Quantum machine learning corrects classical forcefields: Stretching DNA base pairs in explicit solvent

In order to improve the accuracy of molecular dynamics simulations, classical forcefields are supplemented with a kernel-based machine learning method trained on quantum-mechanical fragment energies. As an example application, a potential-energy surface is generalized for a small DNA duplex, taking...

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Veröffentlicht in:	The Journal of chemical physics 2022-08, Vol.157 (6), p.064107-064107
Hauptverfasser:	Berryman, Joshua T., Taghavi, Amirhossein, Mazur, Florian, Tkatchenko, Alexandre
Format:	Artikel
Sprache:	eng
Schlagworte:	Helices Kernels Machine learning Molecular dynamics Nucleic acids Potential energy Qualitative analysis Simulation Solvation Stiffness Stretching Thermodynamic properties Thermodynamics
Online-Zugang:	Volltext
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