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Turner J, Abbott S, Fonseca N, Pye R, Carrijo L, Duraisamy AK, Salih O, Wang Z, Kleywegt GJ, Morris KL, Patwardhan A, Burley SK, Crichlow G, Feng Z, Flatt JW, Ghosh S, Hudson BP, Lawson CL, Liang Y, Peisach E, Persikova I, Sekharan M, Shao C, Young J, Velankar S, Armstrong D, Bage M, Bueno WM, Evans G, Gaborova R, Ganguly S, Gupta D, Harrus D, Tanweer A, Bansal M, Rangannan V, Kurisu G, Cho H, Ikegawa Y, Kengaku Y, Kim JY, Niwa S, Sato J, Takuwa A, Yu J, Hoch JC, Baskaran K, Xu W, Zhang W, Ma X. EMDB-the Electron Microscopy Data Bank. Nucleic Acids Res 2024; 52:D456-D465. [PMID: 37994703 PMCID: PMC10767987 DOI: 10.1093/nar/gkad1019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 10/18/2023] [Accepted: 10/20/2023] [Indexed: 11/24/2023] Open
Abstract
The Electron Microscopy Data Bank (EMDB) is the global public archive of three-dimensional electron microscopy (3DEM) maps of biological specimens derived from transmission electron microscopy experiments. As of 2021, EMDB is managed by the Worldwide Protein Data Bank consortium (wwPDB; wwpdb.org) as a wwPDB Core Archive, and the EMDB team is a core member of the consortium. Today, EMDB houses over 30 000 entries with maps containing macromolecules, complexes, viruses, organelles and cells. Herein, we provide an overview of the rapidly growing EMDB archive, including its current holdings, recent updates, and future plans.
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Flatt JW, Hudson BP, Persikova I, Liang Y, Shao C, Peisach E, Young JY, Burley SK. Assessing and Maximizing the Quality of 3DEM Structure Data at the Worldwide Protein Data Bank. Microsc Microanal 2023; 29:948. [PMID: 37613801 DOI: 10.1093/micmic/ozad067.472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Justin W Flatt
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Brian P Hudson
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Irina Persikova
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Yuhe Liang
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Chenghua Shao
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Ezra Peisach
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Jasmine Y Young
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
| | - Stephen K Burley
- RCSB Protein Data Bank, Rutgers, The State University of New Jersey, New Jersey, United States
- RCSB Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, California, United States
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Burley SK, Bhikadiya C, Bi C, Bittrich S, Chao H, Chen L, Craig PA, Crichlow GV, Dalenberg K, Duarte JM, Dutta S, Fayazi M, Feng Z, Flatt JW, Ganesan S, Ghosh S, Goodsell DS, Green RK, Guranovic V, Henry J, Hudson BP, Khokhriakov I, Lawson CL, Liang Y, Lowe R, Peisach E, Persikova I, Piehl DW, Rose Y, Sali A, Segura J, Sekharan M, Shao C, Vallat B, Voigt M, Webb B, Westbrook JD, Whetstone S, Young JY, Zalevsky A, Zardecki C. RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning. Nucleic Acids Res 2023; 51:D488-D508. [PMID: 36420884 PMCID: PMC9825554 DOI: 10.1093/nar/gkac1077] [Citation(s) in RCA: 119] [Impact Index Per Article: 119.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/17/2022] [Accepted: 11/02/2022] [Indexed: 11/27/2022] Open
Abstract
The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a 'living data resource.' Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.
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Affiliation(s)
- Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08901, USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Charmi Bhikadiya
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Chunxiao Bi
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Sebastian Bittrich
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Henry Chao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Li Chen
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Paul A Craig
- School of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, NY 14623, USA
| | - Gregg V Crichlow
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Kenneth Dalenberg
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jose M Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Shuchismita Dutta
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08901, USA
| | - Maryam Fayazi
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Zukang Feng
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Justin W Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sai Ganesan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA
| | - Sutapa Ghosh
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - David S Goodsell
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08901, USA
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Rachel Kramer Green
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Vladimir Guranovic
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jeremy Henry
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Brian P Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Igor Khokhriakov
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Catherine L Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Yuhe Liang
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Robert Lowe
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ezra Peisach
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Irina Persikova
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Dennis W Piehl
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Yana Rose
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA
| | - Joan Segura
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Monica Sekharan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Chenghua Shao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Maria Voigt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ben Webb
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA
| | - John D Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08901, USA
| | - Shamara Whetstone
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jasmine Y Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Arthur Zalevsky
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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Burley SK, Berman HM, Chiu W, Dai W, Flatt JW, Hudson BP, Kaelber JT, Khare SD, Kulczyk AW, Lawson CL, Pintilie GD, Sali A, Vallat B, Westbrook JD, Young JY, Zardecki C. Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future. Biophys Rev 2022; 14:1281-1301. [PMID: 36474933 PMCID: PMC9715422 DOI: 10.1007/s12551-022-01013-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/06/2022] [Indexed: 12/04/2022] Open
Abstract
As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.
