title: Molecular dynamics simulation of tricaproin in gas phase using machine-learning potential ANI2x
author: Melcr, Josef
description: Tricaproin (Glycerol trihexanoate) is an example of a triglyceride molecule with very short alkyl tails attached to the glycerol moiety, and this deposit contains a 10 ns long simulation of tricaproin in a gas phase. The model chemistry (a.k.a. interaction potential or force field) is the machine-learning potential ANI2x implemented in python package torchANI, which has a close-to-DFT accuracy, yet low cost compared to DFT or other electronic structure theories. Molecular dynamics were run using ASE with Langevin integrator at a constant temperature of 310 K. The resulting trajectory was written every 1 ps ("traj.h5", can be viewed in ASEgui), and gathered every 10 ps in a XTC format ("traj.xtc", open in MDAnalysis, VMD, UnityMol, GROMACS tools ...).   Detailed simulation settings are in the python script.   This simulation was performed for the purpose of building a coarse grained Martini 3 model of this molecule.   ANI2x https://doi.org/10.26434/chemrxiv.11819268.v1 torchANI https://aiqm.github.io/torchani/index.html ASE https://wiki.fysik.dtu.dk/ase/tutorials/md/md.html#constant-temperature-md