AlphaPPIweb: an integration platform for protein-protein interaction prediction and evaluation.

Area of Science:

• Structural biology
• Computational biology
• Bioinformatics

Background:

• AlphaFold and AlphaFold-Multimer significantly advanced protein structure prediction.
• Existing tools for protein complex prediction have limitations in usability and post-prediction analysis.

Purpose of the Study:

• To introduce AlphaPPIweb, a web platform leveraging AlphaPulldown for predicting protein complex structures.
• To streamline the analysis of protein-protein interactions and interface residues.

Main Methods:

• Utilizing AlphaPulldown, an AlphaFold-Multimer-based tool, within a user-friendly web interface.
• Inputting amino acid sequences for automated 3D structure generation and confidence scoring.
• Implementing automated interface residue analysis post-prediction.

Main Results:

• AlphaPPIweb provides accurate 3D structural predictions for protein complexes.
• The platform visualizes results and offers confidence scores for predictions.
• Automated analysis identifies potential ligand-receptor interactions and interface residues.

Conclusions:

• AlphaPPIweb enhances the usability of advanced structural prediction tools for biomedical and educational applications.
• The platform democratizes access to protein complex structure prediction and analysis.
• AlphaPPIweb facilitates deeper understanding of protein interactions within the research community.