structural models have continued to grow, reflecting the productivity of structural biology. Managed by the Worldwide PDB organization, the PDB has been able to meet increasing demands for the quantity of structural information and of quality. In addition to providing unrestricted access to structural information, the PDB also works to promote data standards and to raise the profile of structural biology with broader audiences. In this perspective, we describe the history of PDB and the many ways in which the community continues to shape the archive.

Recognition of Errors in the Refinement and Validation of Three-Dimensional Structures of AC1 Proteins of Begomovirus Strains by Using ProSA-Web

The structural model of begomovirus AC1 protein is useful for understanding biological function at molecular level and docking study. For this study we have used the ProSA program (Protein Structure Analysis) tool to establish the structure prediction and modeling of protein. This tool was used for refinement and validation of experimental protein structures. Potential problems of protein structures based on energy plots are easily seen by ProSA and are displayed in a three-dimensional manner. In the present study we have selected different AC1 proteins of begomovirus strains (YP_003288785, YP_002004579, and YP_003288773) for structural analysis and display of energy plots that highlight potential problems spotted in protein structures. The 3D models of Rep proteins with recognized errors can be effectively used for in silico docking study for development of potential ligand molecules against begomovirus infection.

Structural differences between the avian and human H7N9 hemagglutinin proteins are attributable to modifications in salt bridge formation: a computational study with implications in viral evolution

Influenza A hemagglutinin (HA) is a homotrimeric glycoprotein composed of a fibrous globular stem supporting a globular head containing three sialic acid binding sites responsible for infection. The H7N9 strain has consistently infected an avian host, however, the novel 2013 strain is now capable of infecting a human host which would imply that the HA in both strains structurally differ. A better understanding of the structural differences between the avian and human H7N9 strains may shed light into viral evolution and transmissibility. In this study, we elucidated the structural differences between the avian and human H7N9 strains. Throughout the study, we generated HA homology models, verified the quality of each model, superimposed HA homology models to determine structural differences, and, likewise, elucidated the probable cause for these structural differences. We detected two different types of structural differences between the novel H7N9 human and representative avian strains, wherein, one type (Pattern-1) showed three non-overlapping regions while the other type (Pattern-2) showed only one non-overlapping region. In addition, we found that superimposed HA homology models exhibiting Pattern-1 contain three non-overlapping regions designated as: Region-1 (S157₁-A160₁); Region-3 (R262₁-S265₁); and Region-4 (S270₁-D281₁), whereas, superimposed HA homology models showing Pattern-2 only contain one non-overlapping region designated as Region-2 (S137₁-S145₁). We attributed the two patterns we observed to either the presence of salt bridges involving the E114₁ residue or absence of the R141₁:D77₁ salt bridge. Interestingly, comparison between the human H7N7 and H7N9 HA homology models showed high structural similarity. We propose that the putative absence of the R141₁:D77₁ salt bridge coupled with the putative presence of the E114₁:R262₁ and E114₁:K264₁ salt bridges found in the 2013 H7N9 HA homology model is associated to human-type receptor binding. This highlights the possible significance of HA salt bridge formation modifications in viral infectivity, immune escape, transmissibility and evolution.

IGF1 mRNA splicing variants in Liaoning cashmere goat: identification, characterization, and transcriptional patterns in skin and visceral organs

Insulin-like growth factor I (IGF1) is a member of the insulin superfamily. It performs important roles in the proliferation and differentiation of skin cell and control of hair cycles and is thought to be a potential candidate gene for goat cashmere traits. In this work, we isolated and characterized three kinds of IGF1 mRNA splicing variants from the liver of Liaoning Cashmere goat, and the expression characterization of the IGF1 mRNA splicing variants were investigated in skin and other tissues of Liaoning cashmere goat. The sequencing results indicated that the classes 1w, 1, and 2 of IGF1 cDNAs in Liaoning cashmere goat, each included an open reading frame encoding the IGF1 precursor protein. The deduced amino acid sequences of the three IGF1 precursor proteins differed only in their NH2-terminal leader peptides. Through removal of the signal peptide and extension peptide, the three IGF1 mRNA splicing variants (classes 1w, 1, and 2) resulted in the same mature IGF1 protein in Liaoning cashmere goat. In skin tissue of Liaoning cashmere goat, class 1 and class 2 were detected in all stages of hair follicle cycling, and they had the highest transcription level at anagen, and then early anagen; whereas at telogen both classes 1 and 2 had the lowest expression in mRNA level, but the class 1 appears to be relatively more abundant than class 2 in skin tissue of Liaoning cashmere goat. However, the class 1w transcript was not detected in the skin tissues. Three classes of IGF1 mRNA were transcribed in a variety of tissues, including heart, brain, spleen, lung, kidney, liver, and skeletal muscle, but class 1 IGF1 mRNA was more abundant than classes 1w and 2 in the investigated tissues.

