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Updated: Feb 24, 2026

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: making AWSEM AWSEM-ER by adding evolutionary restraints.

Brian J Sirovetz^1,2, Nicholas P Schafer¹, Peter G Wolynes^1,2,3,4

¹Center for Theoretical Biological Physics, Rice University, Houston, Texas.

|August 12, 2017

Summary

This summary is machine-generated.

This study introduces AWSEM-ER, a new protein structure prediction method that combines evolutionary data with physics-based modeling. AWSEM-ER significantly improves protein structure prediction accuracy, especially for large protein families.

Keywords:

coevolution contact prediction energy landscape theory hybrid model knowledge-based model physically motivated potential sequence covariation

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Area of Science:

Computational Biology
Biophysics
Structural Biology

Background:

Protein sequences evolve into functional structures, leading to families with shared folds.
Coevolutionary information from protein families can predict residue contacts.
Physics-based protein models like AWSEM are used for structure prediction.

Purpose of the Study:

To improve protein structure prediction by integrating coevolutionary information with a physics-based force field.
To develop a novel computational model, AWSEM-ER, for enhanced de novo protein structure prediction.

Main Methods:

Combined coevolutionary information from protein sequence families with the Associative memory, Water mediated, Structure and Energy Model (AWSEM).
Developed the Associative memory, Water mediated, Structure and Energy Model with Evolutionary Restraints (AWSEM-ER).
Analyzed free energy landscapes to understand prediction improvements.

Main Results:

AWSEM-ER significantly improves protein structure prediction quality compared to AWSEM using single sequences.
Improvement is notable when a sufficient number of homologous sequences are available.
Evolutionary term shifts free energy minimum towards native-like structures, enhancing simulated annealing predictions.

Conclusions:

AWSEM-ER enhances de novo protein structure prediction accuracy by incorporating evolutionary data.
The improved model facilitates functional studies of proteins lacking experimentally determined structures.
This approach opens new avenues for understanding protein folding and function.