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Advances in RNA molecular dynamics: a simulator's guide to RNA force fields

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Molecular simulations have become an essential tool for biochemical research. When they work properly, they are able to provide invaluable interpretations of experimental results and ultimately provide novel, experimentally testable predictions. Unfortunately, not all simulation models are created equal, and with inaccurate models it becomes unclear what is a bona fide prediction versus a simulation artifact. RNA models are still in their infancy compared to the many robust protein models that are widely in use, and for that reason the number of RNA force field revisions in recent years has been rapidly increasing. As there is no universally accepted ‘best’ RNA force field at the current time, RNA simulators must decide which one is most suited to their purposes, cognizant of its essential assumptions and their inherent strengths and weaknesses. Hopefully, armed with a better understanding of what goes inside the simulation ‘black box,’ RNA biochemists can devise novel experiments and provide crucial thermodynamic and structural data that will guide the development and testing of improved RNA models. WIREs RNA 2017, 8:e1396. doi: 10.1002/wrna.1396 This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Evolution and Genomics > Computational Analyses of RNA RNA Methods > RNA Analyses In Vitro and In Silico
In an all‐atom simulation, the potential energy V of a system with atomic coordinates R is calculated as a sum of bonded (stretch, bend, and torsion) and nonbonded (Lennard–Jones and Coulomb electrostatics) interactions. Atom‐type specific force‐constants determine the strength of each interaction as a function of geometric deformation (bonded) or interatomic distance rij (nonbonded). A ‘force field’ is a curated collection of force constants suitable for simulating a particular molecular system.
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The experiment‐based parameter calibration scheme for the Chen–Garcia force field.
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Rotatable bonds in RNA polymers.
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The generalized AMBER protocol for parameterizing small molecule ligands is linear, water‐model independent, and assumes the transferability of parameters developed for small organic molecules.
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The iterative, multilevel generalized CHARMM protocol simultaneously optimizes all interaction parameters to provide the best match to the quantum mechanical potential energy surface, including interactions with water. Source: Xu et al.
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RNA Methods > RNA Analyses In Vitro and In Silico
RNA Evolution and Genomics > Computational Analyses of RNA
RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry

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