Predicting Ion Effects in an RNA Conformational Equilibrium

2018

Biophysical Journal

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The interaction between metal ions, especially Mg ions, and RNA plays a critical role in RNA folding. Upon binding to RNA, a metal ion that is fully hydrated in bulk solvent can become dehydrated. Here we use molecular dynamics simulation to investigate the dehydration of bound hexahydrated Mg ions. We find that a hydrated Mg ion in the RNA groove region can involve significant dehydration in the outer hydration shell. The first or innermost hydration shell of the Mg ion, however, is retained during the simulation because of the strong ion-water electrostatic attraction. As a result, water-mediated hydrogen bonding remains an important form for Mg-RNA interaction. Analysis for ions at different binding sites shows that the most pronounced water deficiency relative to the fully hydrated state occurs at a radial distance of around 11 Å from the center of the ion. Based on the independent 200 ns molecular dynamics simulations for three different RNA structures (Protein Data Bank: 1TRA, 2TPK, and 437D), we find that Mg ions overwhelmingly dominate over monovalent ions such as Na and K in ion-RNA binding. Furthermore, application of the free energy perturbation method leads to a quantitative relationship between the Mg dehydration free energy and the local structural environment. We find that ΔΔG, the change of the Mg hydration free energy upon binding to RNA, varies linearly with the inverse distance between the Mg ion and the nearby nonbridging oxygen atoms of the phosphate groups, and ΔΔG can reach -2.0 kcal/mol and -3.0 kcal/mol for an Mg ion bound to the surface and to the groove interior, respectively. In addition, the computation results in an analytical formula for the hydration ratio as a function of the average inverse Mg-O distance. The results here might be useful for further quantitative investigations of ion-RNA interactions in RNA folding.

Section: Discussionmentioning

confidence: 67%

Hexahydrated Mg2+ Binding and Outer-Shell Dehydration on RNA Surface

2018

Biophysical Journal

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“…For the 5BSL3.2 segment, NMR studies revealed that its secondary structure is comprised of a bottom base paired stem, a bulge and an upper single stranded region containing the SL2-complementary sequence (Friebe et al, 2005 ; Kranawetter et al, 2017 ; Sun et al, 2017a ), as shown in Figure 1C (kissing 5BSL3.2). The Vfold model predicts, in addition to the above kissing conformation with the SL2-complementary sequence exposed, an alternative three-way-junction (non-kissing) conformation (the “non-kissing conformation” in Figure 1C ).…”

Section: Mg 2+ Ion Effects In the Formation Of Thementioning

confidence: 99%

“…TB ions are clustered around RNA surface to form a high local concentration (Tan and Chen, 2005 ). TB ions form a mid-state between SSB and DB ions (Sun et al, 2017a ): on the one hand, TB ions do not involve SSB-like specific binding sites and are hydrated, on the other hand, TB ions cannot move around like DB ions, because the local high concentration and the resultant ion-ion coupling (correlation) can significantly lower the ion mobility. The ion correlation prevents a fluid-like model mean-field treatment for the TB ions.…”

Section: Computational Modeling Of Ion-rna Interactionsmentioning

confidence: 99%

“…Since the original TBI framework was first reported, several new models have been developed in the TBI framework. Most recently, using a novel sampling-resampling algorithm, the Monte Carlo tightly bound ion model (MCTBI) (Sun and Chen, 2016 ) was developed in order to enhance the computational efficiency, and the partial charge-based tightly bound ion model (PCTBI) (Sun et al, 2017a ) was developed to account for more detailed RNA charge distribution. These new models have led to 1,000-fold improvement in computational time and thus allow us to treat large RNAs (several hundred nucleotides) (Sun et al, 2017c ).…”

Section: Computational Modeling Of Ion-rna Interactionsmentioning

confidence: 99%

“…Thus, in order to predict RNA structural changes, we need to sample RNA conformations using RNA folding models such as Vfold (Xu et al, 2014 ) and molecular dynamics (MD) simulations, and compute the ion-induced free energy changes for the different conformations. In what follows, we focus on the major conclusions and the analysis for the ion binding effects in the 5BSL3.2:3′X HCV kissing complex formation (Kranawetter et al, 2017 ; Sun et al, 2017a ).…”

Section: Computational Modeling Of Ion-rna Interactionsmentioning

confidence: 99%

See 2 more Smart Citations

Theory Meets Experiment: Metal Ion Effects in HCV Genomic RNA Kissing Complex Formation

Sun

Heng

2017

Front. Mol. Biosci.

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The long-range base pairing between the 5BSL3. 2 and 3′X domains in hepatitis C virus (HCV) genomic RNA is essential for viral replication. Experimental evidence points to the critical role of metal ions, especially Mg2+ ions, in the formation of the 5BSL3.2:3′X kissing complex. Furthermore, NMR studies suggested an important ion-dependent conformational switch in the kissing process. However, for a long time, mechanistic understanding of the ion effects for the process has been unclear. Recently, computational modeling based on the Vfold RNA folding model and the partial charge-based tightly bound ion (PCTBI) model, in combination with the NMR data, revealed novel physical insights into the role of metal ions in the 5BSL3.2-3′X system. The use of the PCTBI model, which accounts for the ion correlation and fluctuation, gives reliable predictions for the ion-dependent electrostatic free energy landscape and ion-induced population shift of the 5BSL3.2:3′X kissing complex. Furthermore, the predicted ion binding sites offer insights about how ion-RNA interactions shift the conformational equilibrium. The integrated theory-experiment study shows that Mg2+ ions may be essential for HCV viral replication. Moreover, the observed Mg2+-dependent conformational equilibrium may be an adaptive property of the HCV genomic RNA such that the equilibrium is optimized to the intracellular Mg2+ concentration in liver cells for efficient viral replication.

IsRNA1: De Novo Prediction and Blind Screening of RNA 3D Structures

Zhang

Jun

J. Chem. Theory Comput.

2021

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Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.