Protein-ligand Docking tutorial using BioExcel Building Blocks (biobb)¶
-- PDB Cluster90 Binding Site Version --¶
+
This tutorial aims to illustrate the process of protein-ligand docking, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Mitogen-activated protein kinase 14 (p38-α) protein (PDB code 3HEC, https://doi.org/10.2210/pdb3HEC/pdb), a well-known Protein Kinase enzyme, +in complex with the FDA-approved Imatinib, (PDB Ligand code STI, DrugBank Ligand Code DB00619), a small molecule kinase inhibitor used to treat certain types of cancer.
The tutorial will guide you through the process of identifying the active site cavity (pocket) without previous knowledge, and the final prediction of the protein-ligand complex.
Please note that docking algorithms, and in particular, AutoDock Vina program used in this tutorial, are non-deterministic. That means that results obtained when running the workflow could be diferent from the ones we obtained during the writing of this tutorial (see AutoDock Vina manual). We invite you to try the docking process several times to verify this behaviour.
--
Settings¶
Biobb modules used¶
-
+
- biobb_io: Tools to fetch biomolecular data from public databases.
- biobb_structure_utils: Tools to modify or extract information from a PDB structure file.
- biobb_chemistry: Tools to perform chemoinformatics processes.
- biobb_vs: Tools to perform virtual screening studies.
- jupyter: Free software, open standards, and web services for interactive computing across all programming languages.
- nglview: Jupyter/IPython widget to interactively view molecular structures and trajectories in notebooks.
- Input Parameters
- Fetching PDB Structure
- Extract Protein Structure @@ -14302,262 +7559,384 @@
- Questions & Comments
+
Settings¶
Biobb modules used¶
Auxiliary libraries used¶
-
+
Auxiliary libraries used¶
Conda Installation and Launch¶
-git clone https://github.com/bioexcel/biobb_wf_virtual-screening.git
+Conda Installation¶
git clone https://github.com/bioexcel/biobb_wf_virtual-screening.git
cd biobb_wf_virtual-screening
conda env create -f conda_env/environment.yml
conda activate biobb_VS_tutorial
-jupyter-notebook biobb_wf_virtual-screening/notebooks/clusterBindingSite/wf_vs_clusterBindingSite.ipynb
+jupyter-notebook biobb_wf_virtual-screening/notebooks/ebi_api/wf_vs_clusterBindingSite.ipynb
-
-Pipeline steps¶
+
+Pipeline steps¶
Pipeline stepsComparing final result with experimental structure
-
-
-
-
+
+
+
+
Initializing colab¶
The two cells below are used only in case this notebook is executed via Google Colab. Take into account that, for running conda on Google Colab, the condacolab library must be installed. As explained here, the installation requires a kernel restart, so when running this notebook in Google Colab, don't run all cells until this installation is properly finished and the kernel has restarted.
+# Only executed when using google colab
+import sys
+if 'google.colab' in sys.modules:
+ import subprocess
+ from pathlib import Path
+ try:
+ subprocess.run(["conda", "-V"], check=True)
+ except FileNotFoundError:
+ subprocess.run([sys.executable, "-m", "pip", "install", "condacolab"], check=True)
+ import condacolab
+ condacolab.install()
+ # Clone repository
+ repo_URL = "https://github.com/bioexcel/biobb_wf_virtual-screening.git"
+ repo_name = Path(repo_URL).name.split('.')[0]
+ if not Path(repo_name).exists():
+ subprocess.run(["mamba", "install", "-y", "git"], check=True)
+ subprocess.run(["git", "clone", repo_URL], check=True)
+ print("⏬ Repository properly cloned.")
+ # Install environment
+ print("⏳ Creating environment...")
+ env_file_path = f"{repo_name}/conda_env/environment.yml"
+ subprocess.run(["mamba", "env", "update", "-n", "base", "-f", env_file_path], check=True)
+ print("🎨 Install NGLView dependencies...")
+ subprocess.run(["mamba", "install", "-y", "-c", "conda-forge", "nglview==3.0.8", "ipywidgets=7.7.2"], check=True)
+ print("👍 Conda environment successfully created and updated.")