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Affiliation(s)
- Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Helen M. Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Wah Chiu
- Department of Bioengineering, Stanford University, Stanford, CA USA
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA USA
| | - Wei Dai
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Justin W. Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Brian P. Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Jason T. Kaelber
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Sagar D. Khare
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854 USA
| | - Arkadiusz W. Kulczyk
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, Piscataway, NJ 08901 USA
| | - Catherine L. Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | | | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158 USA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
| | - John D. Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA
| | - Jasmine Y. Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854 USA
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5
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Burley SK, Bhikadiya C, Bi C, Bittrich S, Chao H, Chen L, Craig PA, Crichlow GV, Dalenberg K, Duarte JM, Dutta S, Fayazi M, Feng Z, Flatt JW, Ganesan SJ, Ghosh S, Goodsell DS, Green RK, Guranovic V, Henry J, Hudson BP, Khokhriakov I, Lawson CL, Liang Y, Lowe R, Peisach E, Persikova I, Piehl DW, Rose Y, Sali A, Segura J, Sekharan M, Shao C, Vallat B, Voigt M, Webb B, Westbrook JD, Whetstone S, Young JY, Zalevsky A, Zardecki C. RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D. Protein Sci 2022; 31:e4482. [PMID: 36281733 PMCID: PMC9667899 DOI: 10.1002/pro.4482] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/17/2022] [Accepted: 10/19/2022] [Indexed: 12/14/2022]
Abstract
Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open-access global archive housing three-dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB-designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction). The RCSB PDB research-focused web portal (RCSB.org) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal (PDB101.RCSB.org) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB-designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org; and (v) supports training, outreach, and education via PDB101.RCSB.org. New tools and features at RCSB.org are presented using examples drawn from high-resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.
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Affiliation(s)
- Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Cancer Institute of New Jersey, Rutgers, The State University of New JerseyNew BrunswickNew JerseyUSA,Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA,Department of Chemistry and Chemical Biology, RutgersThe State University of New JerseyPiscatawayNew JerseyUSA
| | - Charmi Bhikadiya
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Chunxiao Bi
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Sebastian Bittrich
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Henry Chao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Li Chen
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Paul A. Craig
- School of Chemistry and Materials ScienceRochester Institute of TechnologyRochesterNew YorkUSA
| | - Gregg V. Crichlow
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Kenneth Dalenberg
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Jose M. Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Shuchismita Dutta
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Cancer Institute of New Jersey, Rutgers, The State University of New JerseyNew BrunswickNew JerseyUSA
| | - Maryam Fayazi
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Zukang Feng
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Justin W. Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Sai J. Ganesan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic SciencesQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA,Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Pharmaceutical ChemistryQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA
| | - Sutapa Ghosh
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - David S. Goodsell
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Cancer Institute of New Jersey, Rutgers, The State University of New JerseyNew BrunswickNew JerseyUSA,Department of Integrative Structural and Computational BiologyThe Scripps Research InstituteLa JollaCaliforniaUSA
| | - Rachel Kramer Green
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Vladimir Guranovic
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Jeremy Henry
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Brian P. Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Igor Khokhriakov
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Catherine L. Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Yuhe Liang
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Robert Lowe
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Ezra Peisach
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Irina Persikova
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Dennis W. Piehl
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Yana Rose
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic SciencesQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA,Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Pharmaceutical ChemistryQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA
| | - Joan Segura
- Research Collaboratory for Structural Bioinformatics Protein Data BankSan Diego Supercomputer Center, University of CaliforniaLa JollaCaliforniaUSA
| | - Monica Sekharan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Chenghua Shao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Maria Voigt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Benjamin Webb
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic SciencesQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA,Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Pharmaceutical ChemistryQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA
| | - John D. Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Shamara Whetstone
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Jasmine Y. Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Arthur Zalevsky
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic SciencesQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA,Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Pharmaceutical ChemistryQuantitative Biosciences Institute, University of CaliforniaSan FranciscoCaliforniaUSA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA,Institute for Quantitative Biomedicine, Rutgers, The State University of New JerseyPiscatawayNew JerseyUSA
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6
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Burley SK, Berman HM, Duarte JM, Feng Z, Flatt JW, Hudson BP, Lowe R, Peisach E, Piehl DW, Rose Y, Sali A, Sekharan M, Shao C, Vallat B, Voigt M, Westbrook JD, Young JY, Zardecki C. Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students. Biomolecules 2022; 12:1425. [PMID: 36291635 PMCID: PMC9599165 DOI: 10.3390/biom12101425] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/23/2022] [Accepted: 09/26/2022] [Indexed: 11/18/2022] Open
Abstract
The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide.
