Protinfo PPC: a web server for atomic level prediction of protein complexes

Area of Science:

• Structural bioinformatics
• Computational biology
• Protein structure prediction

Background:

• Understanding protein-protein interactions is crucial for deciphering biological processes.
• Predicting the structure of protein complexes is a challenging but essential task in structural biology.

Purpose of the Study:

• To introduce Protinfo PPC, a novel web server for predicting atomic-level structures of interacting proteins.
• To provide researchers with a tool for modeling protein complexes from amino acid sequences.

Main Methods:

• Utilizes the interolog method to identify homologous experimental protein complex structures.
• Employs these structures as templates for comparative modeling of query sequences.
• Supports modeling of both homo and hetero multimers.

Main Results:

• Generates full atomic-level models of protein complexes, including insertions/deletions.
• Models are produced with high accuracy, validated through rigorous benchmarking.
• Provides models in Protein Data Bank (PDB) format via email.

Conclusions:

• Protinfo PPC offers a fully automated, all-atom comparative modeling service for protein complexes.
• The server facilitates prediction of protein complex interactions and identification of interaction sites.
• This tool is valuable for researchers investigating protein-protein interactions and complex structures.