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

Figures & data

Figure 1. (Colour online) Schematic illustrating the atomic local frame (ALF) of N-methylacetamide.

Figure 2. The prediction error of the sum of the atomic energies for the 500 geometries in the test set.

Figure 3. (Colour online) The global minimum geometry of peptide-capped glycine obtained at B3LYP/apc-1 level, with atomic labelling.

Figure 4. (Colour online) The energy convergence of 100 representative structures from the 4000 randomly generated structures, where the 0 kJ mol⁻¹ values refers to the global minimum energy determined by GAUSSIAN09.

Notes: Colours only serve to separate out the various trajectories.

Table 1. A comparison of selected geometric properties of the global energy minimum generated by an ab initio calculation at the B3LYP/acp-1 level of theory and that generated by FFLUX.

Property	Method		Error
	B3LYP	FFLUX
H O/Å	2.046	2.045	0.001
N O/Å	2.944	2.940	0.004
N O/°	145.9	145.3	0.6
ψ/°	67.7	63.3	4.4
φ/°	−82.5	−82.3	0.2
Final energy/kJ mol^−1	−1,198,554.42	−1,198,555.31	−0.89
RMSD/Å			0.15
RMSD (excl. H)/Å			0.05

Figure 5. (Colour online) The relative energy (compared to the target minimum) of the system where the initial configuration was outside of the training domain as a function of time.

Figure 6. (Colour online) The energy difference of glycine dipeptide, where ΔEnergy (y-axis) is the absolute energy difference of the current time step (t _n ) minus the energy of the previous time step (t _n−1).

Figure 7. (Colour online) A comparative RMSD of any geometry in the trajectory against the B3LYP target minimum geometry.