+# Enable widgets for colab
+if 'google.colab' in sys.modules:
+ from google.colab import output
+ output.enable_custom_widget_manager()
+ # Change working dir
+ import os
+ os.chdir("biobb_wf_virtual-screening/biobb_wf_virtual-screening/notebooks/clusterBindingSite")
+ print(f"📂 New working directory: {os.getcwd()}")
+Input parameters¶
Input parameters needed:
+Input parameters¶
Input parameters needed:
-
-
- pdb_code: PDB code of the experimental complex structure (if exists).
-In this particular example, the p38α structure in complex with the Imatinib drug was experimentally solved and deposited in the PDB database under the 3HEC PDB code, https://doi.org/10.2210/pdb3HEC/pdb. The protein structure from this PDB file will be used as a target protein for the docking process, after stripping the small molecule. An APO structure, or any other structure from the p38α cluster 100 (sharing a 100% of sequence similarity with the p38α structure) could also be used as a target protein. This structure of the protein-ligand complex will be also used in the last step of the tutorial to check how close the resulting docking pose is from the known experimental structure.
+ - pdb_code: PDB code of the experimental complex structure (if exists).
+In this particular example, the p38α structure in complex with the Imatinib drug was experimentally solved and deposited in the PDB database under the 3HEC PDB code (https://doi.org/10.2210/pdb3HEC/pdb). The protein structure from this PDB file will be used as a target protein for the docking process, after stripping the small molecule. An APO structure, or any other structure from the p38α cluster 100 (sharing a 100% of sequence similarity with the p38α structure) could also be used as a target protein. This structure of the protein-ligand complex will be also used in the last step of the tutorial to check how close the resulting docking pose is from the known experimental structure.
+
-
-
- ligandCode: Ligand PDB code (3-letter code) for the small molecule (e.g. STI, DrugBank Ligand Code DB00619).
+ - ligandCode: Ligand PDB code (3-letter code) for the small molecule (e.g. STI, DrugBank Ligand Code DB00619).
In this particular example, the small molecule chosen for the tutorial is the FDA-approved drug Imatinib (PDB Code STI, DrugBank Ligand Code DB00619), a type of cancer growth blocker, used in diferent types of leukemia.
import nglview
+
+import nglview
import ipywidgets
-pdb_code = "3HEC" # P38 + Imatinib
+pdb_code = "3HEC" # P38 + Imatinib
-ligand_code = "STI" # Imatinib
+ligand_code = "STI" # Imatinib
-
-
-
Fetching PDB structure¶
Downloading PDB structure with the protein molecule from the PDBe database.
-Alternatively, a PDB file can be used as starting structure.
+
+
Fetching PDB structure¶
Downloading PDB structure with the protein molecule from the PDBe database.
+Alternatively, a PDB file can be used as starting structure.
Building Blocks used:
- Pdb from biobb_io.api.pdb
- +
+
from biobb_io.api.pdb import pdb
+
+from biobb_io.api.pdb import pdb
-download_pdb = "download.pdb"
+download_pdb = "download.pdb"
prop = {
- "pdb_code": pdb_code,
- "filter": ["ATOM", "HETATM"]
+ "pdb_code": pdb_code,
+ "filter": ["ATOM", "HETATM"]
}
pdb(output_pdb_path=download_pdb,
properties=prop)
-
-
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
+
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
Note (and try to identify) the Imatinib small molecule (STI) and the detergent (β-octyl glucoside) (BOG) used in the experimental reservoir solution to obtain the crystal.
view = nglview.show_structure_file(download_pdb, default=True)
+
+view = nglview.show_structure_file(download_pdb, default=True)
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Extract Protein Structure¶
Extract protein structure from the downloaded PDB file. Removing any extra molecule (ligands, ions, water molecules).
+
+
Extract Protein Structure¶
Extract protein structure from the downloaded PDB file. Removing any extra molecule (ligands, ions, water molecules).
The protein structure will be used as a target in the protein-ligand docking process.
