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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

Protein structure prediction using Rosetta in CASP12.

Sergey Ovchinnikov^1,2, Hahnbeom Park^1,2, David E Kim^2,3

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

|September 24, 2017

Summary

This summary is machine-generated.

Rosetta structure predictions in CASP12 showed that previously generated models can serve as excellent starting points for comparative modeling. Expert intervention and refinement techniques further improved protein structure prediction accuracy.

Keywords:

Rosetta ab initio prediction co-evolution protein structure prediction refinement

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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

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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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Computational Biology
Structural Biology
Biophysics

Background:

Accurate protein structure prediction is crucial for understanding biological function.
The Protein Structure Initiative aimed to provide structural models for protein families lacking experimental data.
Co-evolution based contact predictions offer valuable insights for guiding protein modeling.

Purpose of the Study:

To evaluate the performance of Rosetta in CASP12 free modeling and refinement categories.
To assess the utility of pre-generated Rosetta models as starting points for comparative modeling.
To investigate the impact of expert intervention and all-atom refinement on structure prediction accuracy.

Main Methods:

Utilized Rosetta software for protein structure prediction in CASP12.
Employed co-evolution based contact predictions to guide model generation.
Applied Rosetta all-atom refinement and molecular dynamics (MD) simulations.
Incorporated expert intervention for specific challenging targets.

Main Results:

Pre-generated Rosetta models served as superior starting points for comparative modeling compared to known crystal structures for several targets.
Expert intervention significantly improved predictions for six targets, notably T0886 by correctly identifying discontinuous domains.
Rosetta all-atom refinement followed by MD simulations yielded consistent small improvements for near-native models and larger, less consistent improvements for distant models.

Conclusions:

Previously generated Rosetta models are valuable resources for protein structure prediction, contributing to the goals of the Protein Structure Initiative.
Expert human insight combined with computational tools can enhance protein structure prediction accuracy.
Refinement strategies like all-atom refinement and MD simulations offer incremental improvements in structure prediction quality.