ReviewBiochemical Society transactions2016
Computational protein design with backbone plasticity.
Review in Biochemical Society transactions, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Structure-Based Design and Mechanistic Insight for Enhanced Catalytic Activity of Aldo/Keto Reductase AKR13B3 fromToxins · 2026Article
- Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.Molecules (Basel, Switzerland) · 2024Review
- Accelerating the Discovery and Design of Antimicrobial Peptides with Artificial Intelligence.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Step-by-step design of proteins for small molecule interaction: A review on recent milestones.Protein science : a publication of the Protein Society · 2021Review
- A general-purpose protein design framework based on mining sequence-structure relationships in known protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Development and structural characterization of an engineered multi-copper oxidase reporter of protein-protein interactions.The Journal of biological chemistry · 2019Article
- Article
- Unintended specificity of an engineered ligand-binding protein facilitated by unpredicted plasticity of the protein fold.Protein engineering, design & selection : PEDS · 2018Article
- Unraveling co-translational protein folding: Concepts and methods.Methods (San Diego, Calif.) · 2018Review
- ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design.Bioinformatics (Oxford, England) · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as 'scaffolds' onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increased search space, but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process.
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