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Affiliation(s)
- Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Helen M. Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jose M. Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Zukang Feng
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Justin W. Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Brian P. Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Robert Lowe
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ezra Peisach
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Dennis W. Piehl
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Yana Rose
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA
| | - Monica Sekharan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Chenghua Shao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Maria Voigt
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - John D. Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Jasmine Y. Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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7
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Burley SK, Bhikadiya C, Bi C, Bittrich S, Chen L, Crichlow GV, Duarte JM, Dutta S, Fayazi M, Feng Z, Flatt JW, Ganesan SJ, Goodsell DS, Ghosh S, Kramer Green R, Guranovic V, Henry J, Hudson BP, Lawson CL, Liang Y, Lowe R, Peisach E, Persikova I, Piehl DW, Rose Y, Sali A, Segura J, Sekharan M, Shao C, Vallat B, Voigt M, Westbrook JD, Whetstone S, Young JY, Zardecki C. RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D. Protein Sci 2022; 31:187-208. [PMID: 34676613 PMCID: PMC8740825 DOI: 10.1002/pro.4213] [Citation(s) in RCA: 63] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/12/2021] [Accepted: 10/12/2021] [Indexed: 01/03/2023]
Abstract
The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.
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Affiliation(s)
- Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Cancer Institute of New JerseyRutgers, The State University of New JerseyNew BrunswickNew JerseyUSA
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
- Department of Chemistry and Chemical BiologyRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Charmi Bhikadiya
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Chunxiao Bi
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Sebastian Bittrich
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Li Chen
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Gregg V. Crichlow
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Jose M. Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Shuchismita Dutta
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Cancer Institute of New JerseyRutgers, The State University of New JerseyNew BrunswickNew JerseyUSA
| | - Maryam Fayazi
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Zukang Feng
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Justin W. Flatt
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Sai J. Ganesan
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - David S. Goodsell
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Cancer Institute of New JerseyRutgers, The State University of New JerseyNew BrunswickNew JerseyUSA
- Department of Integrative Structural and Computational BiologyThe Scripps Research InstituteLa JollaCaliforniaUSA
| | - Sutapa Ghosh
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Rachel Kramer Green
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Vladimir Guranovic
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Jeremy Henry
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Brian P. Hudson
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Catherine L. Lawson
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Yuhe Liang
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Robert Lowe
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Ezra Peisach
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Irina Persikova
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Dennis W. Piehl
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Yana Rose
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Andrej Sali
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, Quantitative Biosciences InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Joan Segura
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer CenterUniversity of CaliforniaLa JollaCaliforniaUSA
| | - Monica Sekharan
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Chenghua Shao
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Brinda Vallat
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Maria Voigt
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - John D. Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Cancer Institute of New JerseyRutgers, The State University of New JerseyNew BrunswickNew JerseyUSA
| | - Shamara Whetstone
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Jasmine Y. Young
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
| | - Christine Zardecki
- Research Collaboratory for Structural Bioinformatics Protein Data BankRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
- Institute for Quantitative BiomedicineRutgers, The State University of New JerseyPiscatawayNew JerseyUSA
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8
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Bauer M, Flatt JW, Seiler D, Cardel B, Emmenlauer M, Boucke K, Suomalainen M, Hemmi S, Greber UF. The E3 Ubiquitin Ligase Mind Bomb 1 Controls Adenovirus Genome Release at the Nuclear Pore Complex. Cell Rep 2020; 29:3785-3795.e8. [PMID: 31851912 DOI: 10.1016/j.celrep.2019.11.064] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 10/15/2019] [Accepted: 11/14/2019] [Indexed: 01/06/2023] Open
Abstract
Adenoviruses (AdVs) cause respiratory, ocular, and gastrointestinal tract infection and inflammation in immunocompetent people and life-threatening disease upon immunosuppression. AdV vectors are widely used in gene therapy and vaccination. Incoming particles attach to nuclear pore complexes (NPCs) of post-mitotic cells, then rupture and deliver viral DNA (vDNA) to the nucleus or misdeliver to the cytosol. Our genome-wide RNAi screen in AdV-infected cells identified the RING-type E3 ubiquitin ligase Mind bomb 1 (Mib1) as a proviral host factor for AdV infection. Mib1 is implicated in Notch-Delta signaling, ciliary biogenesis, and RNA innate immunity. Mib1 depletion arrested incoming AdVs at NPCs. Induced expression of full-length but not ligase-defective Mib1 in knockout cells triggered vDNA uncoating from NPC-tethered virions, nuclear import, misdelivery of vDNA, and vDNA expression. Mib1 is an essential host factor for AdV uncoating in human cells, and it provides a new concept for licensing virion DNA delivery through the NPC.
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Affiliation(s)
- Michael Bauer
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland; Life Science Zurich Graduate School, ETH and University of Zurich, 8057 Zurich, Switzerland
| | - Justin W Flatt
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland; Institute of Biotechnology, University of Helsinki, 00790 Helsinki, Finland; Department of Biosciences, University of Helsinki, 00790 Helsinki, Finland
| | - Daria Seiler
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Bettina Cardel
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | | | - Karin Boucke
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Maarit Suomalainen
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Silvio Hemmi
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Urs F Greber
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland.
