ArticleProtein science : a publication of the Protein Society2022
Estimating conformational heterogeneity of tryptophan synthase with a template-based Alphafold2 approach.
Article in Protein science : a publication of the Protein Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- From CASP13 to the Nobel Prize: DeepMind's AlphaFold Journey in Revolutionizing Protein Structure Prediction and Beyond.Current protein & peptide science · 2026Review
- Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era.Briefings in bioinformatics · 2025Review
- A naturally occurring standalone TrpB enzyme provides insights into allosteric communication within tryptophan synthase.Protein science : a publication of the Protein Society · 2025Article
- Advances in the biological production of sugar alcohols from biomass-derived xylose.World journal of microbiology & biotechnology · 2025Review
- AFsample2 predicts multiple conformations and ensembles with AlphaFold2.Communications biology · 2025Article
- Proteomic Evidence for Amyloidogenic Cross-Seeding in Fibrinaloid Microclots.International journal of molecular sciences · 2024Article
- Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign.Faraday discussions · 2024Article
- Integration of a Randomized Sequence Scanning Approach in AlphaFold2 and Local Frustration Profiling of Conformational States Enable Interpretable Atomistic Characterization of Conformational Ensembles and Detection of Hidden Allosteric States in the ABL1 Protein Kinase.Journal of chemical theory and computation · 2024Article
- Deep learning for protein structure prediction and design-progress and applications.Molecular systems biology · 2024Review
- AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design.JACS Au · 2023Review
- AlphaFold2 and its applications in the fields of biology and medicine.Signal transduction and targeted therapy · 2023Review
- Exploring AlphaFold2's Performance on Predicting Amino Acid Side-Chain Conformations and Its Utility in Crystal Structure Determination of B318L Protein.International journal of molecular sciences · 2023Article
- Estimating conformational heterogeneity of tryptophan synthase with a template-based Alphafold2 approach.Protein science : a publication of the Protein Society · 2022Article
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4 authors.
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Abstract
The three-dimensional structure of the enzymes provides very relevant information on the arrangement of the catalytic machinery and structural elements gating the active site pocket. The recent success of the neural network Alphafold2 in predicting the folded structure of proteins from the primary sequence with high levels of accuracy has revolutionized the protein design field. However, the application of Alphafold2 for understanding and engineering function directly from the obtained single static picture is not straightforward. Indeed, understanding enzymatic function requires the exploration of the ensemble of thermally accessible conformations that enzymes adopt in solution. In the present study, we evaluate the potential of Alphafold2 in assessing the effect of the mutations on the conformational landscape of the beta subunit of tryptophan synthase (TrpB). Specifically, we develop a template-based Alphafold2 approach for estimating the conformational heterogeneity of several TrpB enzymes, which is needed for enhanced stand-alone activity. Our results show the potential of Alphafold2, especially if combined with molecular dynamics simulations, for elucidating the changes induced by mutation in the conformational landscapes at a rather reduced computational cost, thus revealing its plausible application in computational enzyme design.
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