Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F25%3A00082483" target="_blank" >RIV/00159816:_____/25:00082483 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14310/25:00140783
Result on the web
<a href="https://onlinelibrary.wiley.com/doi/10.1002/anie.202421686" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/anie.202421686</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/anie.202421686" target="_blank" >10.1002/anie.202421686</a>

Result language
angličtina
Original language name
Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins
Original language description
The ability to predict and design protein structures has led to numerous applications in medicine, diagnostics and sustainable chemical manufacture. In addition, the wealth of predicted protein structures has advanced our understanding of how life's molecules function and interact. Honouring the work that has fundamentally changed the way scientists research and engineer proteins, the Nobel Prize in Chemistry in 2024 was awarded to David Baker for computational protein design and jointly to Demis Hassabis and John Jumper, who developed AlphaFold for machine-learning-based protein structure prediction. Here, we highlight notable contributions to the development of these computational tools and their importance for the design of functional proteins that are applied in organic synthesis. Notably, both technologies have the potential to impact drug discovery as any therapeutic protein target can now be modelled, allowing the de novo design of peptide binders and the identification of small molecule ligands through in silico docking of large compound libraries. Looking ahead, we highlight future research directions in protein engineering, medicinal chemistry and material design that are enabled by this transformative shift in protein science.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10608 - Biochemistry and molecular biology

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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