Homology modeling study toward identifying structural properties in the HA2 B-loop that would influence the HA1 receptor-binding site

Influenza hemagglutinin (HA) consists of a fibrous globular stem (HA2) inserted into the viral membrane supporting a globular head (HA1). HA1 receptor-binding has been hypothesized to be structurally correlated to the HA2 B-loop, however, this was never fully understood. Here, we elucidated the structural relationship between the HA2 B-loop and the HA1 receptor-binding site (RBS). Throughout this study, we analyzed 2486 H1N1 HA homology models obtained from human, swine and avian strains during 1976-2012. Quality of all homology models were verified before further analyses. We established that amino acid residue 882 is putatively strain-conserved and differs in the human (K882), swine (H882) and avian (N882) strains. Moreover, we observed that the amino acid at residue 882 and, similarly, its orientation has the potential to influence the HA1 RBS diameter measurements which we hypothesize may consequentially affect influenza H1N1 viral infectivity, immune escape, transmissibility, and evolution.

The Protein Model Portal

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at http://www.proteinmodelportal.org and from the PSI Structural Genomics Knowledgebase.

Outcome of a workshop on applications of protein models in biomedical research

We describe the proceedings and conclusions from the "Workshop on Applications of Protein Models in Biomedical Research" (the Workshop) that was held at the University of California, San Francisco on 11 and 12 July, 2008. At the Workshop, international scientists involved with structure modeling explored (i) how models are currently used in biomedical research, (ii) the requirements and challenges for different applications, and (iii) how the interaction between the computational and experimental research communities could be strengthened to advance the field.

Structural genomics is the largest contributor of novel structural leverage

The Protein Structural Initiative (PSI) at the US National Institutes of Health (NIH) is funding four large-scale centers for structural genomics (SG). These centers systematically target many large families without structural coverage, as well as very large families with inadequate structural coverage. Here, we report a few simple metrics that demonstrate how successfully these efforts optimize structural coverage: while the PSI-2 (2005-now) contributed more than 8% of all structures deposited into the PDB, it contributed over 20% of all novel structures (i.e. structures for protein sequences with no structural representative in the PDB on the date of deposition). The structural coverage of the protein universe represented by today’s UniProt (v12.8) has increased linearly from 1992 to 2008; structural genomics has contributed significantly to the maintenance of this growth rate. Success in increasing novel leverage (defined in Liu et al. in Nat Biotechnol 25:849–851, 2007) has resulted from systematic targeting of large families. PSI’s per structure contribution to novel leverage was over 4-fold higher than that for non-PSI structural biology efforts during the past 8 years. If the success of the PSI continues, it may just take another ~15 years to cover most sequences in the current UniProt database.

The protein structure initiative structural genomics knowledgebase

The Protein Structure Initiative Structural Genomics Knowledgebase (PSI SGKB, http://kb.psi-structuralgenomics.org) has been created to turn the products of the PSI structural genomics effort into knowledge that can be used by the biological research community to understand living systems and disease. This resource provides central access to structures in the Protein Data Bank (PDB), along with functional annotations, associated homology models, worldwide protein target tracking information, available protocols and the potential to obtain DNA materials for many of the targets. It also offers the ability to search all of the structural and methodological publications and the innovative technologies that were catalyzed by the PSI's high-throughput research efforts. In collaboration with the Nature Publishing Group, the PSI SGKB provides a research library, editorials about new research advances, news and an events calendar to present a broader view of structural biology and structural genomics. By making these resources freely available, the PSI SGKB serves as a bridge to connect the structural biology and the greater biomedical communities.

Data deposition and annotation at the worldwide protein data bank

The Protein Data Bank (PDB) is the repository for three-dimensional structures of biological macromolecules, determined by experimental methods. The data in the archive is free and easily available via the Internet from any of the worldwide centers managing this global archive. These data are used by scientists, researchers, bioinformatics specialists, educators, students, and general audiences to understand biological phenomenon at a molecular level. Analysis of this structural data also inspires and facilitates new discoveries in science. This chapter describes the tools and methods currently used for deposition, processing, and release of data in the PDB. References to future enhancements are also included.

Data deposition and annotation at the worldwide protein data bank

The Protein Data Bank (PDB) is the repository for the three-dimensional structures of biological macromolecules, determined by experimental methods. The data in the archive are free and easily available via the Internet from any of the worldwide centers managing this global archive. These data are used by scientists, researchers, bioinformatics specialists, educators, students, and lay audiences to understand biological phenomena at a molecular level. Analysis of these structural data also inspires and facilitates new discoveries in science. This chapter describes the tools and methods currently used for deposition, processing, and release of data in the PDB. References to future enhancements are also included.

Using the tools and resources of the RCSB protein data bank

The Protein Data Bank (PDB; http://www.pdb.org) is the world-wide repository for three-dimensional structural data determined using various experimental methods. The options and procedures for searching and downloading structural data from the Research Collaboratory for Structural Bioinformatics (RCSB) PDB are described here, along with tools for assessing the quality of structures. Several types of information are associated with each structure deposition, including atomic coordinates of the structure, experimental data used to solve it, sequences of all macromolecules in the structures, details about the structure solution method, images showing different views of the structure, derived geometric data, and a variety of links to other resources. These data and resources may be used for understanding the function and stability of the molecule and for designing biochemical, genetic, or other experiments. They can also be used for molecular modeling and drug design.