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9
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Abstract
Viruses are obligatory parasites that take advantage of intracellular niches to replicate. During infection, their genomes are carried in capsids across the membranes of host cells to sites of virion production by exploiting cellular behaviour and resources to guide and achieve all aspects of delivery and the downstream virus manufacturing process. Successful entry hinges on execution of a precisely tuned viral uncoating program where incoming capsids disassemble in consecutive steps to ensure that genomes are released at the right time, and in the right place for replication to occur. Each step of disassembly is cell-assisted, involving individual pathways that transmit signals to regulate discrete functions, but at the same time, these signalling pathways are organized into larger networks, which communicate back and forth in complex ways in response to the presence of virus. In this review, we consider the elegant strategy by which adenoviruses (AdVs) target and navigate cellular networks to initiate the production of progeny virions. There are many remarkable aspects about the AdV entry program; for example, the virus gains targeted control of a large well-defined local network neighbourhood by coupling several interacting processes (including endocytosis, autophagy and microtubule trafficking) around a collective reference state centred on the interactional topology and multifunctional nature of protein VI. Understanding the network targeting activity of protein VI, as well as other built-in mechanisms that allow AdV particles to be efficient at navigating the subsystems of the cell, can be used to improve viral vectors, but also has potential to be incorporated for use in entirely novel delivery systems.
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Affiliation(s)
- Justin W Flatt
- Faculty of Biological and Environmental Sciences and HiLIFE-Institute of Biotechnology, University of Helsinki , 00790 Helsinki , Finland
| | - Sarah J Butcher
- Faculty of Biological and Environmental Sciences and HiLIFE-Institute of Biotechnology, University of Helsinki , 00790 Helsinki , Finland
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10
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Abstract
More than 80 different adenovirus (AdV) types infect humans through the respiratory, ocular, or gastrointestinal tracts. They cause acute clinical mani-festations or persist under humoral and cell-based immunity. Immuno-suppressed individuals are at risk of death from an AdV infection. Concepts about cell entry of AdV build on strong foundations from molecular and cellular biology-and increasingly physical virology. Here, we discuss how virions enter and deliver their genome into the nucleus of epithelial cells. This process breaks open the virion at distinct sites because the particle has nonisometric mechanical strength and reacts to specific host factors along the entry pathway. We further describe how macrophages and dendritic cells resist AdV infection yet enhance productive entry into polarized epithelial cells. A deep understanding of the viral mechanisms and cell biological and biophysical principles will continue to unravel how epithelial and antigen-presenting cells respond to AdVs and control inflammation and persistence in pathology and therapy.
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Affiliation(s)
- Urs F Greber
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland;
| | - Justin W Flatt
- Institute of Biotechnology and Department of Biosciences, University of Helsinki, 00790 Helsinki, Finland;
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11
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Abdelnabi R, Geraets JA, Ma Y, Mirabelli C, Flatt JW, Domanska A, Delang L, Jochmans D, Kumar TA, Jayaprakash V, Sinha BN, Leyssen P, Butcher SJ, Neyts J. A novel druggable interprotomer pocket in the capsid of rhino- and enteroviruses. PLoS Biol 2019; 17:e3000281. [PMID: 31185007 PMCID: PMC6559632 DOI: 10.1371/journal.pbio.3000281] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 05/08/2019] [Indexed: 12/22/2022] Open
Abstract
Rhino- and enteroviruses are important human pathogens, against which no antivirals are available. The best-studied inhibitors are "capsid binders" that fit in a hydrophobic pocket of the viral capsid. Employing a new class of entero-/rhinovirus inhibitors and by means of cryo-electron microscopy (EM), followed by resistance selection and reverse genetics, we discovered a hitherto unknown druggable pocket that is formed by viral proteins VP1 and VP3 and that is conserved across entero-/rhinovirus species. We propose that these inhibitors stabilize a key region of the virion, thereby preventing the conformational expansion needed for viral RNA release. A medicinal chemistry effort resulted in the identification of analogues targeting this pocket with broad-spectrum activity against Coxsackieviruses B (CVBs) and compounds with activity against enteroviruses (EV) of groups C and D, and even rhinoviruses (RV). Our findings provide novel insights in the biology of the entry of entero-/rhinoviruses and open new avenues for the design of broad-spectrum antivirals against these pathogens.
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Affiliation(s)
- Rana Abdelnabi
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
| | - James A. Geraets
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Bioscience Research Programme, University of Helsinki, Helsinki, Finland
- Helsinki Institute of Life Sciences, Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Yipeng Ma
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
| | - Carmen Mirabelli
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
| | - Justin W. Flatt
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Bioscience Research Programme, University of Helsinki, Helsinki, Finland
- Helsinki Institute of Life Sciences, Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Aušra Domanska
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Bioscience Research Programme, University of Helsinki, Helsinki, Finland
- Helsinki Institute of Life Sciences, Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Leen Delang
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
| | - Dirk Jochmans
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
| | - Timiri Ajay Kumar
- Department of Pharmaceutical Sciences & Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
| | - Venkatesan Jayaprakash
- Department of Pharmaceutical Sciences & Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
| | - Barij Nayan Sinha
- Department of Pharmaceutical Sciences & Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
| | - Pieter Leyssen
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
| | - Sarah J. Butcher
- Faculty of Biological and Environmental Sciences, Molecular and Integrative Bioscience Research Programme, University of Helsinki, Helsinki, Finland
- Helsinki Institute of Life Sciences, Institute of Biotechnology, University of Helsinki, Helsinki, Finland
- * E-mail: (JN); (SJB)
| | - Johan Neyts
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Leuven, Belgium
- * E-mail: (JN); (SJB)
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12
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Stichling N, Suomalainen M, Flatt JW, Schmid M, Pacesa M, Hemmi S, Jungraithmayr W, Maler MD, Freudenberg MA, Plückthun A, May T, Köster M, Fejer G, Greber UF. Lung macrophage scavenger receptor SR-A6 (MARCO) is an adenovirus type-specific virus entry receptor. PLoS Pathog 2018. [PMID: 29522575 PMCID: PMC5862501 DOI: 10.1371/journal.ppat.1006914] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Macrophages are a diverse group of phagocytic cells acting in host protection against stress, injury, and pathogens. Here, we show that the scavenger receptor SR-A6 is an entry receptor for human adenoviruses in murine alveolar macrophage-like MPI cells, and important for production of type I interferon. Scavenger receptors contribute to the clearance of endogenous proteins, lipoproteins and pathogens. Knockout of SR-A6 in MPI cells, anti-SR-A6 antibody or the soluble extracellular SR-A6 domain reduced adenovirus type-C5 (HAdV-C5) binding and transduction. Expression of murine SR-A6, and to a lower extent human SR-A6 boosted virion binding to human cells and transduction. Virion clustering by soluble SR-A6 and proximity localization with SR-A6 on MPI cells suggested direct adenovirus interaction with SR-A6. Deletion of the negatively charged hypervariable region 1 (HVR1) of hexon reduced HAdV-C5 binding and transduction, implying that the viral ligand for SR-A6 is hexon. SR-A6 facilitated macrophage entry of HAdV-B35 and HAdV-D26, two important vectors for transduction of hematopoietic cells and human vaccination. The study highlights the importance of scavenger receptors in innate immunity against human viruses. Macrophages are a diverse group of phagocytic cells acting in host protection against stress, injury, and pathogens. They phenotypically and functionally adapt to their local environment, for example, peritoneal macrophages are distinct from brain-resident microglia, from liver-resident Kupffer cells or lung macrophages in the lung. Airway macrophages are among the first cells to encounter human respiratory viruses, such as adenoviruses. They release pro-inflammatory cytokines, kill pathogens, present antigens, and restore tissues. Yet, interactions of viruses with lung macrophages are poorly understood, and it is unclear, how they lead to infection or virus clearance. Here we identified the murine scavenger receptor SR-A6 as a receptor for a subset of human adenoviruses on alveolar macrophage-like cells, so-called MPI cells. Scavenger receptors comprise a large family of trans-membrane proteins, and contribute to the clearance of endogenous proteins, lipoproteins and pathogens. In a series of robust experimentation, we show that adenoviruses use SR-A6 as an entry receptor for infection of MPI cells, and production of type I interferon. MPI cells are non-transformed, self-renewing macrophages derived from fetal murine liver, and closely resemble adult alveolar macrophages. The results demonstrate that SR-A6 binds virions on the surface of alveolar macrophage-like cells, and leads to infection.
