AlphaFold2 transmembrane protein structure prediction shines

Hegedüs, Tamás; Geisler, Markus; Lukacs, Gergely L.; Farkas, Bianka

doi:10.1101/2021.08.21.457196

Cited by 6 publications

(6 citation statements)

References 60 publications

(61 reference statements)

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“…These problems include the prediction of various protein interactions, such as protein-protein, protein-ligand and protein-DNA/RNA, and the prediction of the impact of mutations on protein stability. AlphaFold proved to be useful for experimental determination of protein structures with molecular replacement phasing [4,5] and already facilitated elucidation of SARS-Cov2 protein structures [6,7]. Next, AlphaFold in collaboration with EMBL-EBI constructed the structure models for the whole protein sequence space [8].…”

Section: Introductionmentioning

confidence: 99%

Using AlphaFold to predict the impact of single mutations on protein stability and function

Pak

Markhieva

Novikova³

et al. 2023

PLoS ONE

137

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AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is “solved”. However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted the pLDDT and <pLDDT> metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the same AlphaFold pLDDT metrics with the impact of a single mutation on structure using a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold may not be immediately applied to other problems or applications in protein folding.

show abstract

Section: Introductionmentioning

confidence: 99%

Using AlphaFold to predict the impact of single mutations on protein stability and function

Pak

Markhieva

Novikova³

et al. 2023

PLoS ONE

137

View full text Add to dashboard Cite

show abstract

“…These problems include the prediction of various protein interactions, such as protein-protein, proteinligand and protein-DNA/RNA, and the prediction of the impact of mutations on protein stability. AlphaFold proved to be useful for experimental determination of protein structures with molecular replacement phasing [4,5] and already facilitated elucidation of SARS-Cov2 protein structures [6,7]. Furthermore, AlphaFold in collaboration with EMBL-EBI launched a global initiative on constructing the structure models for the whole protein sequence space [8].…”

Section: Introductionmentioning

confidence: 99%

Using AlphaFold to predict the impact of single mutations on protein stability and function

Pak

Markhieva

Novikova³

et al. 2021

Preprint

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AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the AlphaFold predictions on the impact of a single mutation on structure with a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold cannot be immediately applied to other problems or applications in protein folding.

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“…AlphaFold2 is the new standard for ab-initio structural prediction, and in the 2020 Critical Assessment of protein Structure Prediction (CASP) global challenge, it outperformed any other structure prediction algorithm, including I-TASSER ( ). Furthermore, in a recent preprint ( 52 ), AlphaFold2 was shown to work well on structural prediction for membrane proteins, although the exercise focused mostly on alpha-helical membrane proteins, and additional analyses are necessary to establish the same benchmark for β-barrel proteins.…”

Section: Discussionmentioning

confidence: 99%

B-Cell Epitope Mapping of TprC and TprD Variants of Treponema pallidum Subspecies Informs Vaccine Development for Human Treponematoses

et al. 2022

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Several recent studies have focused on the identification, functional analysis, and structural characterization of outer membrane proteins (OMPs) of Treponema pallidum (Tp). The Tp species encompasses the highly related pallidum, pertenue, and endemicum subspecies of this pathogen, known to be the causative agents of syphilis, yaws, and bejel, respectively. These studies highlighted the importance of identifying surface-exposed OMP regions and the identification of B-cell epitopes that could be protective and used in vaccine development efforts. We previously reported that the TprC and TprD OMPs of Tp are predicted to contain external loops scattered throughout the entire length of the proteins, several of which show a low degree of sequence variability among strains and subspecies. In this study, these models were corroborated using AlphaFold2, a state-of-the-art protein structure modeling software. Here, we identified B-cell epitopes across the full-length TprC and TprD variants using the Geysan pepscan mapping approach with antisera from rabbits infected with syphilis, yaws, and bejel strains and from animals immunized with refolded recombinant TprC proteins from three syphilis strains. Our results show that the humoral response is primarily directed to sequences predicted to be on surface-exposed loops of TprC and TprD proteins, and that the magnitude of the humoral response to individual epitopes differs among animals infected with various syphilis strains and Tp subspecies. Rather than exhibiting strain-specificity, antisera showed various degrees of cross-reactivity with variant sequences from other strains. The data support the further exploration of TprC and TprD as vaccine candidates.

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AlphaFold2 transmembrane protein structure prediction shines

Cited by 6 publications

References 60 publications

Using AlphaFold to predict the impact of single mutations on protein stability and function

Using AlphaFold to predict the impact of single mutations on protein stability and function

Using AlphaFold to predict the impact of single mutations on protein stability and function

B-Cell Epitope Mapping of TprC and TprD Variants of Treponema pallidum Subspecies Informs Vaccine Development for Human Treponematoses

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