Integrating genomic information with protein sequence and 3D atomic level structure at the RCSB protein data bank

The Protein Data Bank (PDB; http://wwpdb.org) was established in 1971 as the first open access digital data resource in biology with seven protein structures as its initial holdings. The global PDB archive now contains more than 126,000 experimentally determined atomic level three-dimensional (3D) structures of biological macromolecules (proteins, DNA, RNA), all of which are freely accessible via the Internet. Knowledge of the 3D structure of the gene product can help in understanding its function and role in disease. Of particular interest in the PDB archive are proteins for which 3D structures of genetic variant proteins have been determined, thus revealing atomic-level structural differences caused by the variation at the DNA level. Herein, we present a systematic and qualitative analysis of such cases. We observe a wide range of structural and functional changes caused by single amino acid differences, including changes in enzyme activity, aggregation propensity, structural stability, binding, and dissociation, some in the context of large assemblies. Structural comparison of wild type and mutated proteins, when both are available, provide insights into atomic-level structural differences caused by the genetic variation.

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“…These tools are available from the RCSB PDB website [71] and were used to verify the integrity of the benchmark data assembled for this study.…”

Section: Methodsmentioning

confidence: 99%

Impact of genetic variation on three dimensional structure and function of proteins

et al. 2017

Self Cite

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“…To facilitate the integration with human genomic information, a new analysis tool (Figure 2) maps any chromosomal position in the human genome to PDB data by matching alternative transcripts that might be available for a gene to the corresponding UniProt isoforms (17). …”

Section: New Website Featuresmentioning

confidence: 99%

“…Each unique polymer entity is listed in the Macromolecules section, with polymer name, chain identifiers, chain length and details, such as mutations, if any. A link to the Gene View is provided to map this structure into a genomic context (17). If the polymer sequence can be mapped to a UniProt sequence, a simplified Protein Feature View diagram (17) is also included.…”

Section: New Website Featuresmentioning

confidence: 99%

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OUP accepted manuscript

Rose

Prlić

Altunkaya

et al. 2016

Nucleic Acids Research

533

233

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The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a ‘Structural View of Biology.’ Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive.

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“…For example, NCBI’s Entrez utility or REST API only export biological data in FASTA and XML formats, although other information is available in JSON 9 . In biology, JSON is mainly used to store or exchange application related data that can include biological data, such as alignments 10 or protein sequences 11 . Another use of JSON is to combine search results 12 or represent XML schemes 13 .…”

Section: Introductionmentioning

confidence: 99%

The Biological Object Notation (BON): a structured file format for biological data

Buchmann

Fourment

Holmes

2018

Sci Rep

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The large size and high complexity of biological data can represent a major methodological challenge for the analysis and exchange of data sets between computers and applications. There has also been a substantial increase in the amount of metadata associated with biological data sets, which is being increasingly incorporated into existing data formats. Despite the existence of structured formats based on XML, biological data sets are mainly formatted using unstructured file formats, and the incorporation of metadata results in increasingly complex parsing routines such that they become more error prone. To overcome these problems, we present the “biological object notation” (BON) format, a new way to exchange and parse nearly all biological data sets more efficiently and with less error than other currently available formats. Based on JavaScript Object Notation (JSON), BON simplifies parsing by clearly separating the biological data from its metadata and reduces complexity compared to XML based formats. The ability to selectively compress data up to 87% compared to other file formats and the reduced complexity results in improved transfer times and less error prone applications.

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Integrating genomic information with protein sequence and 3D atomic level structure at the RCSB protein data bank

Cited by 17 publications

References 14 publications

Impact of genetic variation on three dimensional structure and function of proteins

Impact of genetic variation on three dimensional structure and function of proteins

OUP accepted manuscript

The Biological Object Notation (BON): a structured file format for biological data

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