IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

Area of Science:

• Computational biology
• Structural bioinformatics
• Protein modeling

Background:

• Protein structure and function prediction are crucial for understanding biological processes.
• Accessing and interpreting complex protein modeling data can be challenging for life scientists.

Purpose of the Study:

• To describe major performance and user interface updates to the IntFOLD web server.
• To enhance accessibility of protein modeling data for a broader scientific audience.

Main Methods:

• Integration of leading methods for tertiary structure prediction, quality assessment, disorder prediction, domain prediction, function prediction, and protein-ligand interaction modeling.
• Development of a unified, intuitive web interface for simplified data visualization and interpretation.
• Utilizing amino acid sequence as the sole input for target proteins.

Main Results:

• The updated IntFOLD server provides a user-friendly platform for comprehensive protein modeling.
• Complex quantitative data is integrated and presented on a single page for at-a-glance interpretation.
• The server's pipeline has undergone independent validation through CASP and continuous evaluation by CAMEO.

Conclusions:

• The enhanced IntFOLD server improves accessibility and usability of advanced protein modeling tools.
• It empowers life scientists, including non-expert modelers, to interpret 3D modeling results effectively.
• The server represents a significant advancement in computational tools for structural and functional proteomics.