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Application of PROSPECT in CASP4: characterizing protein structures with new folds
D Xu1, O H Crawford, P F LoCascio
1Computational Biology Section, Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830-6480, USA. xud@ornl.gov
Proteins
|February 9, 2002
Summary
The PROSPECT tool accurately predicted protein structures in the CASP4 experiment. It excels at identifying new protein folds and can aid in ab initio structure prediction.
Area of Science:
- Computational Biology
- Structural Bioinformatics
- Protein Structure Prediction
Background:
- The Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiments are crucial for evaluating protein structure prediction methods.
- Accurate protein structure prediction is essential for understanding protein function and designing new therapeutics.
Purpose of the Study:
- To evaluate the performance of the PROSPECT threading application in the CASP4 experiment.
- To assess PROSPECT's capabilities in comparative modeling, fold recognition, and new fold prediction.
Main Methods:
- PROSPECT utilizes a threading approach with a general energy function and pairwise contact potential for sequence-structure alignment.
- Reliability of predictions is assessed using a neural network approach.
- PROSPECT is integrated into the Genomic Integrated Supercomputing Toolkit (GIST) and deployed on terascale computing resources.
Main Results:
- PROSPECT predicted all 43 targets in CASP4.
- In fold recognition, PROSPECT correctly identified 8 out of 22 targets, ranking sixth among 127 groups.
- For new fold predictions, PROSPECT identified significant structural features for most targets, demonstrating top-tier performance.
Conclusions:
- PROSPECT is a powerful tool for rapid characterization of novel protein folds.
- The method shows potential for providing valuable structural restraints for ab initio prediction techniques.