+
Building Blocks used:
- extract_molecule from biobb_structure_utils.utils.extract_molecule
- +
+
from biobb_structure_utils.utils.extract_molecule import extract_molecule
+
+from biobb_structure_utils.utils.extract_molecule import extract_molecule
-pdb_protein = "pdb_protein.pdb"
+pdb_protein = "pdb_protein.pdb"
extract_molecule(input_structure_path=download_pdb,
- output_protein_path = pdb_protein)
+ output_molecule_path = pdb_protein)
-
-
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
+
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
Note that the small molecules included in the original structure are now gone. The new structure only contains the protein molecule, which will be used as a target for the protein-ligand docking.
view = nglview.show_structure_file(pdb_protein, default=True)
+
+view = nglview.show_structure_file(pdb_protein, default=True)
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Computing Protein Cavities (Cluster90 Binding Site)¶
Computing the protein cavities (pockets) using information from the PDB Cluster90. The PDB Cluster90 is a collection derived from the PDB database, containing structures having less than 90% sequence identity to each other. The Cluster90 Binding Site is using information from all the structures of the Cluster90 collection for a particular input protein to discover the possible binding sites from small molecules attached to similar proteins.
These cavities will be then used in the docking procedure to try to find the best region of the protein surface where the small molecule can bind.
-Although in this particular example we already know the binding site region, as we started from a protein-ligand complex structure where the ligand was located in the same binding site as Imatinib is binding, this is not always the case. In the cases where we do not know these regions, the Cluster90 binding site utility will help us identifying the possible binding sites of our target protein.
-
+
+
Computing Protein Cavities (Cluster90 Binding Site)¶
Computing the protein cavities (pockets) using information from the PDB Cluster90. The PDB Cluster90 is a collection derived from the PDB database, containing structures having less than 90% sequence identity to each other. The Cluster90 Binding Site is using information from all the structures of the Cluster90 collection for a particular input protein to discover the possible binding sites from small molecules attached to similar proteins.
These cavities will be then used in the docking procedure to try to find the best region of the protein surface where the small molecule can bind.
+Although in this particular example we already know the binding site region, as we started from a protein-ligand complex structure where the ligand was located in the same binding site as Imatinib is binding, this is not always the case. In the cases where we do not know these regions, the Cluster90 binding site utility will help us identifying the possible binding sites of our target protein.
+
Building Blocks used:
- pdb_cluster_zip from biobb_io.api.pdb_cluster_zip
- bindingsite from biobb_vs.utils.bindingsite
- +
+
Getting Cluster 90 collection¶
Extracting the Cluster90 collection from the input PDB structure. The collection will contain all the structures in the PDB database having less than 90% sequence identity to the input structure (our target protein).
+
Getting Cluster 90 collection¶
Extracting the Cluster90 collection from the input PDB structure. The collection will contain all the structures in the PDB database having less than 90% sequence identity to the input structure (our target protein).
Please note that depending on the size of the cluster, the execution can take a while (minutes).
from biobb_io.api.pdb_cluster_zip import pdb_cluster_zip
+
+from biobb_io.api.pdb_cluster_zip import pdb_cluster_zip
-pdb_cluster = "pdb_cluster.zip"
+pdb_cluster = "pdb_cluster.zip"
prop = {
- "pdb_code": pdb_code,
- "filter": ["ATOM", "HETATM"],
- "cluster": 90
+ "pdb_code": pdb_code,
+ "filter": ["ATOM", "HETATM"],
+ "cluster": 90
}
pdb_cluster_zip(output_pdb_zip_path = pdb_cluster,
properties=prop)
-
-
Extracting the Cluster90 Binding Site(s)¶
Extracting the protein binding site(s) from the Cluster90 collection. There are two ways in which the Cluster90 Binding Site can be used:
+Extracting the Cluster90 Binding Site(s)¶
Extracting the protein binding site(s) from the Cluster90 collection. There are two ways in which the Cluster90 Binding Site can be used:
-
-
- With information about the ligand: In this particular example we already know the ligand we want to dock, and also that the PDB database contain an experimental structure where the ligand was solved in complex with our protein of interest (p38-α Tyrosine kinase). In that case, the ligand id can be used to guide the binding site tool.
- Without information about the ligand: If the docking study starts from a protein receptor with no information about the binding site or any known protein-ligand complex, the binding site tool can not be guided. Still, the tool should be able to extract binding site(s) information from similar proteins solved with small molecules attached (if any).
- With information about the ligand: In this particular example we already know the ligand we want to dock, and also that the PDB database contain an experimental structure where the ligand was solved in complex with our protein of interest (p38-α Tyrosine kinase). In that case, the ligand id can be used to guide the binding site tool.
