{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T03:58:33Z","timestamp":1790308713738,"version":"4.1.0"},"reference-count":48,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Proteins"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>A straightforward method for the determination of dynamic domains from pairs of conformations or general conformational ensembles of proteins is presented. The method applies metric multi\u2010dimensional scaling (MDS) to distance\u2010differences or root\u2010mean square\u2010fluctuations of inter\u2010atomic distances (RMSFIDs). The approach determines points in a low\u2010dimensional space, each representing an amino\u2010acid residue, where distances between the points give an approximation to the distance\u2010differences, in the case of a pair of conformations, or RMSFIDs for an ensemble. This point\u2010based representation enables top\u2010down clustering methods to be used to determine dynamic domains. The two implementations, Pair\u2010DD and Ensemble\u2010DD, are demonstrated on idealized examples where domains move as perfect rigid bodies, on conformational pairs and ensembles derived from X\u2010ray structures both monomeric and multimeric, and on trajectories derived from simulation methods. A parameter is proposed which can be used as a threshold for acceptance of dynamic domains to enable automatic assignment. The results show excellent correspondence with a well\u2010established approach, but the method has the added advantage of being versatile in that it is applicable to both a pair of structures and an ensemble of conformations. Furthermore, for a pair of conformations, a one\u2010dimensional MDS coordinate seems to be sufficient, meaning that the degree of association of a residue with a dynamic domain can be visualized in a simple plot.<\/jats:p>","DOI":"10.1002\/prot.70176","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T03:02:32Z","timestamp":1790305352000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Method for the Determination of Dynamic Domains in Proteins From Structural Pairs and Conformational Ensembles"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6959-2604","authenticated-orcid":false,"given":"Steven","family":"Hayward","sequence":"first","affiliation":[{"name":"Computational Biology Group School of Computing Sciences, University East Anglia  Norwich UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"issue":"1","key":"e_1_2_9_2_1","first-page":"D376","article-title":"The SCOP Database in 2020: Expanded Classification of Representative Family and Superfamily Domains of Known Protein Structures","volume":"48","author":"Andreeva A.","year":"2019","journal-title":"Nucleic Acids Research"},{"issue":"1","key":"e_1_2_9_3_1","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1093\/nar\/gkg062","article-title":"The CATH Database: An Extended Protein Family Resource for Structural and Functional Genomics","volume":"31","author":"Pearl F. 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