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 communitie

Data to knowledge: how to get meaning from your result

Structural and functional studies require the development of sophisticated `Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB `super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results

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

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods

The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology

Protein Structure Initiative - TargetTrack 2000-2017 - all data files

Protein Structure Initiative - TargetTrack protein target registration database (795 MB, gzipped tarball) The Protein Structure Initiative was a high-throughput structural genomics effort from 2000-2015 focused on developing technologies to enable greater coverage of protein structure space. Over its 15-year tenure, over 100 investigators at 35 centers (see ContributingCenters.xls) declared over 350,000 protein sequences (targets) that they would study using state-of-the-art protein production and structure determination methods. Many of these targets were selected through bioinformatics-based methods to serve as representatives for sequence and structure clusters. From 2003-2010, these selected sequences and some basic identifying metadata were kept in a database called TargetDB, created at the Research Collaboratory for Structural Bioinformatics at Rutgers University. In 2008, a second database named PepcDB was created to track detailed experimental trial history and the standard protocols used by the PSI centers. These two databases became the principal structural genomics target databases, and were rolled into the PSI Structural Biology Knowledgebase in 2008. As part of the third phase of the PSI, TargetDB and PepcDB were merged into a single resource, TargetTrack, to facilitate one-stop access to the data as well as expanding the schema to include new required data items. Participating centers deposited the latest status on their active targets and the protocols that were used (along with any deviations) on a weekly or quarterly basis. TargetTrack provided a variety of pre-computed data downloads on a weekly basis as well. In July 2017, the Structural Biology Knowledgebase ceased operations. The files provided in this tarball represent the final datafiles generated by TargetTrack (timestamp June 30, 2017). Please read the README included in this dataset for descriptions of each file. The entire TargetTrack datafile in XML format can be found in /TargetTrack XML files/tt.xml.gz Key documentation can be found in the /Documentation folder. TargetTrack schema: targetTrack-v1.4.1.pdf Spreadsheet with TargetTrack enumerations for relevant fields: targetTrackEnumeratedDataItems-v1.4.1-1.xls Image depicted the XML data schema: targetTrack-v1.4.1.jpg These files are 868 MB in total size, uncompressed. To open the tarball, use the command 'tar -zxvf TargetTrack-1Jul2017.tar.gz' -- created by the PSI Structural Biology Knowledgebase, July 5, 201

Data to knowledge: how to get meaning from your result

Structural and functional studies require the development of sophisticated `Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB `super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results

Protein Structure Initiative Publications, 2000-2016

These files contain the full list of the 2313 publications and book chapters written as part of the Protein Structure Initiative, from 2000-2016. This data was collected from PubMed and by manual entry by the PSI Structural Biology Knowledgebase's Publication Portal, managed by Wladek Minor at University of Virginia. These files were created at the end of the PSI project on June 30, 2017. The references are provided as lists in two formats: in CSV (comma-separated variables) format that can be read in Excel or other spreadsheet application, or an Endnote Library Import file (store-endnote-pubs). To import this library into Endnote, select File --> Import... and then under Options, select the Import Option "Endnote Library Import". Then this text file will be processed and loaded into the library. --created by the Structural Biology Knowledgebase, July 5, 2017. (sbkb.org

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. Introduction When the Protein Data Bank (PDB) (Protein Data Bank, 1971) was first established in 1971, X-ray crystallography was the only method for determining three-dimensional structures of biological macromolecules at sufficient resolution to build atomic models. A decade later, structures of biomolecules in solution could also be determined by nuclear magnetic resonance (NMR) spectroscopy (Williamson et al., 1985). Recently, three-dimensional cryoelectron microscopy (3DEM) (Henderson et al., 1990) began to achieve unprecedented near-atomic resolution for large complex assemblies. Increasingly, investigators are also modeling structures based on data from more than one method (Rout and Sali, 2019). These integrative/hybrid approaches to structure determination consist of collecting information about a system using multiple experimental and computational methods, followed by integrative/hybrid modeling that converts this information into integrative/hybrid structure models. For succinctness, we will use the term integra-tive hereafter to refer to integrative/hybrid approaches, modeling, and models

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. Introduction When the Protein Data Bank (PDB) (Protein Data Bank, 1971) was first established in 1971, X-ray crystallography was the only method for determining three-dimensional structures of biological macromolecules at sufficient resolution to build atomic models. A decade later, structures of biomolecules in solution could also be determined by nuclear magnetic resonance (NMR) spectroscopy (Williamson et al., 1985). Recently, three-dimensional cryoelectron microscopy (3DEM) (Henderson et al., 1990) began to achieve unprecedented near-atomic resolution for large complex assemblies. Increasingly, investigators are also modeling structures based on data from more than one method (Rout and Sali, 2019). These integrative/hybrid approaches to structure determination consist of collecting information about a system using multiple experimental and computational methods, followed by integrative/hybrid modeling that converts this information into integrative/hybrid structure models. For succinctness, we will use the term integra-tive hereafter to refer to integrative/hybrid approaches, modeling, and models