Dissecting the structural determinants of the interaction between the human cytomegalovirus UL18 protein and the CD85j immune receptor

UL18 is a glycoprotein encoded by the human cytomegalovirus genome and is thought to play a pivotal role during human cytomegalovirus infection, although its exact function is still a matter of debate. UL18 shares structural similarity with MHC class I and binds the receptor CD85j on immune cells. Besides UL18, CD85j binds MHC class I molecules. The binding properties of CD85j to MHC class I molecules have been thoroughly studied. Conversely, very little information is available on the CD85j/UL18 complex, namely that UL18 binds CD85j through its alpha3 domain with an affinity that is approximately 1000-fold higher than the MHC class I affinity for CD85j. Deeper knowledge of features of the UL18/CD85j complex would help to disclose the function of UL18 when it binds to CD85j. In this study we first demonstrated that the UL18alpha3 domain is not sufficient per se for binding and that beta2-microglobulin is necessary for UL18-CD85j interaction. We then dissected structural determinants of binding UL18 to CD85j. To this end, we constructed a three-dimensional model of the complex. The model was used to design mutants in selected regions of the putative interaction interface, the effects of which were measured on binding. Six regions in both the alpha2 and alpha3 domains and specific amino acids within them were identified that are potentially involved in the UL18-CD85j interaction. The higher affinity of UL18 to CD85j, compared with MHC class I, seems to be due not to additional interaction regions but to an overall better fit of the two molecules.

Thermodynamics of natural selection I: Energy flow and the limits on organization

This is the first of three papers analyzing the representation of information in the biosphere, and the energetic constraints limiting the imposition or maintenance of that information. Biological information is inherently a chemical property, but is equally an aspect of control flow and a result of processes equivalent to computation. The current paper develops the constraints on a theory of biological information capable of incorporating these three characterizations and their quantitative consequences. The paper illustrates the need for a theory linking energy and information by considering the problem of existence and reslience of the biosphere, and presents empirical evidence from growth and development at the organismal level suggesting that the theory developed will capture relevant constraints on real systems. The main result of the paper is that the limits on the minimal energetic cost of information flow will be tractable and universal whereas the assembly of more literal process models into a system-level description often is not. The second paper in the series then goes on to construct reversible models of energy and information flow in chemistry which achieve the idealized limits, and the third paper relates these to fundamental operations of computation.

On the structural convergence of biomolecular simulations by determination of the effective sample size

Although atomistic simulations of proteins and other biological systems are approaching microsecond timescales, the quality of simulation trajectories has remained difficult to assess. Such assessment is critical not only for establishing the relevance of any individual simulation but also in the extremely active field of developing computational methods. Here we map the trajectory assessment problem onto a simple statistical calculation of the "effective sample size", that is, the number of statistically independent configurations. The mapping is achieved by asking the question, "How much time must elapse between snapshots included in a sample for that sample to exhibit the statistical properties expected for independent and identically distributed configurations?" Our method is more general than autocorrelation methods in that it directly probes the configuration-space distribution without requiring a priori definition of configurational substates and without any fitting parameters. We show that the method is equally and directly applicable to toy models, peptides, and a 72-residue protein model. Variants of our approach can readily be applied to a wide range of physical and chemical systems.

ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins

A major problem in structural biology is the recognition of errors in experimental and theoretical models of protein structures. The ProSA program (Protein Structure Analysis) is an established tool which has a large user base and is frequently employed in the refinement and validation of experimental protein structures and in structure prediction and modeling. The analysis of protein structures is generally a difficult and cumbersome exercise. The new service presented here is a straightforward and easy to use extension of the classic ProSA program which exploits the advantages of interactive web-based applications for the display of scores and energy plots that highlight potential problems spotted in protein structures. In particular, the quality scores of a protein are displayed in the context of all known protein structures and problematic parts of a structure are shown and highlighted in a 3D molecule viewer. The service specifically addresses the needs encountered in the validation of protein structures obtained from X-ray analysis, NMR spectroscopy and theoretical calculations. ProSA-web is accessible at https://prosa.services.came.sbg.ac.at

The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data

The worldwide Protein Data Bank (wwPDB) is the international collaboration that manages the deposition, processing and distribution of the PDB archive. The online PDB archive is a repository for the coordinates and related information for more than 38 000 structures, including proteins, nucleic acids and large macromolecular complexes that have been determined using X-ray crystallography, NMR and electron microscopy techniques. The founding members of the wwPDB are RCSB PDB (USA), MSD-EBI (Europe) and PDBj (Japan) [H.M. Berman, K. Henrick and H. Nakamura (2003) Nature Struct. Biol., 10, 980]. The BMRB group (USA) joined the wwPDB in 2006. The mission of the wwPDB is to maintain a single archive of macromolecular structural data that are freely and publicly available to the global community. Additionally, the wwPDB provides a variety of services to a broad community of users. The wwPDB website at provides information about services provided by the individual member organizations and about projects undertaken by the wwPDB.