Abstract
The optimisation of a peptide-capped glycine using the novel force field FFLUX is presented. FFLUX is a force field based on the machine-learning method kriging and the topological energy partitioning method called Interacting Quantum Atoms. FFLUX has a completely different architecture to that of traditional force fields, avoiding (harmonic) potentials for bonded, valence and torsion angles. In this study, FFLUX performs an optimisation on a glycine molecule and successfully recovers the target density-functional-theory energy with an error of 0.89 ± 0.03 kJ mol−1. It also recovers the structure of the global minimum with a root-mean-squared deviation of 0.05 Å (excluding hydrogen atoms). We also show that the geometry of the intra-molecular hydrogen bond in glycine is recovered accurately.
Original language | English |
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Journal | MOLECULAR SIMULATION |
Early online date | 11 Feb 2018 |
DOIs | |
Publication status | Published - 2018 |
Keywords
- FFLUX
- Machine Learning
- Quantum chemical topology (QCT)
- Force Field
- peptide
- QTAIM
- Kriging
Research Beacons, Institutes and Platforms
- Manchester Institute of Biotechnology
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Towards the simulation of biomolecules: optimisation of peptide-capped glycine using FFLUX
Thacker, J. (Creator), Wilson, A. (Creator), Hughes, Z. (Creator), Burn, M. J. (Creator), Maxwell, P. (Creator), Popelier, P. (Creator) & Howell, A. (Creator), figshare , 12 Feb 2018
DOI: 10.6084/m9.figshare.5877985.v1
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