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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America. >Quantitative tests of a reconstitution model for RNA folding thermodynamics and kinetics
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Quantitative tests of a reconstitution model for RNA folding thermodynamics and kinetics

机译：Quantitative tests of a reconstitution model for RNA folding thermodynamics and kinetics

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摘要

Decades of study of the architecture and function of structured RNAs have led to the perspective that RNA tertiary structure is modular, made of locally stable domains that retain their structure across RNAs. We formalize a hypothesis inspired by this modularity-that RNA folding thermodynamics and kinetics can be quantitatively predicted from separable energetic contributions of the individual components of a complex RNA. This reconstitution hypothesis considers RNA tertiary folding in terms of Delta G(align), the probability of aligning tertiary contact partners, and Delta G(tert), the favorable energetic contribution from the formation of tertiary contacts in an aligned state. This hypothesis predicts that changes in the alignment of tertiary contacts from different connecting helices and junctions (Delta G(HJH)) or from changes in the electrostatic environment (Delta G(+/-)) will not affect the energetic perturbation from a mutation in a tertiary contact (Delta Delta G(tert)). Consistent with these predictions, single-molecule FRET measurements of folding of model RNAs revealed constant Delta Delta G(tert) values for mutations in a tertiary contact embedded in different structural contexts and under different electrostatic conditions. The kinetic effects of these mutations provide further support for modular behavior of RNA elements and suggest that tertiary mutations may be used to identify rate-limiting steps and dissect folding and assembly pathways for complex RNAs. Overall, our model and results are foundational for a predictive understanding of RNA folding that will allow manipulation of RNA folding thermodynamics and kinetics. Conversely, the approaches herein can identify cases where an independent, additive model cannot be applied and so require additional investigation.

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