JOURNAL ARTICLE
Molecular dynamics simulations of ribosome-binding sites in theophylline-responsive riboswitch associated with improving the gene expression regulation in chloroplasts.
Published In: Journal of Bioinformatics & Computational Biology, 2024, v. 22, n. 5. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Berahmand, Rahim; Emadpour, Masoumeh; Javaran, Mokhtar Jalali; Haji-Allahverdipoor, Kaveh; Akbarabadi, Ali 3 of 3
Abstract
The existence of an efficient inducible transgene expression system is a valuable tool in recombinant protein production. The synthetic theophylline-responsive riboswitch (theo.RS) can be replaced in the 5 ′ untranslated region of an mRNA and control the translation of downstream gene in chloroplasts in response to the binding with a ligand molecule, theophylline. One of the drawbacks associated with the efficiency of the theo.RS is the leak in the RS structure allowing undesired background translation when the switch is expected to be off. The purpose of this study was to detect the factors causing the leak of the theo.RS in the off mode, using molecular dynamics (MD) simulations the appropriate balancing of the simulation system, using the necessary commands, a 40 ns simulation was conducted. Analysis of the solvent-accessible surface area for both ribosome-binding site (RBS) regions indicated that nucleotide 79 of the theo.RS, a guanine, had the highest surface exposure to ribosome access. These results were verified with the study of hydrogen bonding of RBS regions with the RNA structure. Therefore, redesigning the RBS regions and avoiding the unmasked nucleotide(s) in the structure may improve the tightness of theo.RS in off mode resulting in the efficient inhibition of translation. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Bioinformatics & Computational Biology. 2024/10, Vol. 22, Issue 5, p1
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:0219-7200
- DOI:10.1142/S0219720024500239
- Accession Number:181070940
- Copyright Statement:Copyright of Journal of Bioinformatics & Computational Biology is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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