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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home.

Rhiju Das¹, Bin Qian, Srivatsan Raman

¹Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA.

|September 27, 2007

Summary

This summary is machine-generated.

Rosetta structure prediction achieved near-atomic accuracy for protein targets using aggressive sampling and all-atom refinement. This advance, powered by Rosetta@home, improved template-based and free modeling predictions, enhancing protein structure determination.

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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

Computational Biology
Structural Biology
Bioinformatics

Background:

Protein structure prediction is crucial for understanding biological function.
Accurate prediction of protein structures remains a significant challenge in bioinformatics.
The Critical Assessment of Techniques for Protein Structure Prediction (CASP) benchmarks prediction methodologies.

Purpose of the Study:

To evaluate the Rosetta structure prediction methodology in the Seventh CASP.
To assess the performance of template-based and free modeling approaches within Rosetta.
To demonstrate the impact of enhanced sampling and all-atom refinement on prediction accuracy.

Main Methods:

Utilized the Rosetta structure prediction software suite.
Employed aggressive sampling and all-atom refinement techniques.
Leveraged the Rosetta@home distributed computing network for computational power.

Main Results:

Rosetta@home enabled aggressive sampling and all-atom refinement for most targets.
Template-based modeling improved existing predictions for proteins <200 residues.
Free modeling achieved near-atomic accuracy for several small proteins (<100 residues).

Conclusions:

All-atom refinement is a powerful, albeit computationally intensive, method for accurate protein structure prediction.
Advances in computational resources, like Rosetta@home, are critical for pushing the boundaries of structure prediction.
Rosetta methodology shows significant promise for both template-based and de novo protein structure prediction.