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Protein and Protein Structure

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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
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Updated: Jan 21, 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

Integrating ab initio and template-based algorithms for protein-protein complex structure prediction.

Sweta Vangaveti¹, Thom Vreven¹, Yang Zhang²

¹Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA.

Bioinformatics (Oxford, England)

|August 9, 2019

Summary

This summary is machine-generated.

Combining template-based and template-free methods improves protein-protein complex structure prediction. The new ZING method integrates SPRING and ZDOCK predictions, achieving higher success rates than individual approaches.

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Area of Science:

Computational biology
Structural bioinformatics
Protein structure prediction

Background:

Template-based and template-free methods are established for protein-protein complex structure prediction.
Each method has limitations: template-based requires known structures, while template-free is for novel interfaces.

Purpose of the Study:

To enhance computational protein-protein complex structure prediction.
To combine strengths of template-based and template-free modeling approaches.

Main Methods:

Developed ZING, a method integrating SPRING (template-based) and ZDOCK (template-free).
Employed a statistics-based approach to evaluate and combine predictions.
Validated using the protein-protein docking benchmark version 5.0.

Main Results:

ZING achieved a 68.2% success rate, outperforming SPRING (52.1%) and ZDOCK (35.9%) for top 10 predictions.
The integrated approach demonstrated superior performance compared to individual methods.

Conclusions:

A statistics-based integration of template-based and template-free predictions significantly improves accuracy.
ZING offers a more successful strategy for computational protein-protein complex structure prediction.