Secondary Structure Libraries for Artificial Evolution Experiments
Language English Country Switzerland Media electronic
Document type Journal Article
Grant support
19-20989S
Grantová Agentura České Republiky
CZ.02.1.01/0.0/0.0/16_019/0000729
European Regional Development Fund (OP RDE)
PubMed
33802780
PubMed Central
PMC8002575
DOI
10.3390/molecules26061671
PII: molecules26061671
Knihovny.cz E-resources
- Keywords
- DNA, RNA, SELEX, aptamer, artificial evolution, deoxyribozyme, in vitro selection, nucleic acids, ribozyme, secondary structure, synthetic biology,
- MeSH
- Aptamers, Nucleotide genetics MeSH
- DNA, Catalytic genetics MeSH
- Gene Library * MeSH
- Nucleic Acid Conformation MeSH
- Mutagenesis MeSH
- Nucleotide Motifs genetics MeSH
- Inverted Repeat Sequences genetics MeSH
- Base Pairing MeSH
- Probability MeSH
- Directed Molecular Evolution methods MeSH
- RNA, Catalytic genetics MeSH
- Synthetic Biology methods MeSH
- In Vitro Techniques MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Aptamers, Nucleotide MeSH
- DNA, Catalytic MeSH
- RNA, Catalytic MeSH
Methods of artificial evolution such as SELEX and in vitro selection have made it possible to isolate RNA and DNA motifs with a wide range of functions from large random sequence libraries. Once the primary sequence of a functional motif is known, the sequence space around it can be comprehensively explored using a combination of random mutagenesis and selection. However, methods to explore the sequence space of a secondary structure are not as well characterized. Here we address this question by describing a method to construct libraries in a single synthesis which are enriched for sequences with the potential to form a specific secondary structure, such as that of an aptamer, ribozyme, or deoxyribozyme. Although interactions such as base pairs cannot be encoded in a library using conventional DNA synthesizers, it is possible to modulate the probability that two positions will have the potential to pair by biasing the nucleotide composition at these positions. Here we show how to maximize this probability for each of the possible ways to encode a pair (in this study defined as A-U or U-A or C-G or G-C or G.U or U.G). We then use these optimized coding schemes to calculate the number of different variants of model stems and secondary structures expected to occur in a library for a series of structures in which the number of pairs and the extent of conservation of unpaired positions is systematically varied. Our calculations reveal a tradeoff between maximizing the probability of forming a pair and maximizing the number of possible variants of a desired secondary structure that can occur in the library. They also indicate that the optimal coding strategy for a library depends on the complexity of the motif being characterized. Because this approach provides a simple way to generate libraries enriched for sequences with the potential to form a specific secondary structure, we anticipate that it should be useful for the optimization and structural characterization of functional nucleic acid motifs.
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