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Updated: Sep 6, 2025

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

AlphaFold2 models indicate that protein sequence determines both structure and dynamics.

Hao-Bo Guo^1,2, Alexander Perminov^1,3, Selemon Bekele^1,2

¹Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson Air Force Base, 45433, OH, USA.

Scientific Reports

|June 23, 2022

Summary

This summary is machine-generated.

AlphaFold 2 (AF2) predicts protein structures and residue flexibility from amino acid sequences. AF2-derived scores correlate with molecular dynamics simulations, offering insights into protein dynamics.

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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

Area of Science:

Computational Biology
Structural Biology
Biophysics

Background:

AlphaFold 2 (AF2) revolutionized molecular biology by enabling structure and function prediction from primary sequences.
Understanding protein dynamics and residue flexibility is crucial for biological function.

Purpose of the Study:

To investigate if AlphaFold 2 predictions contain information beyond static 3D structures, specifically regarding protein residue flexibility.
To evaluate the correlation between AF2-derived metrics (pLDDT, PAE) and protein dynamics.

Main Methods:

AF2 structure predictions were performed for diverse protein systems, including globular proteins, multi-domain proteins, intrinsically disordered proteins (IDPs), and protein complexes.
Predicted Local Distance Difference (pLDDT) scores and Predicted Aligned Error (PAE) maps were analyzed.
PAE maps were compared with distance variation (DV) matrices from molecular dynamics (MD) simulations.
New "AF2-scores" derived from pLDDT were correlated with root mean square fluctuations (RMSF) from MD simulations.

Main Results:

AF2 predictions decode protein sequences into residue flexibilities using pLDDT and PAE.
PAE maps from AF2 correlate with MD-derived DV matrices, indicating predictive power for residue dynamics.
AF2-scores show high correlation with MD-derived RMSF for most proteins and complexes.
AF2-scores did not correlate well with MD-derived RMSF for an IDP and a randomized protein.

Conclusions:

AF2-predicted protein structures contain valuable information about residue flexibility and protein dynamics.
AF2-scores offer a computationally efficient proxy for estimating protein residue flexibility.
While powerful, AF2's ability to capture dynamics may be limited for intrinsically disordered or randomized proteins.