Predicted structural proteome of Sphagnum divinum and proteome-scale annotation

Area of Science:

• * Structural biology
• * Bioinformatics
• * Peatland ecology

Background:

• * Sphagnum-dominated peatlands are crucial terrestrial carbon sinks.
• * The genus Sphagnum is undersampled, with limited structural data in public databases.
• * Accurate protein structure prediction tools are needed to analyze Sphagnum proteomes.

Purpose of the Study:

• * To generate the predicted structural proteome of Sphagnum divinum.
• * To enable structure-based functional annotation of Sphagnum proteins.
• * To provide computational tools for proteome-scale analysis.

Main Methods:

• * Computation of the Sphagnum divinum proteome using AlphaFold (25,134 primary transcripts).
• * Structural alignment of high-confidence models against a crystallographic database (>90,000 structures).
• * Structure-based classification of putative Enzyme Commission (EC) numbers.

Main Results:

• * Generation of a comprehensive predicted structural proteome for Sphagnum divinum.
• * Identification of structural similarities and functional annotations for Sphagnum proteins.
• * Development of a computational method for proteome-scale structure-based annotation.

Conclusions:

• * The predicted structural proteome provides a valuable resource for Sphagnum research.
• * This work facilitates functional and evolutionary studies of Sphagnum.
• * Open data access promotes further investigation into peatland ecosystems.