ReviewProtein science : a publication of the Protein Society2016
Why reinvent the wheel? Building new proteins based on ready-made parts.
Review in Protein science : a publication of the Protein Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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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
24 citing papers in PubMed.
- Opportunities and challenges in design and optimization of protein function.Nature reviews. Molecular cell biology · 2024Review
- Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Back in time to the Gly-rich prototype of the phosphate binding elementary function.Current research in structural biology · 2024Review
- Cold-Active Lipases and Esterases: A Review on Recombinant Overexpression and Other Essential Issues.International journal of molecular sciences · 2022Review
- Engineering functional thermostable proteins using ancestral sequence reconstruction.The Journal of biological chemistry · 2022Review
- Protein-protein interaction prediction with deep learning: A comprehensive review.Computational and structural biotechnology journal · 2022Review
- What Have We Learned from Design of Function in Large Proteins?Biodesign research · 2022Review
- Step-by-step design of proteins for small molecule interaction: A review on recent milestones.Protein science : a publication of the Protein Society · 2021Review
- The AbDesign computational pipeline for modular backbone assembly and design of binders and enzymes.Protein science : a publication of the Protein Society · 2021Article
- Tight and specific lanthanide binding in a de novo TIM barrel with a large internal cavity designed by symmetric domain fusion.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Harnessing Conformational Plasticity to Generate Designer Enzymes.Journal of the American Chemical Society · 2020Review
- 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
- A lipophilicity-based energy function for membrane-protein modelling and design.PLoS computational biology · 2019Article
- Optimizing antibody affinity and stability by the automated design of the variable light-heavy chain interfaces.PLoS computational biology · 2019Article
- Article
- Ultrahigh specificity in a network of computationally designed protein-interaction pairs.Nature communications · 2018Article
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- Highly active enzymes by automated combinatorial backbone assembly and sequence design.Nature communications · 2018Article
- Computational Protein Design with Deep Learning Neural Networks.Scientific reports · 2018Article
- Principles for computational design of binding antibodies.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
We protein engineers are ambivalent about evolution: on the one hand, evolution inspires us with myriad examples of biomolecular binders, sensors, and catalysts; on the other hand, these examples are seldom well-adapted to the engineering tasks we have in mind. Protein engineers have therefore modified natural proteins by point substitutions and fragment exchanges in an effort to generate new functions. A counterpoint to such design efforts, which is being pursued now with greater success, is to completely eschew the starting materials provided by nature and to design new protein functions from scratch by using de novo molecular modeling and design. While important progress has been made in both directions, some areas of protein design are still beyond reach. To this end, we advocate a synthesis of these two strategies: by using design calculations to both recombine and optimize fragments from natural proteins, we can build stable and as of yet un-sampled structures, thereby granting access to an expanded repertoire of conformations and desired functions. We propose that future methods that combine phylogenetic analysis, structure and sequence bioinformatics, and atomistic modeling may well succeed where any one of these approaches has failed on its own.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.