---

search: exclude: true¶

Visualization¶

Visualize the best fitted pdb by powerfit with MolStar.

This notebook expects you have executed protein-detective powerfit run command as described in README.md.

This notebook must be executed to see the visualization.

In [1]:

from pathlib import Path

from pathlib import Path

In [2]:

# Replace `../mysession` with your own session directory.
session_dir = Path("../mysession")
session_dir

# Replace `../mysession` with your own session directory. session_dir = Path("../mysession") session_dir

Out[2]:

PosixPath('../mysession')

Fit the models and write metadata to csv files. This will apply the rotation and translation of the best solution for each template structure.

In [3]:

!protein-detective powerfit fit-models {session_dir} --output {session_dir}/fitted.csv
!protein-detective powerfit report {session_dir} --output {session_dir}/report.csv
!protein-detective powerfit list-runs {session_dir} --output {session_dir}/runs.csv

!protein-detective powerfit fit-models {session_dir} --output {session_dir}/fitted.csv !protein-detective powerfit report {session_dir} --output {session_dir}/report.csv !protein-detective powerfit list-runs {session_dir} --output {session_dir}/runs.csv

Writing fitted model PDB files: 100%|█████████| 114/114 [00:01<00:00, 74.53it/s]

In [4]:

from protein_detective.visualization import load_fitted_models

from protein_detective.visualization import load_fitted_models

In [5]:

fitted_csv = session_dir / "fitted.csv"
report_csv = session_dir / "report.csv"
runs_csv = session_dir / "runs.csv"
df = load_fitted_models(fitted_models_csv=fitted_csv, report_csv=report_csv, runs_csv=runs_csv)
df

fitted_csv = session_dir / "fitted.csv" report_csv = session_dir / "report.csv" runs_csv = session_dir / "runs.csv" df = load_fitted_models(fitted_models_csv=fitted_csv, report_csv=report_csv, runs_csv=runs_csv) df

Out[5]:

	powerfit_run_id	structure	rank	fitted_model_file	unfitted_model_file	cc	fishz	relz	translation	rotation	uniprot_accessions	structure_id	is_alphafold	density_map	run_dir	options
0	myrun1	3i8z_updated_A2A.cif.gz	1	../mysession/powerfit/myrun1/3i8z_updated_A2A....	../mysession/combined_output/3i8z_updated_A2A....	0.598	0.690	12.959	[239.46, 187.27, 211.83]	[-0.238, 0.322, 0.916, 0.916, -0.238, 0.322, 0...	[O00257]	3I8Z	False	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
1	myrun1	6mzc_updated_E2A.cif.gz	1	../mysession/powerfit/myrun1/6mzc_updated_E2A....	../mysession/combined_output/6mzc_updated_E2A....	0.547	0.614	14.671	[199.55, 214.9, 165.78]	[1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, -1.0]	[O00268]	6MZC	False	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
2	myrun1	6mzd_updated_D2A.cif.gz	1	../mysession/powerfit/myrun1/6mzd_updated_D2A....	../mysession/combined_output/6mzd_updated_D2A....	0.514	0.568	13.612	[273.23, 251.74, 165.78]	[0.916, 0.238, -0.322, -0.238, -0.322, -0.916,...	[O00268]	6MZD	False	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
3	myrun1	AF-O00110-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-O00110-F1-mode...	../mysession/combined_output/AF-O00110-F1-mode...	0.471	0.512	14.765	[236.39, 236.39, 227.18]	[0.0, 1.0, 0.0, 0.0, 0.0, -1.0, -1.0, 0.0, 0.0]	[O00110]	AF-O00110-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
4	myrun1	AF-A0A2R8Y619-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-A0A2R8Y619-F1-...	../mysession/combined_output/AF-A0A2R8Y619-F1-...	0.463	0.501	13.182	[221.04, 227.18, 190.34]	[0.0, -1.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 0.0]	[A0A2R8Y619]	AF-A0A2R8Y619-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
109	myrun1	AF-A6NKF2-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-A6NKF2-F1-mode...	../mysession/combined_output/AF-A6NKF2-F1-mode...	0.227	0.231	9.861	[202.62, 208.76, 184.2]	[-1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, -1.0]	[A6NKF2]	AF-A6NKF2-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
110	myrun1	AF-A8MPP1-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-A8MPP1-F1-mode...	../mysession/combined_output/AF-A8MPP1-F1-mode...	0.205	0.208	14.988	[199.55, 168.85, 214.9]	[-0.238, -0.916, -0.322, -0.916, 0.322, -0.238...	[A8MPP1]	AF-A8MPP1-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
111	myrun1	AF-A8MQ14-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-A8MQ14-F1-mode...	../mysession/combined_output/AF-A8MQ14-F1-mode...	0.205	0.208	16.845	[257.88, 227.18, 214.9]	[-0.238, -0.916, -0.322, -0.916, 0.322, -0.238...	[A8MQ14]	AF-A8MQ14-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
112	myrun1	AF-O14497-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-O14497-F1-mode...	../mysession/combined_output/AF-O14497-F1-mode...	0.194	0.196	12.303	[190.34, 153.5, 239.46]	[-0.322, -0.238, 0.916, 0.916, -0.322, 0.238, ...	[O14497]	AF-O14497-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...
113	myrun1	AF-A3KN83-F1-model_v6.cif.gz	1	../mysession/powerfit/myrun1/AF-A3KN83-F1-mode...	../mysession/combined_output/AF-A3KN83-F1-mode...	0.182	0.184	14.510	[205.69, 184.2, 233.32]	[0.916, -0.238, 0.322, 0.238, -0.322, -0.916, ...	[A3KN83]	AF-A3KN83-F1	True	../mysession/powerfit/myrun1/ribosome-KsgA.map	../mysession/powerfit/myrun1	--workers-per-gpu 2 --angle 40 --powerfit-run-...

114 rows × 16 columns

Show top 3 fitted structures with density map¶

In [6]:

from protein_detective.visualization import show_fitted_models_and_density

from protein_detective.visualization import show_fitted_models_and_density

In [9]:

show_fitted_models_and_density(
    df.head(3),
)

show_fitted_models_and_density( df.head(3), )

Show best fitted model with density map¶

Pick first and best fitted PDB to visualize

In [8]:

fitted_model_file = df.iloc[0].fitted_model_file
density_map = df.iloc[0].density_map
fitted_model_file, density_map

fitted_model_file = df.iloc[0].fitted_model_file density_map = df.iloc[0].density_map fitted_model_file, density_map

Out[8]:

('../mysession/powerfit/myrun1/3i8z_updated_A2A.cif.gz/fit_1.pdb',
 '../mysession/powerfit/myrun1/ribosome-KsgA.map')

The view object contains the density map data whichi is very large (>10Mb). So it is not executed by default to keep the notebook size small. You can copy the code below to execute it.

from protein_detective.visualization import show_structure_and_density

view = show_structure_and_density(fitted_model_file, density_map)
view