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MESH Headings
- Adenoviridae Infections/immunology
- Adenoviridae Infections/metabolism
- Adenoviridae Infections/virology
- Adenoviruses, Human/immunology
- Animals
- Humans
- Immunity, Innate
- Lung/immunology
- Lung/metabolism
- Lung/virology
- Macrophages/immunology
- Macrophages/metabolism
- Macrophages/virology
- Macrophages, Alveolar/immunology
- Macrophages, Alveolar/metabolism
- Macrophages, Alveolar/virology
- Mice
- Mice, Inbred BALB C
- Mice, Inbred C57BL
- Mice, Knockout
- Protein Binding
- Receptors, Immunologic/genetics
- Receptors, Immunologic/metabolism
- Receptors, Immunologic/physiology
- Virus Internalization
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Affiliation(s)
- Nicole Stichling
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- Molecular Life Sciences Graduate School, ETH and University of Zurich, Switzerland
| | - Maarit Suomalainen
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Justin W. Flatt
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Markus Schmid
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Martin Pacesa
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Silvio Hemmi
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Wolfgang Jungraithmayr
- University Hospital Zurich, Institute of Thorax Surgery, Zurich, Switzerland
- present address: Department of Thoracic Surgery, Medical University Brandenburg, Neuruppin, Germany
| | - Mareike D. Maler
- Max-Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
- Allergy Research Group, Department of Dermatology, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Marina A. Freudenberg
- Max-Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
- BIOSS Centre for Biological Signalling Studies, Albert-Ludwigs-Universität, Freiburg, Germany
- Department of Pneumology, Medical Center–University of Freiburg and Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Andreas Plückthun
- Department of Biochemistry, University of Zurich, Zurich, Switzerland
| | - Tobias May
- Inscreenex GmbH, Inhoffenstr. Brunswick, Germany
| | - Mario Köster
- Helmholtz-Zentrum für Infektionsforschung GmbH, Braunschweig, Germany
| | - György Fejer
- School of Biomedical and Healthcare Sciences, Peninsula Schools of Medicine and Dentistry, University of Plymouth, Plymouth, United Kingdom
| | - Urs F. Greber
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- * E-mail:
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13
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Pacesa M, Hendrickx R, Bieri M, Flatt JW, Greber UF, Hemmi S. Small-size recombinant adenoviral hexon protein fragments for the production of virus-type specific antibodies. Virol J 2017; 14:158. [PMID: 28821267 PMCID: PMC5563037 DOI: 10.1186/s12985-017-0822-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 08/08/2017] [Indexed: 12/30/2022] Open
Abstract
Background Adenoviruses are common pathogens infecting animals and humans. They are classified based on serology, or genome sequence information. These methods have limitations due to lengthy procedures or lack of infectivity data. Adenoviruses are easy to produce and amenable to genetic and biochemical modifications, which makes them a powerful tool for biological studies, and clinical gene-delivery and vaccine applications. Antibodies directed against adenoviral proteins are important diagnostic tools for virus identification in vivo and in vitro, and are used to elucidate infection mechanisms, often in combination with genomic sequencing and type specific information from hyper-variable regions of structural proteins. Results Here we describe a novel and readily useable method for cloning, expressing and purifying small fragments of hyper-variable regions 1-6 of the adenoviral hexon protein. We used these polypeptides as antigens for generating polyclonal rabbit antibodies against human adenovirus 3 (HAdV-B3), mouse adenovirus 1 (MAdV-1) and MAdV-2 hexon. In Western immunoblots with lysates from cells infected from thirteen human and three mouse viruses, these antibodies bound to homologous full-length hexon protein and revealed variable levels of cross-reactivity to heterologous hexons. Results from immuno-fluorescence and electron microscopy studies indicated that HAdV-B3 and MAdV-2 hexon antibodies recognized native forms of hexon. Conclusions The procedure described here can in principle be applied to any adenovirus for which genome sequence information is available. It provides a basis for generating novel type-specific tools in diagnostics and research, and extends beyond the commonly used anti-viral antibodies raised against purified viruses or subviral components. Electronic supplementary material The online version of this article (doi:10.1186/s12985-017-0822-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martin Pacesa
- Institute of Molecular Life Sciences, University of Zurich, CH-8057, Zurich, Switzerland
| | - Rodinde Hendrickx
- Institute of Molecular Life Sciences, University of Zurich, CH-8057, Zurich, Switzerland.,Molecular Life Sciences Graduate School, Eidgenössische Technische Hochschule and University of Zurich, CH-8057, Zurich, Switzerland
| | - Manuela Bieri
- Institute of Molecular Life Sciences, University of Zurich, CH-8057, Zurich, Switzerland.,Molecular Life Sciences Graduate School, Eidgenössische Technische Hochschule and University of Zurich, CH-8057, Zurich, Switzerland
| | - Justin W Flatt
- Institute of Molecular Life Sciences, University of Zurich, CH-8057, Zurich, Switzerland
| | - Urs F Greber
- Institute of Molecular Life Sciences, University of Zurich, CH-8057, Zurich, Switzerland
| | - Silvio Hemmi
- Institute of Molecular Life Sciences, University of Zurich, CH-8057, Zurich, Switzerland.
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14
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Flatt JW, Greber UF. Viral mechanisms for docking and delivering at nuclear pore complexes. Semin Cell Dev Biol 2017; 68:59-71. [PMID: 28506891 DOI: 10.1016/j.semcdb.2017.05.008] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Accepted: 05/11/2017] [Indexed: 12/22/2022]
Abstract
Some viruses possess the remarkable ability to transport their genomes across nuclear pore complexes (NPCs) for replication inside the host cell's intact nuclear compartment. Viral mechanisms for crossing the restrictive NPC passageway are highly complex and astonishingly diverse, requiring in each case stepwise interaction between incoming virus particles and components of the nuclear transport machinery. Exactly how a large viral genome loaded with accessory proteins is able to pass through the relatively narrow central channel of the NPC without causing catastrophic structural damage is not yet fully understood. It appears likely, however, that the overall structure of the NPC changes in response to the cargo. Translocation may result in nucleic acids being misdelivered to the cytoplasm. Here we consider in detail the diverse strategies that viruses have evolved to target and subvert NPCs during infection. For decades, this process has both captivated and confounded researchers in the fields of virology, cell biology, and structural biology.
