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Integrating molecular dynamics simulations with chemical probing experiments using SHAPE-FIT.

Serdal Kirmizialtin¹, Scott P Hennelly¹, Alexander Schug²

¹New Mexico Consortium, Los Alamos, New Mexico, USA; Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.

Methods in Enzymology

|March 2, 2015

Summary

We developed SHAPE-FIT, a new method to combine RNA molecular simulations with chemical probing experiments. This approach optimizes simulation parameters for greater accuracy in understanding RNA dynamics and function.

Keywords:

Modeling Molecular dynamics simulation RNA Riboswitch SHAPE

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Area of Science:

Computational Biology
Biophysics
RNA Science

Background:

Integrating molecular dynamics (MD) simulations with experimental data for RNA molecules is complex.
Accurate simulations require precise force field parameters, which are difficult to obtain.
Experimental techniques like Selective 2'-hydroxyl acylation by primer extension (SHAPE) provide residue-specific mobility data.

Purpose of the Study:

To develop a novel method for integrating chemical probing experiments with molecular simulations of RNA.
To automatically optimize molecular simulation force field parameters using experimental reactivity data.
To enable more accurate atomistic simulations of RNA dynamics grounded in experimental measurements.

Main Methods:

Developed SHAPE-FIT, a method that integrates SHAPE chemical probing data with RNA molecular simulations.
Utilized a native structure-based model for RNA simulations.
Implemented an automated process to optimize force field parameters based on SHAPE reactivity measurements.

Main Results:

Achieved optimization of potential parameters for molecular dynamics force fields.
Generated simulation dynamics that demonstrate high consistency with SHAPE probing experiments.
Demonstrated the feasibility of grounding atomistic simulations in experimental data.

Conclusions:

SHAPE-FIT successfully integrates chemical probing data with molecular simulations for RNA.
Optimized simulations provide a more accurate representation of RNA dynamics.
This approach enhances the study of RNA structure-function relationships through experimentally validated simulations.