Gradations in protein dynamics captured by experimental NMR are not well represented by AlphaFold2 models and other computational metrics

[Display omitted] •AlphaFold2’s pLDDT can differentiate between ordered or disordered residues.•AlphaFold2’s pLDDT does not reflect gradations on residue dynamics.•Biases in the training sets result in predicted rigidity of flexible regions.•Conformational diversity in NMR ensembles is associated wi...

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Veröffentlicht in:Journal of molecular biology Jg. 437; H. 2; S. 168900
Hauptverfasser: Gavalda-Garcia, Jose, Dixit, Bhawna, Díaz, Adrián, Ghysels, An, Vranken, Wim
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Netherlands Elsevier Ltd 15.01.2025
Schlagworte:
AlphaFold2
Computational Biology - methods
large-scale analysis
Magnetic Resonance Spectroscopy - methods
Molecular Dynamics Simulation
nuclear magnetic resonance
Nuclear Magnetic Resonance, Biomolecular - methods
Protein Conformation
protein dynamics
Protein Folding
Proteins - chemistry
structural biology
structural biology
nuclear magnetic resonance
large-scale analysis
protein dynamics
AlphaFold2
ISSN:0022-2836, 1089-8638, 1089-8638
Online-Zugang:Volltext
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Zusammenfassung:[Display omitted] •AlphaFold2’s pLDDT can differentiate between ordered or disordered residues.•AlphaFold2’s pLDDT does not reflect gradations on residue dynamics.•Biases in the training sets result in predicted rigidity of flexible regions.•Conformational diversity in NMR ensembles is associated with lower pLDDT values. The advent of accurate methods to predict the fold of proteins initiated by AlphaFold2 is rapidly changing our understanding of proteins and helping their design. However, these methods are mainly trained on protein structures determined with X-ray diffraction, where the protein is packed in crystals at often cryogenic temperatures. They can therefore only reliably cover well-folded parts of proteins that experience few, if any, conformational changes. Experimentally, solution nuclear magnetic resonance (NMR) is the experimental method of choice to gain insight into protein dynamics at near physiological conditions. Computationally, methods such as molecular dynamics (MD) simulations and Normal Mode Analysis (NMA) allow the estimation of a protein’s intrinsic flexibility based on a single protein structure. This work addresses, on a large scale, the relationships for proteins between the AlphaFold2 pLDDT metric, the observed dynamics in solution from NMR metrics, interpreted MD simulations, and the computed dynamics with NMA from single AlphaFold2 models and NMR ensembles. We observe that these metrics agree well for rigid residues that adopt a single well-defined conformation, which are clearly distinct from residues that exhibit dynamic behavior and adopt multiple conformations. This direct order/disorder categorisation is reflected in the correlations observed between the parameters, but becomes very limited when considering only the likely dynamic residues. The gradations of dynamics observed by NMR in flexible protein regions are therefore not represented by these computational approaches. Our results are interactively available for each protein from https://bio2byte.be/af_nmr_nma/.
Bibliographie:ObjectType-Article-1
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content type line 23
ISSN:0022-2836
1089-8638
1089-8638
DOI:10.1016/j.jmb.2024.168900