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Updated: Sep 14, 2025

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

Toward Modeling Protein Multimers by Combining AlphaFold 3 Predictions with Secondary Structures from

Changrui Li¹, Thu Nguyen¹, Willy Wriggers²

¹Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA.

Computational Structural Bioinformatics : International Workshop, CSBW 2024, Boston, MA, USA, November 16, 2024, Proceeding. Computational Structural Bioinformatics Workshop (2024 : Boston, Mass.)

|July 24, 2025

Summary

This summary is machine-generated.

AlphaFold 3 models show promise for protein structure prediction, accurately modeling domains and chains in cryo-electron microscopy maps. Cross-correlation scores effectively distinguish model accuracy, guiding future structural biology advancements.

Keywords:

AlphaFold Cryo-Electron Microscopy Fitting Protein Structure Secondary Structure Structure Validation

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Published on: January 31, 2022

Area of Science:

Structural Biology
Computational Biology
Biophysics

Background:

AlphaFold 3 (AF3) demonstrates enhanced accuracy in predicting protein multimer structures.
Fitting predicted models to medium-resolution cryo-electron microscopy (cryo-EM) maps (5-10 Å) presents challenges due to limited high-resolution features.

Purpose of the Study:

To evaluate the accuracy of AlphaFold 3 multimer models when fitted to medium-resolution cryo-EM maps.
To assess the utility of cross-correlation (CC) scores and secondary structure analysis for distinguishing model quality.

Main Methods:

A case study using four AF3 multimer models and corresponding 7-8 Å resolution cryo-EM maps.
Comparison of AF3 models with deposited atomic structures using TM-scores.
Analysis of cross-correlation (CC) scores between models and cryo-EM maps.
Secondary structure segmentation using the DeepSSETracer tool.

Main Results:

AF3 multimer models showed partial correctness, with accurate domains, secondary structures, and individual chains (16/17 chains had TM-scores > 0.5).
Some models exhibited inaccuracies in the relative positioning of chains or domains.
Cross-correlation (CC) scores correlated with TM-scores, indicating their sensitivity in distinguishing model quality when regions are correctly masked.
Major secondary structures (α-helices, β-sheets) were detectable in medium-resolution cryo-EM maps.

Conclusions:

AF3-predicted multimer models hold potential for integration with medium-resolution cryo-EM data.
Combining CC scores and secondary structure similarity can improve the assessment of AF3 model accuracy.
Further development is needed to refine model fitting and address domain/chain positioning errors in cryo-EM map interpretation.