Protein structure prediction in CASP6 using CHIMERA and FAMS

Area of Science:

• Computational biology
• Structural bioinformatics
• Protein structure prediction

Background:

• The Critical Assessment of protein Structure Prediction (CASP) is a community-wide experiment to assess the accuracy of protein structure prediction methods.
• Homology modeling and fold recognition are key approaches in protein structure prediction.

Purpose of the Study:

• To introduce and evaluate the SKE-CHIMERA system used by the CHIMERA group in the CASP6 competition.
• To analyze the performance of the CHIMERA group's prediction methods, focusing on successes and failures.

Main Methods:

• Utilized SKE-CHIMERA, a web-user interface system for protein structure prediction incorporating human intervention.
• Employed an iterative approach combining manual steps (template selection and alignment via CHIMERA) and automatic steps (3D model building via FAMS).
• Leveraged extensive internal and publicly available data for model generation.

Main Results:

• The CHIMERA group was identified as one of the most successful predictors in CASP6.
• Demonstrated particular strength in homology modeling, specifically for Fold Recognition/Homologous (FR/H) targets.
• The SKE-CHIMERA system facilitated effective human intervention in the prediction process.

Conclusions:

• The SKE-CHIMERA system, with its hybrid manual-automatic approach, proved effective for protein structure prediction.
• The CHIMERA group's performance highlights the value of integrating human expertise with automated tools in structural bioinformatics.
• Analysis of CASP6 results provides insights into the strengths and limitations of the employed prediction strategies.