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Generalized comparative modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling
A Kolinski1, M R Betancourt, D Kihara
1Laboratory of Computational Genomics, Donald Danforth Plant Science Center, St. Louis, Missouri 63141, USA.
Proteins
|June 8, 2001
Summary
A new computational method, GENECOMP, refines protein threading models. This approach uses ab initio folding and structure selection protocols, improving model accuracy on benchmark datasets.
Area of Science:
- Computational biology
- Structural bioinformatics
- Protein modeling
Background:
- Protein threading is crucial for predicting protein structures.
- Existing threading methods require refinement for accuracy.
- Ab initio folding and structure selection are key components in computational protein modeling.
Purpose of the Study:
- To develop and validate an improved generalized comparative modeling method (GENECOMP).
- To refine protein threading models using ab initio folding and advanced structure selection protocols.
- To assess the performance of GENECOMP on a standard benchmark dataset.
Main Methods:
- Development of the GENECOMP method integrating PROSPECTOR threading and SICHO ab initio folding.
- Utilizing distance geometry and clustering for structure selection protocols.
- Validation on the Fischer database comprising 68 probe-template pairs.
Main Results:
- GENECOMP refines threading models, showing significant improvements in structure quality.
- Clustering protocol generally yields better structures compared to distance geometry.
- The method demonstrates robustness, improving upon initial threading models in numerous cases.
Conclusions:
- GENECOMP offers an effective approach for refining protein threading models.
- The integration of ab initio folding and structure selection enhances prediction accuracy.
- The method is automatable and scalable for genomic applications.