Tutorial #1: Working with the prolint2 Universe#

In this tutorial, we will focus on working with the prolint2 Universe object, which allows you to access and manipulate data related to lipid-protein interactions. You will learn how to load your trajectory data, and how to modify the query and database groups to analyze lipid-protein interactions.

Prerequisites#

Before you begin, make sure you have prolint2 installed in your Python environment.

from prolint2 import Universe
from prolint2.sampledata import GIRKDataSample

GIRK = GIRKDataSample()

Creating a prolint2 Universe Instance#

ProLint can read data directly from an MDAnalysis Universe object, which is often used in molecular dynamics simulations. You can create a prolint2 Universe object from an existing MDAnalysis Universe, and then you can further manipulate the query and database AtomGroups.

  • Using MDAnalysis to Create a Universe Instance

# Create an MDAnalysis Universe instance
mda_u = MDUniverse(GIRK.coordinates, GIRK.trajectory)

# Define custom query and database AtomGroups
mda_u_query = mda_u.select_atoms('protein and name BB')
mda_u_db = mda_u.select_atoms('resname POPE')

# Create a ProLint Universe instance from the MDAnalysis Universe
u = Universe(universe=mda_u)

Alternatively, you can create a ProLint Universe instance directly from the MDAnalysis Universe with query and database information:

# Create a ProLint Universe instance with query and database
u = Universe(universe=mda_u, query=mda_u_query, db=mda_u_db)

Accessing the Query and Database AtomGroups#

Both the query and database AtomGroups in the prolint2 Universe are wrappers around the MDAnalysis AtomGroups. This allows you to leverage all the functionality of MDAnalysis AtomGroups while also benefiting from ProLint-specific functions for lipid-protein interaction analysis.

  • Example: Accessing AtomGroup Information

You can access various information about the query and database AtomGroups:

# Accessing unique residue names in the database
u.database.unique_resnames

# Get residue names for specific residue numbers
u.database.get_resnames([2345, 2346, 3050])

# Filter residue IDs by a specific residue name
u.database.filter_resids_by_resname([2345, 2346, 3050], 'CHOL')

# Get residue names for specific residue numbers and store the result in a dictionary
u.query.get_resnames([1, 2, 3, 4, 5], out=dict)

Modifying the Query and Database AtomGroups#

prolint2 provides methods for modifying the query and database AtomGroups. These modifications can be useful for tailoring the AtomGroups to your specific analysis needs.

  • Removing from prolint2 AtomGroup

You can remove elements from an AtomGroup using the remove method. The method combines all input arguments into a single selection string concatenated with or statements. The resulting AtomGroup is a new instance, and it does not modify the original AtomGroup.

# Remove all residues with resname 'ARG' from the query
s = u.query.remove(resname='ARG')

# Remove all residues with resname 'ARG' and all residue numbers lower than 100
s = u.query.remove(resname='ARG', resnum=[*range(100)])

# More complex example: Remove all residues with resname 'ARG' and the residue number 1,
# and all atoms with the name 'BB' and the atomids 1-9
s = u.query.remove(resname='ARG', resnum=[1], atomname=['BB'], atomids=[1, 2, 3, 4, 5, 6, 7, 8, 9])

# To modify the original AtomGroup, use assignment
u.query = u.query.remove(resname='ARG')

  • Adding to prolint2 AtomGroup

To add elements back to an AtomGroup, you can use the add method. This allows you to revert any removals or extend the AtomGroup.

# Add back the residues that were removed from the query
u.query = u.query.add(resname='ARG')

Computing Contacts#

After modifying the query AtomGroup, you can compute lipid-protein contacts using the compute_contacts method. This method calculates interactions between the query and the database based on a specified cutoff distance.

# Compute contacts with a cutoff distance of 7 angstroms
c = u.compute_contacts(cutoff=7)

# Get the number of residues for which contacts have been computed
len(c.contact_frames.keys())

By following this tutorial, you should now be comfortable with creating and working with the prolint2 Universe object for lipid-protein interaction analysis and visualization. This tool offers a flexible and powerful way to study molecular interactions in your simulations.