Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis
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Updated: Feb 11, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
Published on: May 31, 2013
Travis Hurst1, Xiaojun Xu1, Peinan Zhao1
1Department of Physics, Department of Biochemistry , and University of Missouri Informatics Institute , University of Missouri , Columbia , Missouri 65211 , United States.
Abstract:
The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.
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