Path B - Module 32: Visualizing Interaction Matrices#

Identifying contacts in a table is useful, but seeing them in a Matrix Plot is transformative. For an industrial enzyme, you want to see if the plastic substrate is interacting with the entire active site cleft or just a few residues.

In this module, you will learn to use show_contacts() to generate a visual heatmap of the binding interface.

import molsysmt as msm
from molsysmt import systems

# Load our engineered complex (Enzyme + BHET substrate)
petase = msm.convert('pdb:6EQE', to_form='molsysmt.MolSys', selection='molecule_type=="protein"')
bhet = msm.convert('C1=CC(=CC=C1C(=O)OCCO)C(=O)OCCO', from_form='string:smiles', to_form='molsysmt.MolSys')
molsys = msm.merge([petase, bhet])

1. The Interaction Heatmap#

The function show_contacts() generates a plot where each pixel represents the distance between an atom of the protein and an atom of the substrate. Darker areas mean closer interaction.

# Generate the contact plot
msm.structure.show_contacts(molsys, selection='molecule_type=="small molecule"', 
                            selection_2='molecule_type=="protein"', threshold='0.6 nm')

2. Identifying Interaction Clefts#

In the PETase, the active site is an open cleft. Look for the residues that appear as “bands” in the plot: those are the ones providing the stabilization for the plastic monomer.

3. Comparing Wild-type vs Mutant Contacts#

In a real engineering project, you would plot both systems side-by-side to see if your mutation created new contact points.

🏆 Path B Challenge: The Heatmap Analyst#

  1. Change the element to 'group' in the show_contacts function to get a residue-residue matrix instead of atom-atom.

  2. Identify the top 5 residues with the strongest signal in the plot.

  3. Use msm.get_label() on those indices to verify their biological identity.

You now have a powerful tool for reporting! In Module 33, we will calculate global metrics like the Radius of Gyration to see if our enzyme became more compact.