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Template-free modeling by LEE and LEER in CASP11
InSuk Joung1,2, Sun Young Lee1, Qianyi Cheng1,2
1Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea.
Proteins
|October 17, 2015
Summary
We developed LEE and LEER modeling protocols for template-free protein structure prediction. These methods efficiently screen existing models to generate accurate three-dimensional protein structures, outperforming input templates.
Area of Science:
- Computational Biology
- Structural Biology
- Bioinformatics
Background:
- Protein structure prediction is crucial for understanding biological function.
- Template-based modeling is a common approach, but novel targets pose challenges.
Purpose of the Study:
- To develop and evaluate novel template-free modeling protocols for human targets in CASP11.
- To improve the accuracy of three-dimensional (3D) protein structure modeling.
Main Methods:
- Utilized LEE and LEER protocols for template-free modeling.
- Employed server model clustering and community detection for template selection.
- Integrated selected templates with energy terms for 3D model construction.
- Rebuilt side-chains using consensus and rotamer libraries.
- Refined models using restrained molecular dynamics simulations (LEER).
Main Results:
- The LEE protocol achieved efficient server model screening, with selected models comparable to top 30% server models.
- Generated 3D models with better backbone accuracy than input template models in 10 out of 24 cases.
- LEER models showed improved physical realism and stereochemistry compared to LEE models.
- LEE models outperformed average template models in backbone structure and side-chain orientation.
Conclusions:
- The LEE protocol's success stems from efficient model screening and effective energy function optimization.
- LEER models offer enhanced physical realism and stereochemical quality.
- These protocols provide a robust approach for template-free protein structure prediction.
