AMOEBA Polarizable Atomic Multipole Force Field for Nucleic Acids.
Changsheng ZhangChao LuZhifeng JingChuanjie WuJean-Philip PiquemalJay W PonderPengyu RenPublished in: Journal of chemical theory and computation (2018)
The AMOEBA polarizable atomic multipole force field for nucleic acids is presented. Valence and electrostatic parameters were determined from high-level quantum mechanical data, including structures, conformational energy, and electrostatic potentials, of nucleotide model compounds. Previously derived parameters for the phosphate group and nucleobases were incorporated. A total of over 35 μs of condensed-phase molecular dynamics simulations of DNA and RNA molecules in aqueous solution and crystal lattice were performed to validate and refine the force field. The solution and/or crystal structures of DNA B-form duplexes, RNA duplexes, and hairpins were captured with an average root-mean-squared deviation from NMR structures below or around 2.0 Å. Structural details, such as base pairing and stacking, sugar puckering, backbone and χ-torsion angles, groove geometries, and crystal packing interfaces, agreed well with NMR and/or X-ray. The interconversion between A- and B-form DNAs was observed in ethanol-water mixtures at 328 K. Crystal lattices of B- and Z-form DNA and A-form RNA were examined with simulations. For the RNA tetraloop, single strand tetramers, and HIV TAR with 29 residues, the simulated conformational states, 3 J-coupling, nuclear Overhauser effect, and residual dipolar coupling data were compared with NMR results. Starting from a totally unstacked/unfolding state, the rCAAU tetranucleotide was folded into A-form-like structures during ∼1 μs molecular dynamics simulations.
Keyphrases
- molecular dynamics simulations
- high resolution
- single molecule
- solid state
- nucleic acid
- molecular docking
- circulating tumor
- magnetic resonance
- cell free
- molecular dynamics
- aqueous solution
- electronic health record
- antiretroviral therapy
- hiv infected
- hepatitis c virus
- big data
- human immunodeficiency virus
- mass spectrometry
- hiv positive
- ionic liquid
- hiv testing
- deep learning