Setting phases manually

Depending on the situation, some lipids - or other membrane molecules - might not undergo a phase transition during the simulations. For instance, the dioleoyl-glycerophosphocholine (DOPC) has a transition temperature of -17C, so it more than likely that it will remain in the fluid phase for all simulations run in the water (> 0C). The problem of these molecules is that ML-LPA cannot be trained to predict their phases, and because of that analysis of the local environment cannot be processed.

To avoid these problem, phases can be assigned manually in ML-LPA to an instance of the System class.

Manual phase assignment

Single assignment

To assign the lipid phases in a simulation, we need to first load the simulation files in an instance of the System class. Then, we can use the class method .setPhases() to assign the phases. This method only takes as an argument the string with the name of the phase.

import mllpa

# Load the unknown system
unknown_system = mllpa.openSystem('unknown.gro', 'unknown.tpr', 'DOPC')

# Assign the phases
unknown_system.setPhases("fluid")

ML-LPA will then process all the lipids in the system and assign to each of them the given phase. The final result can be accessed through the .states attribute of the instance of the System class as shown previously.

Molecule-by-molecule assignment

The method .setPhases() can also be used to assign a whole NumPy string array to the molecules stored in the instance.

unknown_system.setPhases(lipid_phases)

In this example, we call a NumPy array named lipid_phases which have been generated outside of the example script.

The NumPy string array used as input should have the dimension (# frames, # molecules).

What is next?

Now you know how the phases of your unknown systems can been predicted, you can start to analyse the local environment of the lipids.
You can also store the results in a file.

Check the API

The following elements have been used in this tutorial:

System class