ArticleNucleic acids research2015
SwiftLib: rapid degenerate-codon-library optimization through dynamic programming.
Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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Who cites it
37 citing papers in PubMed, 69 citations in OpenAlex.
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- De novo design of protein minibinder agonists of TLR3.Nature communications · 2025Article
- Bioengineering hybrid artificial life.Frontiers in bioinformatics · 2025Review
- De novo design of mini-protein binders broadly neutralizing Clostridioides difficile toxin B variants.Nature communications · 2024Article
- GGAssembler: Precise and economical design and synthesis of combinatorial mutation libraries.Protein science : a publication of the Protein Society · 2024Article
- Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.Nature communications · 2024Article
- De novo design of protein minibinder agonists of TLR3.bioRxiv : the preprint server for biology · 2024Article
- Single-domain antibodies against SARS-CoV-2 RBD from a two-stage phage screening of universal and focused synthetic libraries.BMC infectious diseases · 2024Article
- Machine Learning for Protein Engineering.ArXiv · 2023Article
- Inhibition of a malaria host-pathogen interaction by a computationally designed inhibitor.Protein science : a publication of the Protein Society · 2023Article
- Studying the characteristics of nanobody CDR regions based on sequence analysis in combination with 3D structures.Journal, genetic engineering & biotechnology · 2022Article
- In Vitro Evolution Reveals Noncationic Protein-RNA Interaction Mediated by Metal Ions.Molecular biology and evolution · 2022Article
- Therapeutic enzyme engineering using a generative neural network.Scientific reports · 2022Article
- Site-wise Diversification of Combinatorial Libraries Using Insights from Structure-guided Stability Calculations.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Machine Learning-driven Protein Library Design: A Path Toward Smarter Libraries.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Designer proteins that competitively inhibit GαThe Journal of biological chemistry · 2021Article
- A Platform for Deep Sequence-Activity Mapping and Engineering Antimicrobial Peptides.ACS synthetic biology · 2021Article
- CoLiDe: Combinatorial Library Design tool for probing protein sequence space.Bioinformatics (Oxford, England) · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.
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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.