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How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database,
Hiroto Anbo1, Koya Sakuma2, Satoshi Fukuchi1
1Faculty of Engineering, Maebashi Institute of Technology, Maebashi 371-0816, Japan.
Biology
|February 25, 2023
Summary
AlphaFold2 accurately models protein structures, including intrinsically disordered regions (IDRs). This study identifies features predicting disorder-to-order transitions in IDRs, crucial for understanding protein interactions.
Area of Science:
- Computational Biology
- Structural Biology
- Bioinformatics
Background:
- Accurate protein structure prediction is essential for understanding biological function.
- AlphaFold2 (AF2) provides reliable protein models, including intrinsically disordered regions (IDRs).
- Some IDRs transition from disordered to ordered states upon partner binding, a phenomenon captured by Protean Segments (ProSs) in the IDEAL database.
Purpose of the Study:
- To assess AlphaFold2 model structures for intrinsically disordered regions that undergo disorder-to-order transitions.
- To identify structural and sequential features predictive of these disorder-to-order transition regions (Protean Segments).
Main Methods:
- Non-redundant selection of Protean Segments (ProSs) from the IDEAL database.
- Classification of ProSs based on root mean square deviation to corresponding AlphaFold2 model regions.
- Statistical analysis to identify 11 predictive structural and sequential features.
Main Results:
- Identified two groups of predictive features for ProS structures.
- Features related to prediction confidence (pLDDT) indicated long alpha-helices or domains.
- Features related to normalized radius of gyration indicated short alpha-helices with terminal loops.
Conclusions:
- AlphaFold2's prediction reliability (pLDDT) and structural compactness (radius of gyration) can predict disorder-to-order transitions in intrinsically disordered regions.
- These findings enhance the utility of AF2 models for studying dynamic protein regions and interactions.
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