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Affiliation(s)
- Justin W Flatt
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
| | - Urs F Greber
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
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15
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Flatt JW, Kim R, Smith JG, Nemerow GR, Stewart PL. An intrinsically disordered region of the adenovirus capsid is implicated in neutralization by human alpha defensin 5. PLoS One 2013; 8:e61571. [PMID: 23620768 PMCID: PMC3631211 DOI: 10.1371/journal.pone.0061571] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 03/10/2013] [Indexed: 11/18/2022] Open
Abstract
Human α-defensins are proteins of the innate immune system that suppress viral and bacterial infections by multiple mechanisms including membrane disruption. For viruses that lack envelopes, such as human adenovirus (HAdV), other, less well defined, mechanisms must be involved. A previous structural study on the interaction of an α-defensin, human α-defensin 5 (HD5), with HAdV led to a proposed mechanism in which HD5 stabilizes the vertex region of the capsid and blocks uncoating steps required for infectivity. Studies with virus chimeras comprised of capsid proteins from sensitive and resistant serotypes supported this model. To further characterize the critical binding site, we determined subnanometer resolution cryo-electron microscopy (cryoEM) structures of HD5 complexed with both neutralization-sensitive and -resistant HAdV chimeras. Models were built for the vertex regions of these chimeras with monomeric and dimeric forms of HD5 in various initial orientations. CryoEM guided molecular dynamics flexible fitting (MDFF) was used to restrain the majority of the vertex model in well-defined cryoEM density. The RGD-containing penton base loops of both the sensitive and resistant virus chimeras are predicted to be intrinsically disordered, and little cryoEM density is observed for them. In simulations these loops from the sensitive virus chimera, interact with HD5, bridge the penton base and fiber proteins, and provides significant stabilization with a three-fold increase in the intermolecular nonbonded interactions of the vertex complex. In the case of the resistant virus chimera, simulations revealed fewer bridging interactions and reduced stabilization by HD5. This study implicates a key dynamic region in mediating a stabilizing interaction between a viral capsid and a protein of the innate immune system with potent anti-viral activity.
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Affiliation(s)
- Justin W. Flatt
- Department of Pharmacology and Cleveland Center for Membrane and Structural Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Robert Kim
- Department of Molecular Physiology and Biophysics, School of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Jason G. Smith
- Department of Microbiology, University of Washington, Seattle, Washington, United States of America
| | - Glen R. Nemerow
- Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, California, United States of America
| | - Phoebe L. Stewart
- Department of Pharmacology and Cleveland Center for Membrane and Structural Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
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16
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Flatt JW, Fox TL, Makarova N, Blackwell JL, Dmitriev IP, Kashentseva EA, Curiel DT, Stewart PL. CryoEM visualization of an adenovirus capsid-incorporated HIV antigen. PLoS One 2012; 7:e49607. [PMID: 23166728 PMCID: PMC3498208 DOI: 10.1371/journal.pone.0049607] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Accepted: 10/11/2012] [Indexed: 01/12/2023] Open
Abstract
Adenoviral (Ad) vectors show promise as platforms for vaccine applications against infectious diseases including HIV. However, the requirements for eliciting protective neutralizing antibody and cellular immune responses against HIV remain a major challenge. In a novel approach to generate 2F5- and 4E10-like antibodies, we engineered an Ad vector with the HIV membrane proximal ectodomain region (MPER) epitope displayed on the hypervariable region 2 (HVR2) of the viral hexon capsid, instead of expressed as a transgene. The structure and flexibility of MPER epitopes, and the structural context of these epitopes within viral vectors, play important roles in the induced host immune responses. In this regard, understanding the critical factors for epitope presentation would facilitate optimization strategies for developing viral vaccine vectors. Therefore we undertook a cryoEM structural study of this Ad vector, which was previously shown to elicit MPER-specific humoral immune responses. A subnanometer resolution cryoEM structure was analyzed with guided molecular dynamics simulations. Due to the arrangement of hexons within the Ad capsid, there are twelve unique environments for the inserted peptide that lead to a variety of conformations for MPER, including individual α-helices, interacting α-helices, and partially extended forms. This finding is consistent with the known conformational flexibility of MPER. The presence of an extended form, or an induced extended form, is supported by interaction of this vector with the human HIV monoclonal antibody 2F5, which recognizes 14 extended amino acids within MPER. These results demonstrate that the Ad capsid influences epitope structure, flexibility and accessibility, all of which affect the host immune response. In summary, this cryoEM structural study provided a means to visualize an epitope presented on an engineered viral vector and suggested modifications for the next generation of Ad vectors with capsid-incorporated HIV epitopes.
