{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:46:10Z","timestamp":1753875970780,"version":"3.41.2"},"reference-count":16,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T00:00:00Z","timestamp":1680480000000},"content-version":"vor","delay-in-days":92,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Recent improvements in computational and experimental techniques for obtaining protein structures have resulted in an explosion of 3D coordinate data. To cope with the ever-increasing sizes of structure databases, this work proposes the Protein Data Compression (PDC) format, which compresses coordinates and temperature factors of full-atomic and C\u03b1-only protein structures. Without loss of precision, PDC results in 69% to 78% smaller file sizes than Protein Data Bank (PDB) and macromolecular Crystallographic Information File (mmCIF) files with standard GZIP compression. It uses \u223c60% less space than existing compression algorithms specific to macromolecular structures. PDC optionally performs lossy compression with minimal sacrifice of precision, which allows reduction of file sizes by another 79%. Conversion between PDC, mmCIF and PDB formats is typically achieved within 0.02\u2009s. The compactness and fast reading\/writing speed of PDC make it valuable for storage and analysis of large quantity of tertiary structural data.<\/jats:p><jats:p>Database URL https:\/\/github.com\/kad-ecoli\/pdc<\/jats:p>","DOI":"10.1093\/database\/baad018","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T14:00:01Z","timestamp":1680530401000},"source":"Crossref","is-referenced-by-count":1,"title":["PDC: a highly compact file format to store protein 3D coordinates"],"prefix":"10.1093","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7290-1324","authenticated-orcid":false,"given":"Chengxin","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Computational Medicine and Bioinformatics, University of Michigan , 100 Washtenaw Av, Ann Arbor, MI 48109, USA"},{"name":"Howard Hughes Medical Institute , 4000 Jones Bridge Rd, Chevy Chase, MD 20815, USA"},{"name":"Department of Molecular, Cellular, and Developmental Biology, Yale University , 266 Whitney Av, New Haven, CT 06511, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna Marie","family":"Pyle","sequence":"additional","affiliation":[{"name":"Howard Hughes Medical Institute , 4000 Jones Bridge Rd, Chevy Chase, MD 20815, USA"},{"name":"Department of Molecular, Cellular, and Developmental Biology, Yale University , 266 Whitney Av, New Haven, CT 06511, USA"},{"name":"Department of Chemistry, Yale University , 225 Prospect St, New Haven, CT 06511, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,4,3]]},"reference":[{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1038\/s41586-021-03819-2","article-title":"Highly accurate protein structure prediction with AlphaFold","volume":"596","author":"Jumper","year":"2021","journal-title":"Nature"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1126\/science.abj8754","article-title":"Accurate prediction of protein structures and interactions using a three-track neural network","volume":"373","author":"Baek","year":"2021","journal-title":"Science"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"1734","DOI":"10.1002\/prot.26193","article-title":"Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14","volume":"89","author":"Zheng","year":"2021","journal-title":"Proteins"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"D439","DOI":"10.1093\/nar\/gkab1061","article-title":"AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models","volume":"50","author":"Varadi","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"2023040313595136000_","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1008247","article-title":"BinaryCIF and CIFTools-Lightweight, efficient and extensible macromolecular data management","volume":"16","author":"Sehnal","year":"2020","journal-title":"PLoS Comput. 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Biol."},{"key":"2023040313595136000_","doi-asserted-by":"crossref","DOI":"10.1101\/2022.01.20.477098","article-title":"Image-centric compression of protein structures improves space savings","volume-title":"bioRxiv","author":"Staniscia","year":"2022"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0174846","article-title":"Towards an efficient compression of 3D coordinates of macromolecular structures","volume":"12","author":"Valasatava","year":"2017","journal-title":"PLoS One"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1016\/j.str.2011.03.019","article-title":"A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions","volume":"19","author":"Shapovalov","year":"2011","journal-title":"Structure"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","DOI":"10.7717\/peerj.80","article-title":"PeptideBuilder: a simple Python library to generate model peptides","volume":"1","author":"Tien","year":"2013","journal-title":"PeerJ."},{"key":"2023040313595136000_","first-page":"922","article-title":"A solution for the best rotation to relate two sets of vectors. Acta Crystallographica Section\u00a0A: crystal physics, diffraction","volume":"32","author":"Kabsch","year":"1976","journal-title":"Theor. Gen. Crystallogr."},{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"2937","DOI":"10.1093\/bioinformatics\/btac207","article-title":"AMIGOS III: pseudo-torsion angle visualization and motif-based structure comparison of nucleic acids","volume":"38","author":"Shine","year":"2022","journal-title":"Bioinformatics"},{"key":"2023040313595136000_","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/S0022-2836(63)80023-6","article-title":"Stereochemistry of polypeptide chain configurations","volume":"7","author":"Ramachandran","year":"1963","journal-title":"J. Mol. 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