DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction.

Area of Science:

• Biochemistry
• Bioinformatics
• Computational Biology

Background:

• Intrinsic protein disorder is prevalent and crucial for cellular functions.
• Predicting protein disorder from sequences is feasible but challenging for multiple functions.
• Existing tools lack comprehensive coverage of various disorder-related functions.

Purpose of the Study:

• Introduce DEPICTER2, a webserver for predicting protein disorder and its functions.
• Provide convenient access to accurate and fast prediction methods.
• Integrate predictors for various disorder functions.

Main Methods:

• Developed the DEPICTER2 webserver.
• Integrated a state-of-the-art disorder predictor (flDPnn).
• Included five modern predictors for disordered linkers, protein, peptide, DNA, RNA, and lipid binding.

Main Results:

• DEPICTER2 offers a curated collection of disorder and disorder function predictors.
• The server allows selection of multiple prediction methods.
• Supports batch predictions for up to 25 proteins with interactive visualization.

Conclusions:

• DEPICTER2 provides a comprehensive resource for disorder and disorder function prediction.
• Facilitates research on the roles of intrinsically disordered proteins in biology.
• The webserver is freely accessible for the scientific community.