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Affiliation(s)
- Justin W. Flatt
- Department of Pharmacology and Cleveland Center for Membrane and Structural Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Tara L. Fox
- Department of Pharmacology and Cleveland Center for Membrane and Structural Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Natalia Makarova
- Department of Medicine, Division of Infectious Diseases, Emory Vaccine Center and Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, United States of America
| | - Jerry L. Blackwell
- Department of Medicine, Division of Infectious Diseases, Emory Vaccine Center and Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, United States of America
| | - Igor P. Dmitriev
- Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Elena A. Kashentseva
- Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - David T. Curiel
- Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Phoebe L. Stewart
- Department of Pharmacology and Cleveland Center for Membrane and Structural Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
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17
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Doronin K, Flatt JW, Di Paolo NC, Khare R, Kalyuzhniy O, Acchione M, Sumida JP, Ohto U, Shimizu T, Akashi-Takamura S, Miyake K, MacDonald JW, Bammler TK, Beyer RP, Farin FM, Stewart PL, Shayakhmetov DM. Coagulation factor X activates innate immunity to human species C adenovirus. Science 2012; 338:795-8. [PMID: 23019612 DOI: 10.1126/science.1226625] [Citation(s) in RCA: 116] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Although coagulation factors play a role in host defense for "living fossils" such as horseshoe crabs, the role of the coagulation system in immunity in higher organisms remains unclear. We modeled the interface of human species C adenovirus (HAdv) interaction with coagulation factor X (FX) and introduced a mutation that abrogated formation of the HAdv-FX complex. In vivo genome-wide transcriptional profiling revealed that FX-binding-ablated virus failed to activate a distinct network of nuclear factor κB-dependent early-response genes that are activated by HAdv-FX complex downstream of TLR4/MyD88/TRIF/TRAF6 signaling. Our study implicates host factor "decoration" of the virus as a mechanism to trigger an innate immune sensor that responds to a misplacement of coagulation FX from the blood into intracellular macrophage compartments upon virus entry into the cell.
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Affiliation(s)
- Konstantin Doronin
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
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18
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Wilson RC, Edmondson SP, Flatt JW, Helms K, Twigg PD. The E2-25K ubiquitin-associated (UBA) domain aids in polyubiquitin chain synthesis and linkage specificity. Biochem Biophys Res Commun 2011; 405:662-6. [PMID: 21281599 DOI: 10.1016/j.bbrc.2011.01.089] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2011] [Accepted: 01/25/2011] [Indexed: 11/18/2022]
Abstract
E2-25K is an ubiquitin-conjugating enzyme with the ability to synthesize Lys48-linked polyubiquitin chains. E2-25K and its homologs represent the only known E2 enzymes which contain a C-terminal ubiquitin-associated (UBA) domain as well as the conserved catalytic ubiquitin-conjugating (UBC) domain. As an additional non-covalent binding surface for ubiquitin, the UBA domain must provide some functional specialization. We mapped the protein-protein interface involved in the E2-25K UBA/ubiquitin complex by solution nuclear magnetic resonance (NMR) spectroscopy and subsequently modeled the structure of the complex. Domain-domain interactions between the E2-25K catalytic UBC domain and the UBA domain do not induce significant structural changes in the UBA domain or alter the affinity of the UBA domain for ubiquitin. We determined that one of the roles of the C-terminal UBA domain, in the context of E2-25K, is to increase processivity in Lys48-linked polyubiquitin chain synthesis, possibly through increased binding to the ubiquitinated substrate. Additionally, we see evidence that the UBA domain directs specificity in polyubiquitin chain linkage.
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Affiliation(s)
- Randall C Wilson
- Laboratory for Structural Biology, University of Alabama in Huntsville, Huntsville, AL 35899, USA
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19
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Wilson RC, Hughes RC, Flatt JW, Meehan EJ, Ng JD, Twigg PD. Structure of full-length ubiquitin-conjugating enzyme E2-25K (huntingtin-interacting protein 2). Acta Crystallogr Sect F Struct Biol Cryst Commun 2009; 65:440-4. [PMID: 19407372 DOI: 10.1107/s1744309109011117] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2009] [Accepted: 03/25/2009] [Indexed: 11/10/2022]
Abstract
The ubiquitin-conjugating enzyme E2-25K has been identified as a huntingtin (the key protein in Huntington's disease) interacting protein and has been shown to play a role in mediating the toxicity of Abeta, the principal protein involved in Alzheimer's disease pathogenesis. E2-25K is a dual-domain protein with an ubiquitin-associated (UBA) domain as well as a conserved ubiquitin-conjugating (UBC) domain which catalyzes the formation of a covalent bond between the C-terminal glycine of an ubiquitin molecule and the -amine of a lysine residue on the acceptor protein as part of the ubiquitin-proteasome pathway. The crystal structures of E2-25K M172A mutant protein at pH 6.5 and pH 8.5 were determined to 1.9 and 2.2 A resolution, respectively. Examination of the structures revealed domain-domain interactions between the UBC and UBA domains which have not previously been reported.
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