- Without information about the ligand: If the docking study starts from a protein receptor with no information about the binding site or any known protein-ligand complex, the binding site tool can not be guided. Still, the tool should be able to extract binding site(s) information from similar proteins solved with small molecules attached (if any).
This example is using the ligand id to guide the binding site tool, but we invite you to try and explore the differences in the output removing this input information (ligand property in the next building block).
The Cluster90 binding site tool is internally running sequence alignments to structurally superpose the structures contained in the Cluster90 collection and extract the residue numbering corresponding to the binding site residues. Thus, sequence alignment parameters can be changed using building block input properties. In this example, we have chosen the well-known blosum62 substitution matrix, with a penalty for opening a gap of -10.0, and a penalty to extend a gap of -0.5. The total number of superimposed ligands to be extracted from the cluster is limited at 15, and the cut-off distance around the ligand atoms to consider a residue to be part of a binding site is fixed at 5 Ångstroms.
-from biobb_vs.utils.bindingsite import bindingsite
+
+from biobb_vs.utils.bindingsite import bindingsite
-output_bindingsite = "bindingsite.pdb"
+output_bindingsite = "bindingsite.pdb"
prop = {
- "ligand": ligand_code,
- "matrix_name": "BLOSUM62",
- "gap_open": -10.0,
- "gap_extend": -0.5,
- "max_num_ligands": 15,
- "radius": 5
+ "ligand": ligand_code,
+ "matrix_name": "BLOSUM62",
+ "gap_open": -10.0,
+ "gap_extend": -0.5,
+ "max_num_ligands": 15,
+ "radius": 5
}
bindingsite(input_pdb_path = pdb_protein,
@@ -14565,423 +7944,483 @@ Extracting the Cluster90 Bindi
output_pdb_path = output_bindingsite,
properties=prop)
-
-
Visualizing selected pockets (cavities)¶
Visualizing the selected pockets (cavities) from the generated list using NGL viewer.
Visualizing selected pockets (cavities)¶
Visualizing the selected pockets (cavities) from the generated list using NGL viewer.
Protein residues forming the cavity are shown in licorice representation. Pockets are represented in a greyish surface. The original ligand (if exists) is shown in green-colored ball and stick representation.
-view = nglview.show_structure_file(download_pdb, default=False)
+
+view = nglview.show_structure_file(download_pdb, default=False)
# ligand
-view[0].add_representation(repr_type='ball+stick',
- selection='STI',
+view[0].add_representation(repr_type='ball+stick',
+ selection='STI',
aspect_ratio=4,
- color='green')
+ color='green')
-view[0].add_representation(repr_type='cartoon',
- selection='not het',
+view[0].add_representation(repr_type='cartoon',
+ selection='not het',
opacity=.2,
- color='#cccccc')
+ color='#cccccc')
-view.add_component(output_bindingsite, default=False)
-view[1].add_representation(repr_type='surface',
- selection='*',
+view.add_component(nglview.FileStructure(output_bindingsite), default=False)
+view[1].add_representation(repr_type='surface',
+ selection='*',
opacity = .3,
- radius='1.5',
+ radius='1.5',
lowResolution= True,
# 0: low resolution
smooth=1,
- useWorker= True,
+ #useWorker= True,
wrap= True)
-view[1].add_representation(repr_type='licorice',
- selection='*')
+view[1].add_representation(repr_type='licorice',
+ selection='*')
view[0].center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Generating Cavity Box¶
Generating a box surrounding the selected protein cavity (pocket), to be used in the docking procedure. The box is defining the region on the surface of the protein target where the docking program should explore a possible ligand dock.
-An offset of 12 Angstroms is used to generate a big enough box to fit the small molecule and its possible rotations.
+
+
Generating Cavity Box¶
Generating a box surrounding the selected protein cavity (pocket), to be used in the docking procedure. The box is defining the region on the surface of the protein target where the docking program should explore a possible ligand dock.
+An offset of 12 Angstroms is used to generate a big enough box to fit the small molecule and its possible rotations.
