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SeqCP: A sequence-based algorithm for searching circularly permuted proteins
Chi-Chun Chen1,2, Yu-Wei Huang3, Hsuan-Cheng Huang1,4
1Bioinformatics Program, Institute of Information Science, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.
Computational and Structural Biotechnology Journal
|December 30, 2022
Summary
SeqCP identifies circular permutation (CP) in proteins using sequence alignments, advancing protein studies and bioengineering. This method helps find circularly permuted protein pairs (CPMs) even without structural data.
Area of Science:
- Proteomics
- Bioinformatics
- Structural Biology
Background:
- Circular permutation (CP) rearranges protein termini, often preserving structure and function.
- Current CP detection relies heavily on protein structures, limiting identification for proteins lacking structural data.
Purpose of the Study:
- To develop an efficient sequence-based method for identifying circularly permuted protein pairs (CPMs).
- To overcome limitations of structure-based methods for CP detection, especially for proteins with unknown structures.
Main Methods:
- Developed SeqCP, a sequence-based algorithm analyzing normal and duplicated sequence alignments.
- Trained SeqCP using data from the Circular Permutation Database.
- Tested SeqCP on nonredundant datasets from the Protein Data Bank.
Main Results:
- SeqCP demonstrates high reliability in identifying CPMs.
- Achieved an Area Under the Curve (AUC) of 0.9, indicating strong performance.
- Identified candidate CP sites within protein sequences.
Conclusions:
- SeqCP offers a valuable tool for discovering CPMs using only sequence information.
- This method facilitates functional annotation and bioengineering applications for proteins lacking structural data.
- A web server for SeqCP is available at http://pcnas.life.nthu.edu.tw/SeqCP/.
Keywords:
AUC, area under the ROC curveCE, combinatorial extensionCE-CP, CE with Circular PermutationsCP, circular permutationCPDB, Circular Permutation DatabaseCPMs, circular permutantsCPSARST, Circular Permutation Search Aided by Ramachandran Sequential TransformationCircular permutantsCircular permutationMCC, Matthews correlation coefficientProtein sequence analysisProtein structure modelingRMSD, root-mean-square distanceROC, receiver operating characteristic
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