Abstract

Flexible nucleic acid structures can be challenging to accurately resolve with currently available experimental structural determination techniques. As an alternative, molecular dynamics (MD) simulations can provide a window into understanding the unique dynamics and population distributions of these biomolecules. Previously, molecular dynamics simulations of noncanonical (non-duplex) nucleic acids have proven difficult to accurately model. With a new influx of improved nucleic acid force fields, achieving an in-depth understanding of the dynamics of flexible nucleic acid structures may be achievable. In this project, currently available nucleic acid force fields are evaluated using a flexible yet stable model system: the DNA mini-dumbbell. Prior to MD simulations, nuclear magnetic resonance (NMR) re-refinement was accomplished using improved refinement techniques in explicit solvent to yield DNA mini-dumbbell structures with better agreement between the newly determined PDB snapshots, with the NMR data itself, as well as the unrestrained simulation data. Starting from newly determined structures, a total aggregate of over 800 μs of production data between 2 DNA mini-dumbbell sequences and 8 force fields was collected to compare to these newly refined structures. The force fields tested spanned from traditional Amber force fields: bsc0, bsc1, OL15, and OL21 to Charmm force fields: Charmm36 and the Drude polarizable force field, as well as force fields from independent developers: Tumuc1 and CuFix/NBFix. The results indicated slight variations not only between the different force fields but also between the sequences as well. Given our previous experiences with high populations of potentially anomalous structures in RNA UUCG tetraloops and in various tetranucleotides, we expected the mini-dumbbell system to be challenging to accurately model. Surprisingly, many of the recently developed force fields generated structures in good agreement with experiments. Yet, each of the force fields provided a different distribution of potentially anomalous structures.

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