Building Blocks used:
- box from biobb_vs.utils.box
- +
+
from biobb_vs.utils.box import box
+
+from biobb_vs.utils.box import box
-output_box = "box.pdb"
+output_box = "box.pdb"
prop = {
- "offset": 12,
- "box_coordinates": True
+ "offset": 12,
+ "box_coordinates": True
}
box(input_pdb_path = output_bindingsite,
output_pdb_path = output_box,
properties=prop)
-
-
Visualizing binding site box in 3D structure¶
Visualizing the protein structure, the selected cavity, and the generated box, all together using NGL viewer. Using the original structure with the small ligand inside (Imatinib, STI, DrugBank Ligand Code DB00619), to check that the selected cavity is placed in the same region as the original ligand.
- +Visualizing binding site box in 3D structure¶
Visualizing the protein structure, the selected cavity, and the generated box, all together using NGL viewer. Using the original structure with the small ligand inside (Imatinib, STI, DrugBank Ligand Code DB00619), to check that the selected cavity is placed in the same region as the original ligand.
+#view = nglview.show_structure_file(box, default=False)
+
+#view = nglview.show_structure_file(box, default=False)
view = nglview.NGLWidget()
#s = view.add_component(pdb_single_chain)
-s = view.add_component(download_pdb)
-b = view.add_component(output_box)
-s = view.add_component(output_bindingsite)
+s = view.add_component(nglview.FileStructure(download_pdb))
+b = view.add_component(nglview.FileStructure(output_box))
+s = view.add_component(nglview.FileStructure(output_bindingsite))
atomPair = [
- [ "9999:Z.ZN1", "9999:Z.ZN2" ],
- [ "9999:Z.ZN2", "9999:Z.ZN4" ],
- [ "9999:Z.ZN4", "9999:Z.ZN3" ],
- [ "9999:Z.ZN3", "9999:Z.ZN1" ],
+ [ "9999:Z.ZN1", "9999:Z.ZN2" ],
+ [ "9999:Z.ZN2", "9999:Z.ZN4" ],
+ [ "9999:Z.ZN4", "9999:Z.ZN3" ],
+ [ "9999:Z.ZN3", "9999:Z.ZN1" ],
- [ "9999:Z.ZN5", "9999:Z.ZN6" ],
- [ "9999:Z.ZN6", "9999:Z.ZN8" ],
- [ "9999:Z.ZN8", "9999:Z.ZN7" ],
- [ "9999:Z.ZN7", "9999:Z.ZN5" ],
+ [ "9999:Z.ZN5", "9999:Z.ZN6" ],
+ [ "9999:Z.ZN6", "9999:Z.ZN8" ],
+ [ "9999:Z.ZN8", "9999:Z.ZN7" ],
+ [ "9999:Z.ZN7", "9999:Z.ZN5" ],
- [ "9999:Z.ZN1", "9999:Z.ZN5" ],
- [ "9999:Z.ZN2", "9999:Z.ZN6" ],
- [ "9999:Z.ZN3", "9999:Z.ZN7" ],
- [ "9999:Z.ZN4", "9999:Z.ZN8" ]
+ [ "9999:Z.ZN1", "9999:Z.ZN5" ],
+ [ "9999:Z.ZN2", "9999:Z.ZN6" ],
+ [ "9999:Z.ZN3", "9999:Z.ZN7" ],
+ [ "9999:Z.ZN4", "9999:Z.ZN8" ]
]
#view.shape.add_cylinder( [ 0, 2, 7 ], [ 10, 0, 9 ], [ 1, 0, 0 ], 0.1 )
# structure
-s.add_representation(repr_type='cartoon',
- selection='not het',
- color='#cccccc',
+s.add_representation(repr_type='cartoon',
+ selection='not het',
+ color='#cccccc',
opacity=.2)
# ligands box
-b.add_representation(repr_type='ball+stick',
- selection='9999',
- color='pink',
+b.add_representation(repr_type='ball+stick',
+ selection='9999',
+ color='pink',
aspectRatio = 10)
# lines box
-b.add_representation(repr_type='distance',
+b.add_representation(repr_type='distance',
atomPair= atomPair,
- labelColor= 'transparent',
- color= 'black')
+ labelColor= 'transparent',
+ color= 'black')
# output bindingsite
-s.add_representation(repr_type='surface',
- selection='*',
- color='skyblue',
+s.add_representation(repr_type='surface',
+ selection='*',
+ color='skyblue',
lowResolution= True,
# 0: low resolution
smooth=1,
- surfaceType= 'av',
+ surfaceType= 'av',
contour=True,
opacity=0.4,
- useWorker= True,
+ #useWorker= True,
wrap= True)
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Downloading Small Molecule¶
Downloading the desired small molecule to be used in the docking procedure.
