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Exploring protein symmetry at the RCSB Protein Data Bank.
Duarte, Jose M; Dutta, Shuchismita; Goodsell, David S; Burley, Stephen K.
Afiliação
  • Duarte JM; Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, U.S.A.
  • Dutta S; Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, U.S.A.
  • Goodsell DS; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, U.S.A.
  • Burley SK; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08903, U.S.A.
Emerg Top Life Sci ; 6(3): 231-243, 2022 09 09.
Article em En | MEDLINE | ID: mdl-35801924
The symmetry of biological molecules has fascinated structural biologists ever since the structure of hemoglobin was determined. The Protein Data Bank (PDB) archive is the central global archive of three-dimensional (3D), atomic-level structures of biomolecules, providing open access to the results of structural biology research with no limitations on usage. Roughly 40% of the structures in the archive exhibit some type of symmetry, including formal global symmetry, local symmetry, or pseudosymmetry. The Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (founding member of the Worldwide Protein Data Bank partnership that jointly manages, curates, and disseminates the archive) provides a variety of tools to assist users interested in exploring the symmetry of biological macromolecules. These tools include multiple modalities for searching and browsing the archive, turnkey methods for biomolecular visualization, documentation, and outreach materials for exploring functional biomolecular symmetry.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Biologia Computacional Idioma: En Revista: Emerg Top Life Sci Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Biologia Computacional Idioma: En Revista: Emerg Top Life Sci Ano de publicação: 2022 Tipo de documento: Article