Generalized Manning Condensation Model Captures the RNA Ion Atmosphere

Hayes, Ryan L.; Noel, Jeffrey K.; Mandic, Ana; Whitford, Paul C.; Sanbonmatsu, Karissa Y.; Mohanty, Udayan; Onuchic, José N.

doi:10.1103/physrevlett.114.258105

Cited by 69 publications

(105 citation statements)

References 53 publications

(54 reference statements)

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“…Computer simulations can treat discrete ions and the ion correlation and fluctuation effects (Chen et al 2009Kirmizialtin and Elber 2010;Hayes et al 2012Hayes et al , 2015Yoo and Aksimentiev 2012;Fried et al 2013;Mak and Henke 2013;Giambasu et al 2014Giambasu et al , 2015Henke and Mak 2014;Denesyuk and Thirumalai 2015;Wu et al 2015). However, a sampling of a large number of ions often demands exceedingly long computer time (Dong et al 2008).…”

Section: Introductionmentioning

confidence: 99%

“…For example, the three-dimensional interaction site model (3D-RISM), a method based on Ornstein and Zernike integral equation theory, can provide a direct solution to the 3D density distribution around the RNA by considering the correlation effect (Giambaşu et al 2014. The generalized counterion condensation theory (Hayes et al 2015) is another recently developed model that can treat the Mg 2+ -mediated correlation effect while taking into account the complicated structure of RNA.…”

Section: Introductionmentioning

confidence: 99%

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MCTBI: a web server for predicting metal ion effects in RNA structures

Sun

Zhang

Chen

2017

RNA

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Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna. physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg 2+ effects, as shown by extensive theoryexperiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MCTBI: a web server for predicting metal ion effects in RNA structures

Sun

Zhang

Chen

2017

RNA

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“…Recently, several new theories have been developed to account for the ion correlation effect for biomolecular systems. 53–55 For example, the three-dimensional reference interaction site model (3D-RISM) was developed based on the Ornstein and Zernike integral equation theory, 54 and a generalized counterion condensation theory was proposed to explicitly treat Mg 2+ ions with ion-ion correlations. 55 …”

Section: Introductionmentioning

confidence: 99%

Predicting Ion Effects in an RNA Conformational Equilibrium

et al. 2017

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We develop a partial charge-based Tightly Bound Ion (PCTBI) model for the ion effects in RNA folding. Based on the Monte Carlo Tightly Bound Ion (MCTBI) approach, the model can account for ion fluctuation and correlation effects, and can predict the ion distribution around the RNA. Furthermore, unlike the previous coarse-grained RNA charge models, where negative charges are placed on the phosphates only, the current new model considers the detailed all-atom partial charge distribution on the RNA. Thus, the model not only keeps the advantage of the MCTBI model but also has the potential to provide important detailed information unattainable by the previous MCTBI models. For example, the model predicts the reduction in ion binding upon protein binding and ion-induced conformational switches. For Hepatitis C virus (HCV) genomic RNA, the model predicts a Mg2+-induced stabilization of a kissing motif for a cis-acting regulatory element in the genomic RNA. Extensive theory-experiment comparisons support the reliability of the theoretical predictions. Therefore, the model may serve as a robust starting point for further development of an accurate method for ion effects in RNA conformational equilibrium and RNA-cofactor interactions.

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“…50, 54 Several new theories have been developed to treat the ion correlation effect for biomolecular systems. 55–58 For example, novel Monte Carlo and coarse-grained molecular dynamics simulations were employed to sample counterion distributions around an RNA, 9, 55 and in the three-dimensional interaction site model (3D-RISM), Ornstein and Zernike integral equation theory was used to account for the ion-ion correlations 57 . In a recently developed model, a generalized counterion condensation theory was developed to explicitly treat Mg 2+ ions and ion-ion correlations.…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo Tightly Bound Ion Model: Predicting Ion-Binding Properties of RNA with Ion Correlations and Fluctuations

Sun

Chen

2016

J. Chem. Theory Comput.

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Experiments have suggested that ion correlation and fluctuation effects can be potentially important for multivalent ions in RNA folding. However, most existing computational methods for the ion electrostatics in RNA folding tend to ignore these effects. The previously reported Tightly Bound Ion (TBI) model can treat ion correlation and fluctuation but its applicability to biologically important RNAs is severely limited by the low computational efficiency. Here, based on Monte Carlo sampling for the many-body ion distribution, we develop a new computational model, Monte Carlo Tightly Bound Ion (MCTBI) model, for ion binding properties around an RNA. Due to an enhanced sampling algorithm for ion distribution, the model leads to significant improvement in computational efficiency. For example, for a 160-nt RNA, the model causes more than 10-fold increase in the computational efficiency, and the improvement in computational efficiency is more pronounced for larger systems. Furthermore, unlike the earlier model, which describes ion distribution using the number of bound ions around each nucleotide, the current MCTBI model is based on the three-dimensional coordinates of the ions. The higher efficiency of the model allows us to treat the ion effects for medium to large RNA molecules, RNA-ligand complexes, and RNA-protein complexes. This new model, together with proper RNA conformational sampling and energetics model, may serve as a starting point for further development for the ion effects in RNA folding and conformational changes and for large nucleic acids systems.

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Generalized Manning Condensation Model Captures the RNA Ion Atmosphere

Cited by 69 publications

References 53 publications

MCTBI: a web server for predicting metal ion effects in RNA structures

MCTBI: a web server for predicting metal ion effects in RNA structures

Predicting Ion Effects in an RNA Conformational Equilibrium

Monte Carlo Tightly Bound Ion Model: Predicting Ion-Binding Properties of RNA with Ion Correlations and Fluctuations

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