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SeqCP: A sequence-based algorithm for searching circularly permuted proteins.
Chen, Chi-Chun; Huang, Yu-Wei; Huang, Hsuan-Cheng; Lo, Wei-Cheng; Lyu, Ping-Chiang.
Afiliación
  • Chen CC; Bioinformatics Program, Institute of Information Science, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.
  • Huang YW; Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu 300, Taiwan.
  • Huang HC; Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan.
  • Lo WC; Bioinformatics Program, Institute of Information Science, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.
  • Lyu PC; Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei 112, Taiwan.
Comput Struct Biotechnol J ; 21: 185-201, 2023.
Article en En | MEDLINE | ID: mdl-36582435
ABSTRACT
Circular permutation (CP) is a protein sequence rearrangement in which the amino- and carboxyl-termini of a protein can be created in different positions along the imaginary circularized sequence. Circularly permutated proteins usually exhibit conserved three-dimensional structures and functions. By comparing the structures of circular permutants (CPMs), protein research and bioengineering applications can be approached in ways that are difficult to achieve by traditional mutagenesis. Most current CP detection algorithms depend on structural information. Because there is a vast number of proteins with unknown structures, many CP pairs may remain unidentified. An efficient sequence-based CP detector will help identify more CP pairs and advance many protein studies. For instance, some hypothetical proteins may have CPMs with known functions and structures that are informative for functional annotation, but existing structure-based CP search methods cannot be applied when those hypothetical proteins lack structural information. Despite the considerable potential for applications, sequence-based CP search methods have not been well developed. We present a sequence-based method, SeqCP, which analyzes normal and duplicated sequence alignments to identify CPMs and determine candidate CP sites for proteins. SeqCP was trained by data obtained from the Circular Permutation Database and tested with nonredundant datasets from the Protein Data Bank. It shows high reliability in CP identification and achieves an AUC of 0.9. SeqCP has been implemented into a web server available at http//pcnas.life.nthu.edu.tw/SeqCP/.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Año: 2023 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Año: 2023 Tipo del documento: Article País de afiliación: Taiwán