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Secondary Structure Libraries for Artificial Evolution Experiments

ABSTRACT: 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.

SUBMITTER: Sgallova R

PROVIDER: S-EPMC8002575 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The in vitro selection of nucleic acid libraries has driven the discovery of RNA and DNA receptors (aptamers) and catalysts with tailor-made functional properties. Functional nucleic acids emerging from selections have been observed to possess an unusually high degree of secondary structure. In this study, we experimentally examined the relationship between the degree of secondary structure in a nucleic acid library and its ability to yield aptamers that bind protein targets. We designed a patterned nucleic acid library (denoted R*Y*) to enhance the formation of stem-loop structures without imposing any specific sequence or secondary structural requirement. This patterned library was predicted computationally to contain a significantly higher average folding energy compared to a standard, unpatterned N(60) library of the same length. We performed three different iterated selections for protein binding using patterned and unpatterned libraries competing in the same solution. In all three cases, the patterned R*Y* library was enriched relative to the unpatterned library over the course of the 9- to 10-round selection. Characterization of individual aptamer clones emerging from the three selections revealed that the highest affinity aptamer assayed arose from the patterned library for two protein targets, while in the third case, the highest affinity aptamers from the patterned and random libraries exhibited comparable affinity. We identified the binding motif requirements for the most active aptamers generated against two of the targets. The two binding motifs are 3.4- and 27-fold more likely to occur in the R*Y* library than in the N(60) library. Collectively, our findings suggest that researchers performing selections for nucleic acid aptamers and catalysts should consider patterned libraries rather than commonly used N(m) libraries to increase both the likelihood of isolating functional molecules and the potential activities of the resulting molecules.

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Secondary Structure Libraries for Artificial Evolution Experiments

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