{"title":"25年的蛋白质块之旅:揭示结构字母表的多功能性。","authors":"Bernard Offmann, Alexandre G de Brevern","doi":"10.1016/j.biochi.2025.08.007","DOIUrl":null,"url":null,"abstract":"<p><p>Protein Blocks (PBs) represent a widely used structural alphabet that enables the approximation and analysis of local protein conformations through 16 prototype fragments defined by dihedral angles. Initially developed to overcome the limitations of classical secondary structure definitions, PBs provide a powerful tool for understanding protein structure, dynamics, and function. Their applications span structural annotation, protein fold superimposition and recognition, sequence-based prediction and molecular dynamics analysis. Notably, PBs facilitate the distinction between rigid, flexible, and disordered regions via an entropy-based index (N<sub>eq</sub>), offering insights into protein flexibility and intrinsic disorder. Their integration with deep learning has dramatically improved predictive performance, and their utility has been demonstrated in diverse contexts such as integrin polymorphisms, V<sub>H</sub>H variability and AlphaFold structure analysis. As a robust and adaptable framework, PBs remain central in modern structural bioinformatics.</p>","PeriodicalId":93898,"journal":{"name":"Biochimie","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A 25-year journey with protein blocks: Unveiling the versatility of a structural alphabet.\",\"authors\":\"Bernard Offmann, Alexandre G de Brevern\",\"doi\":\"10.1016/j.biochi.2025.08.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Protein Blocks (PBs) represent a widely used structural alphabet that enables the approximation and analysis of local protein conformations through 16 prototype fragments defined by dihedral angles. Initially developed to overcome the limitations of classical secondary structure definitions, PBs provide a powerful tool for understanding protein structure, dynamics, and function. Their applications span structural annotation, protein fold superimposition and recognition, sequence-based prediction and molecular dynamics analysis. Notably, PBs facilitate the distinction between rigid, flexible, and disordered regions via an entropy-based index (N<sub>eq</sub>), offering insights into protein flexibility and intrinsic disorder. Their integration with deep learning has dramatically improved predictive performance, and their utility has been demonstrated in diverse contexts such as integrin polymorphisms, V<sub>H</sub>H variability and AlphaFold structure analysis. As a robust and adaptable framework, PBs remain central in modern structural bioinformatics.</p>\",\"PeriodicalId\":93898,\"journal\":{\"name\":\"Biochimie\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biochimie\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.biochi.2025.08.007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochimie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.biochi.2025.08.007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A 25-year journey with protein blocks: Unveiling the versatility of a structural alphabet.
Protein Blocks (PBs) represent a widely used structural alphabet that enables the approximation and analysis of local protein conformations through 16 prototype fragments defined by dihedral angles. Initially developed to overcome the limitations of classical secondary structure definitions, PBs provide a powerful tool for understanding protein structure, dynamics, and function. Their applications span structural annotation, protein fold superimposition and recognition, sequence-based prediction and molecular dynamics analysis. Notably, PBs facilitate the distinction between rigid, flexible, and disordered regions via an entropy-based index (Neq), offering insights into protein flexibility and intrinsic disorder. Their integration with deep learning has dramatically improved predictive performance, and their utility has been demonstrated in diverse contexts such as integrin polymorphisms, VHH variability and AlphaFold structure analysis. As a robust and adaptable framework, PBs remain central in modern structural bioinformatics.