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Cited by 1,206

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

In Vitro Selection of Functional Nucleic Acids

Wilson, David S., Szostak, Jack W.·1999·Annual Review of Biochemistry

Abstract

▪ Abstract In vitro selection allows rare functional RNA or DNA molecules to be isolated from pools of over 10 15 different sequences. This approach has been used to identify RNA and DNA ligands for numerous small molecules, and recent three-dimensional structure solutions have revealed the basis for ligand recognition in several cases. By selecting high-affinity and -specificity nucleic acid ligands for proteins, promising new therapeutic and diagnostic reagents have been identified. Selection experiments have also been carried out to identify ribozymes that catalyze a variety of chemical transformations, including RNA cleavage, ligation, and synthesis, as well as alkylation and acyl-transfer reactions and N-glycosidic and peptide bond formation. The existence of such RNA enzymes supports the notion that ribozymes could have directed a primitive metabolism before the evolution of protein synthesis. New in vitro protein selection techniques should allow for a direct comparison of the frequency of ligand binding and catalytic structures in pools of random sequence polynucleotides versus polypeptides.

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Metadata

Authors
Wilson, D. S., & Szostak, J. W.
Venue
Annual Review of Biochemistry
Published
1999-06
Volume
68
Issue
1
Pages
611-647
ISSN
  • 0066-4154 (ISSN-L)
  • 1545-4509
OpenAlex
W2149005864
Cited by
1,206
References
7
FWCI
1.91
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: In Vitro Selection of Functional Nucleic Acids. https://app.cochat.ai/papers/10.1146/annurev.biochem.68.1.611
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Wilson, D. S., & Szostak, J. W. (1999). In Vitro Selection of Functional Nucleic Acids. Annual Review of Biochemistry. https://doi.org/10.1146/annurev.biochem.68.1.611

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.