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Updated: Jun 17, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
PreDisorder: ab initio sequence-based prediction of protein disordered regions
Xin Deng1, Jesse Eickholt, Jianlin Cheng
1Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA. xd9d3@mail.missouri.edu
PreDisorder is a new server for predicting protein disordered regions. It uses an ab initio method and performs comparably to top predictors, enabling genomic-scale analysis.
Area of Science:
- Biochemistry and Molecular Biology
- Bioinformatics and Computational Biology
Background:
- Protein disordered regions lack stable structures but are crucial for protein expression and function.
- Accurate prediction of these regions is vital for protein structure prediction, determination, and function annotation.
Purpose of the Study:
- To introduce PreDisorder, a novel computational server for predicting protein disordered regions.
- To evaluate the performance of PreDisorder against existing protein disorder prediction methods.
Main Methods:
- The PreDisorder server is based on the MULTICOM-CMFR ab initio prediction method.
- Performance was benchmarked against 26 other predictors using the CASP8 dataset and various accuracy measures.
Main Results:
- PreDisorder demonstrated favorable performance compared to other ab initio methods.
- Its accuracy was found to be comparable to leading meta and clustering prediction methods.
Conclusions:
- PreDisorder offers a fast and reliable solution for predicting protein disordered regions at a genomic scale.
- The server is accessible online for researchers to utilize.
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