Molecular Visualization with GGMolVis
This notebook provides some basic usage examples of the GGMolVis library.
Currently, they are proof of concept examples and are subject to change (and implement) in the future.
Please refer to the Installation guide for instructions on how to install the library.
[1]:
import MDAnalysis as mda
from ggmolvis.tests.data import PSF, DCD
from MDAnalysis.analysis.rms import RMSD
import molecularnodes as mn
import numpy as np
import bpy
import ggmolvis
from ggmolvis.ggmolvis import GGMolVis
/Users/scottzhuang/mambaforge/envs/ggmolvis/lib/python3.11/site-packages
Read blend: "/Users/scottzhuang/git_rego/ggmolvis/examples/ggmolvis_3.blend"
Creating new GGMolVis
[4]:
print(f'ggmolvis version: {ggmolvis.__version__}')
print(f'ggmolvis path: {ggmolvis.__file__}')
print(f'molecularnodes version: {mn.__file__}')
ggmolvis version: 0.0.0+32.g11e3891.dirty
ggmolvis path: /Users/scottzhuang/git_rego/ggmolvis/ggmolvis/__init__.py
molecularnodes version: /Users/scottzhuang/mambaforge/envs/ggmolvis/lib/python3.11/site-packages/molecularnodes/__init__.py
Trajectory Visualization
Load the trajectory file by creating a MDAnalysis Universe object. Replace PSF to your own topology file and DCD to your own trajectory file.
[5]:
u = mda.Universe(PSF, DCD)
/Users/scottzhuang/mambaforge/envs/ggmolvis/lib/python3.11/site-packages/MDAnalysis/coordinates/DCD.py:165: DeprecationWarning: DCDReader currently makes independent timesteps by copying self.ts while other readers update self.ts inplace. This behavior will be changed in 3.0 to be the same as other readers. Read more at https://github.com/MDAnalysis/mdanalysis/issues/3889 to learn if this change in behavior might affect you.
warnings.warn("DCDReader currently makes independent timesteps"
Initialize the GGMolVis object. It can be thought of as a Figure or a canvas for the molecular visualization.
[6]:
ggmv = GGMolVis()
Select molecular entities of interest to be visualized. Refer to: https://docs.mdanalysis.org/stable/documentation_pages/selections.html for the selection syntax.
[7]:
residues_ag = u.select_atoms('resid 127 40')
protein_ag = u.select_atoms('protein')
Here we include our molecules into the GGMolVis object by calling the molecule method.
[8]:
residue_mol = ggmv.molecule(residues_ag)
protein_mol = ggmv.molecule(protein_ag, style='cartoon')
protein_surface_mol = ggmv.molecule(protein_ag, style='surface', material='transparent')
Render the current frame by calling the render method.
[ ]:
residue_mol.render()
Render the selected frame by calling the render(frame) method.
[11]:
residue_mol.render(frame=60)
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpe5t3efjj.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpe5t3efjj.PNG'
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You can render the whole trajectory by calling the .render(mode='movie') method.
[ ]:
residue_mol.render(mode='movie')
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpdt6p703c.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpdt6p703c.PNG'
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You can change the representation style by calling set_style method.
[12]:
residue_mol.set_style('ball_and_stick')
[13]:
residue_mol.render()
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpdt6p703c.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpdt6p703c.PNG'
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Each molecule has a unique camera view pointing to the center of the molecule. There is also a global camera view. You can render different camera views by calling render with different molecules.
[14]:
ggmv.global_camera.render()
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmp4iphu0ds.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmp4iphu0ds.PNG'
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Alternatively, GGMolVis also provides a visualize method to AtomGroup.
[15]:
residues_ag.visualize()
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpwk_toxj1.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpwk_toxj1.PNG'
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[15]:
<ggmolvis.sceneobjects.molecules.Molecule at 0x371dfc0d0>
Geometric feature Visualization
Visualize simple geometric features, e.g. distance can be done by calling the distance method.
[16]:
res_1 = residues_ag.residues[0].atoms
res_2 = residues_ag.residues[1].atoms
line = ggmv.distance(res_1, res_2, location=(5,0,0))
[17]:
line.render()
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpor3nc2eq.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpor3nc2eq.PNG'
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Analysis Visualization
[18]:
rmsd = RMSD(u.select_atoms('name CA'))
rmsd.run()
[18]:
<MDAnalysis.analysis.rms.RMSD at 0x371df9bd0>
[19]:
vis = rmsd.visualize()
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpw8_mwxcr.PNG
Saved: '/var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmpw8_mwxcr.PNG'
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[ ]:
vis.render(mode='movie')
Rendering to: /var/folders/fn/_k4nj2nd6zv85t7_r3417nb40000gn/T/tmplda9vmc2.mp4
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