def test_gyration_radius():
stack = strucio.load_structure(join(data_dir("structure"), "1l2y.mmtf"))
radii = struc.gyration_radius(stack)
# Compare with results from MDTraj
exp_radii = \
[7.30527532, 7.34189463, 7.21863721, 7.29877736, 7.25389752, 7.22292189,
7.20646252, 7.27215909, 7.30437723, 7.30455437, 7.37979331, 7.14176259,
7.20674397, 7.27594995, 7.31665835, 7.29850786, 7.34378951, 7.2642137,
7.20727158, 7.16336879, 7.3479218, 7.19362027, 7.24841519, 7.29229237,
7.15243826, 7.31285673, 7.22585756, 7.25467109, 7.3493648, 7.34203588,
7.3310182, 7.29236536, 7.20527373, 7.33138918, 7.2284936, 7.40374312,
7.24856173, 7.25581809]
assert radii.tolist() == pytest.approx(exp_radii, abs=2e-2)
# Same for atom array instead of stack
array = stack[0]
radius = struc.gyration_radius(array)
assert radius == pytest.approx(exp_radii[0], abs=2e-2)
print(" ... writing frame[1] ... ")
frame_1 = template_model.copy()
frame_1.coord = trajectory[1].coord
save_structure("frame_1_coord.pdb", frame_1)
save_structure("frame_1.pdb", trajectory[1])
print(" ... done ... ")
print(" ... writing end frame ...")
frame_end = template_model.copy()
frame_end.coord = trajectory[-1].coord
save_structure("frame_end_coord.pdb", frame_end)
save_structure("frame_end.pdb", trajectory[-1])
print(" ... done ... ")
rmsd_overall = struc.rmsd(trajectory[0], trajectory)
radius_overall = struc.gyration_radius(trajectory)
# kinase left
trajectory_kinase_left, transform = struc.superimpose(
trajectory_kinase_left[0], trajectory_kinase_left)
rmsd_kinase_left = struc.rmsd(trajectory_kinase_left[0],
trajectory_kinase_left)
radius_kinase_left = struc.gyration_radius(trajectory_kinase_left)
# kinase right
trajectory_kinase_right, transform = struc.superimpose(
trajectory_kinase_right[0], trajectory_kinase_right)
rmsd_kinase_right = struc.rmsd(trajectory_kinase_right[0],
trajectory_kinase_right)
radius_kinase_right = struc.gyration_radius(trajectory_kinase_right)
ax.set_ylabel("RMSD (Angstrom)")
figure.tight_layout()
########################################################################
# As we can see the simulation seems to converge already in the
# beginning of the simulation. After a few ps the RMSD stays in a range
# of approx. 2 - 3 Angstrom. However it seems like there are two kinds
# of quasi-dicrete states as the two plateaus suggest. For further
# investigation we would require more simulation time.
#
# In order to better evaluate the unfolding of our miniprotein in the
# course of simulation, we calculate and plot the radius of gyration
# (a measure for the protein radius).
radius = struc.gyration_radius(trajectory)
figure = plt.figure(figsize=(6,3))
ax = figure.add_subplot(111)
ax.plot(time, radius, color=biotite.colors["dimorange"])
ax.set_xlim(0,1000)
ax.set_xlabel("Time (ps)")
ax.set_ylabel("Radius of gyration (Angstrom)")
figure.tight_layout()
########################################################################
# From this perspective, the protein seems really stable.
# The radius does merely fluctuate in a range of approx. 0.5 Angstrom
# during the entire simulation.
#
# Let's have a look at single amino acids:
def rmsf_plot(topology,
xtc_traj,
start_frame=None,
stop_frame=None,
write_dat_files=None):
# Gromacs does not set the element symbol in its PDB files,
# but Biotite guesses the element names from the atom names,
# emitting a warning
template = strucio.load_structure(topology)
# The structure still has water and ions, that are not needed for our
# calculations, we are only interested in the protein itself
# These are removed for the sake of computational speed using a boolean
# mask
protein_mask = struc.filter_amino_acids(template)
template = template[protein_mask]
residue_names = struc.get_residues(template)[1]
xtc_file = XTCFile()
xtc_file.read(xtc_traj,
atom_i=np.where(protein_mask)[0],
start=start_frame,
stop=stop_frame + 1)
trajectory = xtc_file.get_structure(template)
time = xtc_file.get_time() # Get simulation time for plotting purposes
trajectory = struc.remove_pbc(trajectory)
trajectory, transform = struc.superimpose(trajectory[0], trajectory)
rmsd = struc.rmsd(trajectory[0], trajectory)
figure = plt.figure(figsize=(6, 3))
ax = figure.add_subplot(111)
ax.plot(time, rmsd, color=biotite.colors["dimorange"])
ax.set_xlim(time[0], time[-1])
ax.set_ylim(0, 2)
ax.set_xlabel("Time (ps)")
ax.set_ylabel("RMSD (Å)")
figure.tight_layout()
radius = struc.gyration_radius(trajectory)
figure = plt.figure(figsize=(6, 3))
ax = figure.add_subplot(111)
ax.plot(time, radius, color=biotite.colors["dimorange"])
ax.set_xlim(time[0], time[-1])
ax.set_ylim(14.0, 14.5)
ax.set_xlabel("Time (ps)")
ax.set_ylabel("Radius of gyration (Å)")
figure.tight_layout()
# In all models, mask the CA atoms
ca_trajectory = trajectory[:, trajectory.atom_name == "CA"]
rmsf = struc.rmsf(struc.average(ca_trajectory), ca_trajectory)
figure = plt.figure(figsize=(6, 3))
ax = figure.add_subplot(111)
res_count = struc.get_residue_count(trajectory)
ax.plot(np.arange(1, res_count + 1),
rmsf,
color=biotite.colors["dimorange"])
ax.set_xlim(1, res_count)
ax.set_ylim(0, 1.5)
ax.set_xlabel("Residue")
ax.set_ylabel("RMSF (Å)")
figure.tight_layout()
if write_dat_files == True:
# Write RMSD *.dat file
frames = np.array(range(start_frame - 1, stop_frame), dtype=int)
frames[0] = 0
df = pd.DataFrame(data=rmsd, index=frames, columns=["RMSD Values"])
df.index.name = 'Frames'
df.to_csv('rmsd.dat', header=True, index=True, sep='\t', mode='w')
# Write RMSF *.dat file
df1 = pd.DataFrame(data=rmsf,
index=residue_names,
columns=["RMSF Values"])
df1.index.name = 'Residues'
df1.to_csv('rmsf.dat', header=True, index=True, sep='\t', mode='w')
plt.show()
