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Computational Design of Allosteric Ribozymes via Genetic Algorithms.
Kaloudas, Dimitrios; Pavlova, Nikolet; Penchovsky, Robert.
Affiliation
  • Kaloudas D; Laboratory of Synthetic Biology and Bioinformatics, Faculty of Biology, Sofia University "St. Kliment Ohridski", Sofia, Bulgaria.
  • Pavlova N; Laboratory of Synthetic Biology and Bioinformatics, Faculty of Biology, Sofia University "St. Kliment Ohridski", Sofia, Bulgaria.
  • Penchovsky R; Laboratory of Synthetic Biology and Bioinformatics, Faculty of Biology, Sofia University "St. Kliment Ohridski", Sofia, Bulgaria. robert.penchovsky@biofac.uni-sofia.bg.
Methods Mol Biol ; 2822: 443-469, 2024.
Article in En | MEDLINE | ID: mdl-38907934
ABSTRACT
In vitro selection of allosteric ribozymes has many challenges, such as complex and time-consuming experimental procedures, uncertain results, and the unwanted functionality of the enriched sequences. The precise computational design of allosteric ribozymes is achievable using RNA secondary structure folding principles. The computational design of allosteric ribozymes is based on experimentally validated EAs, random search algorithms, and a partition function for RNA folding. The in silico design achieves an accuracy exceeding 90%. Various algorithms with different logic gates have been automated via computer programs that can quickly create many allosteric sequences. This can eliminate the need for in vitro selection of allosteric ribozymes, thus vastly reducing the time and cost required.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / RNA, Catalytic / Computational Biology / Nucleic Acid Conformation Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / RNA, Catalytic / Computational Biology / Nucleic Acid Conformation Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2024 Document type: Article Affiliation country: Country of publication: