Towards the simulation of biomolecules: optimisation of peptide-capped glycine using FFLUX |
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Authors: | Joseph C R Thacker Alex L Wilson Zak E Hughes Matthew J Burn Peter I Maxwell |
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Institution: | 1. Manchester Institute of Biotechnology (MIB) , Manchester, UK;2. School of Chemistry, University of Manchester , Manchester, UK |
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Abstract: | AbstractThe 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. |
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Keywords: | FFLUX machine learning quantum chemical topology (QCT) force field peptide QTAIM kriging |
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