Towards the simulation of biomolecules: optimisation of peptide-capped glycine using FFLUX

Research output: Contribution to journalArticlepeer-review

  • External authors:
  • Joseph Thacker
  • Alex Wilson
  • Zak Hughes
  • Matthew Burn
  • Peter I. Maxwell


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.

Bibliographical metadata

Original languageEnglish
Early online date11 Feb 2018
Publication statusPublished - 2018

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