SeqCP: A sequence-based algorithm for searching circularly permuted proteins

Chi-Chun Chen; Yu-Wei Huang; Hsuan-Cheng Huang; Wei-Cheng Lo; Ping-Chiang Lyu

doi:10.1016/j.csbj.2022.11.024

SeqCP: A sequence-based algorithm for searching circularly permuted proteins

Comput Struct Biotechnol J. 2022 Nov 14:21:185-201. doi: 10.1016/j.csbj.2022.11.024. eCollection 2023.

Authors

Chi-Chun Chen^{1

2}, Yu-Wei Huang³, Hsuan-Cheng Huang^{1

4}, Wei-Cheng Lo^{3

5

6}, Ping-Chiang Lyu²

Affiliations

¹ Bioinformatics Program, Institute of Information Science, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.
² Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu 300, Taiwan.
³ Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan.
⁴ Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei 112, Taiwan.
⁵ Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan.
⁶ The Center for Bioinformatics Research, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.

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/.

Keywords: AUC, area under the ROC curve; CE, combinatorial extension; CE-CP, CE with Circular Permutations; CP, circular permutation; CPDB, Circular Permutation Database; CPMs, circular permutants; CPSARST, Circular Permutation Search Aided by Ramachandran Sequential Transformation; Circular permutants; Circular permutation; MCC, Matthews correlation coefficient; Protein sequence analysis; Protein structure modeling; RMSD, root-mean-square distance; ROC, receiver operating characteristic.