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Programmed-1 ribosomal frameshifting from the perspective of the conformational dynamics of mRNA and ribosomes

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出版社

ELSEVIER
DOI: 10.1016/j.csbj.2021.06.015

关键词

Ribosomal frameshifting; Single-molecule; Optical tweezers; smFRET; MD simulation; Cryo-EM

资金

  1. Ministry of Science and Technology (MOST) [109-2311-B-002-009-MY3, 1092311B002025]

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-1 PRF is a translation mechanism used by viruses to regulate protein expression levels encoded on the same mRNA. It is rarely used by host human cells and is considered a potential target for antiviral drug development. -1 PRF occurs when ribosomes encounter specific mRNA signals impeding their translocation, leading to unique conformational changes essential for frameshifting.
Programmed-1 ribosomal frameshifting (-1 PRF) is a translation mechanism that regulates the relative expression level of two proteins encoded on the same messenger RNA (mRNA). This regulation is commonly used by viruses such as coronaviruses and retroviruses but rarely by host human cells, and for this reason, it has long been considered as a therapeutic target for antiviral drug development. Understanding the molecular mechanism of -1 PRF is one step toward this goal. Minus-one PRF occurs with a certain efficiency when translating ribosomes encounter the specialized mRNA signal consisting of the frameshifting site and a downstream stimulatory structure, which impedes translocation of the ribosome. The impeded ribosome can still undergo profound conformational changes to proceed with translocation; however, some of these changes may be unique and essential to frameshifting. In addition, most stimulatory structures exhibit conformational dynamics and sufficient mechanical strength, which, when under the action of ribosomes, may in turn further promote-1 PRF efficiency. In this review, we discuss how the dynamic features of ribosomes and mRNA stimulatory structures may influence the occurrence of -1 PRF and propose a hypothetical frameshifting model that recapitulates the role of conformational dynamics. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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