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MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and
Duolin Wang1,2, Dongpeng Liu2, Jiakang Yuchi2
1Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.
Nucleic Acids Research
|April 24, 2020
Summary
MusiteDeep offers a fast, deep-learning tool for predicting protein post-translational modification (PTM) sites using only protein sequences. This updated framework enhances prediction accuracy and visualizes multiple PTMs simultaneously, aiding in the analysis of PTM cross-talks.
Area of Science:
- Computational Biology
- Bioinformatics
- Molecular Biology
Background:
- Protein post-translational modifications (PTMs) are crucial for cellular functions.
- Accurate prediction of PTM sites is essential for understanding protein regulation.
- Existing methods often require complex features or extensive computation.
Purpose of the Study:
- To present an updated deep-learning framework, MusiteDeep, for efficient PTM site prediction and visualization.
- To enable simultaneous prediction and analysis of multiple PTMs and potential cross-talks.
- To provide an interactive platform for reviewing predicted PTM sites with known annotations and 3D structures.
Main Methods:
- Utilized advanced ensemble techniques within a deep-learning framework.
- Developed a webserver accepting only protein sequences for PTM site prediction.
- Integrated homology-based search for PTM site visualization against known annotations and structures.
- Maintained a downloadable database of pre-processed PTM annotations from UniProt/Swiss-Prot.
Main Results:
- Achieved real-time prediction for large protein sets, processing 1000 sequences in under three minutes per PTM type.
- Demonstrated competitive performance in PTM site prediction, validated by external benchmarking.
- Enabled simultaneous prediction and visualization of multiple PTMs, facilitating PTM cross-talk analysis.
- Provided interactive tools for exploring predicted PTM sites in context with structural and functional data.
Conclusions:
- MusiteDeep provides a highly efficient and accurate platform for PTM site prediction and analysis.
- The updated framework supports simultaneous multi-PTM analysis and PTM cross-talk investigation.
- The integrated database and visualization tools enhance the utility for researchers studying protein modifications.
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