-In this particular example, the small molecule of interest is the FDA-approved drug Imatinib, with PDB code STI.
+
+
Downloading Small Molecule¶
Downloading the desired small molecule to be used in the docking procedure.
+In this particular example, the small molecule of interest is the FDA-approved drug Imatinib, with PDB code STI.
Building Blocks used:
- ideal_sdf from biobb_io.api.ideal_sdf
- +
+
from biobb_io.api.ideal_sdf import ideal_sdf
+
+from biobb_io.api.ideal_sdf import ideal_sdf
-sdf_ideal = "ideal.sdf"
+sdf_ideal = "ideal.sdf"
prop = {
- "ligand_code": ligand_code
+ "ligand_code": ligand_code
}
ideal_sdf(output_sdf_path=sdf_ideal,
properties=prop)
-
-
-
Converting Small Molecule¶
Converting the desired small molecule to be used in the docking procedure, from SDF format to PDB format using the OpenBabel chemoinformatics tool.
+
+
Converting Small Molecule¶
Converting the desired small molecule to be used in the docking procedure, from SDF format to PDB format using the OpenBabel chemoinformatics tool.
Building Blocks used:
- babel_convert from biobb_chemistry.babelm.babel_convert
- +
+
from biobb_chemistry.babelm.babel_convert import babel_convert
+
+from biobb_chemistry.babelm.babel_convert import babel_convert
-ligand = "ligand.pdb"
+ligand = "ligand.pdb"
prop = {
- "input_format": "sdf",
- "output_format": "pdb",
- "binary_path": "obabel"
+ "input_format": "sdf",
+ "output_format": "pdb",
+ "binary_path": "obabel"
}
babel_convert(input_path = sdf_ideal,
output_path = ligand,
properties=prop)
-
-
-
Preparing Small Molecule (ligand) for Docking¶
Preparing the small molecule structure for the docking procedure. Converting the PDB file to a PDBQT file format (AutoDock PDBQT: Protein Data Bank, with Partial Charges (Q), & Atom Types (T)), needed by AutoDock Vina.
-The process adds partial charges and atom types to every atom. Besides, the ligand flexibility is also defined in the information contained in the file. The concept of "torsion tree" is used to represent the rigid and rotatable pieces of the ligand. A rigid piece ("root") is defined, with zero or more rotatable pieces ("branches"), hanging from the root, and defining the rotatable bonds.
+
+
Preparing Small Molecule (ligand) for Docking¶
Preparing the small molecule structure for the docking procedure. Converting the PDB file to a PDBQT file format (AutoDock PDBQT: Protein Data Bank, with Partial Charges (Q), & Atom Types (T)), needed by AutoDock Vina.
+The process adds partial charges and atom types to every atom. Besides, the ligand flexibility is also defined in the information contained in the file. The concept of "torsion tree" is used to represent the rigid and rotatable pieces of the ligand. A rigid piece ("root") is defined, with zero or more rotatable pieces ("branches"), hanging from the root, and defining the rotatable bonds.
More info about PDBQT file format can be found in the AutoDock FAQ pages.
+
Building Blocks used:
- babel_convert from biobb_chemistry.babelm.babel_convert
- +
+
from biobb_chemistry.babelm.babel_convert import babel_convert
+
+from biobb_chemistry.babelm.babel_convert import babel_convert
-prep_ligand = "prep_ligand.pdbqt"
+prep_ligand = "prep_ligand.pdbqt"
prop = {
- "input_format": "pdb",
- "output_format": "pdbqt",
- "binary_path": "obabel"
+ "input_format": "pdb",
+ "output_format": "pdbqt",
+ "binary_path": "obabel"
}
babel_convert(input_path = ligand,
output_path = prep_ligand,
properties=prop)
-
-
Visualizing small molecule (drug)¶
Visualizing the desired drug to be docked to the target protein, using NGL viewer.
Visualizing small molecule (drug)¶
Visualizing the desired drug to be docked to the target protein, using NGL viewer.
- Left panel: PDB-formatted file, with all hydrogen atoms.
- Right panel: PDBqt-formatted file (AutoDock Vina-compatible), with united atom model (only polar hydrogens are placed in the structures to correctly type heavy atoms as hydrogen bond donors).
from ipywidgets import HBox
+
+from ipywidgets import HBox
v0 = nglview.show_structure_file(ligand)
v1 = nglview.show_structure_file(prep_ligand)
-v0._set_size('500px', '')
-v1._set_size('500px', '')
+v0._set_size('500px', '')
+v1._set_size('500px', '')
def on_change(change):
- v1._set_camera_orientation(change['new'])
+ v1._set_camera_orientation(change['new'])
-v0.observe(on_change, ['_camera_orientation'])
+v0.observe(on_change, ['_camera_orientation'])
HBox([v0, v1])
-
-
-
Preparing Target Protein for Docking¶
Preparing the target protein structure for the docking procedure. Converting the PDB file to a PDBqt file, needed by AutoDock Vina. Similarly to the previous step, the process adds partial charges and atom types to every target protein atom. In this case, however, we are not taking into account receptor flexibility, although Autodock Vina allows some limited flexibility of selected receptor side chains (see the documentation).
+
+
Preparing Target Protein for Docking¶
Preparing the target protein structure for the docking procedure. Converting the PDB file to a PDBqt file, needed by AutoDock Vina. Similarly to the previous step, the process adds partial charges and atom types to every target protein atom. In this case, however, we are not taking into account receptor flexibility, although Autodock Vina allows some limited flexibility of selected receptor side chains (see the documentation).
Building Blocks used:
- str_check_add_hydrogens from biobb_structure_utils.utils.str_check_add_hydrogens
- +
+
from biobb_structure_utils.utils.str_check_add_hydrogens import str_check_add_hydrogens
+
+from biobb_structure_utils.utils.str_check_add_hydrogens import str_check_add_hydrogens
-prep_receptor = "prep_receptor.pdbqt"
+prep_receptor = "prep_receptor.pdbqt"
prop = {
- "charges": True,
- "mode": "auto"
+ "charges": True,
+ "mode": "auto"
}
str_check_add_hydrogens(input_structure_path = pdb_protein,
output_structure_path = prep_receptor,
properties=prop)
-
-
-
Running the Docking¶
Running the docking process with the prepared files:
++
Running the Docking¶
Running the docking process with the prepared files:
- ligand
- target protein -
- binding site box
- binding site box
using AutoDock Vina.
+
using AutoDock Vina.
Building Blocks used:
- autodock_vina_run from biobb_vs.vina.autodock_vina_run
- +
+
from biobb_vs.vina.autodock_vina_run import autodock_vina_run
+
+from biobb_vs.vina.autodock_vina_run import autodock_vina_run
-output_vina_pdbqt = "output_vina.pdbqt"
-output_vina_log = "output_vina.log"
+output_vina_pdbqt = "output_vina.pdbqt"
+output_vina_log = "output_vina.log"
prop = { }
autodock_vina_run(input_ligand_pdbqt_path = prep_ligand,
@@ -14989,251 +8428,286 @@ Running the Dockinginput_box_path = output_box,
output_pdbqt_path = output_vina_pdbqt,
output_log_path = output_vina_log,
- properties=prop)
+ properties = prop)
-
-
Visualizing docking output poses¶
Visualizing the generated docking poses for the ligand, using NGL viewer.
Visualizing docking output poses¶
Visualizing the generated docking poses for the ligand, using NGL viewer.
- Left panel: Docking poses displayed with atoms coloured by partial charges and licorice representation.
- Right panel: Docking poses displayed with atoms coloured by element and ball-and-stick representation.
models = 'all'
-#models = '/0 or /1 or /4'
+
+models = 'all'
+#models = '/0 or /1 or /4'
v0 = nglview.show_structure_file(output_vina_pdbqt, default=False)
-v0.add_representation(repr_type='licorice',
+v0.add_representation(repr_type='licorice',
selection=models,
- colorScheme= 'partialCharge')
+ colorScheme= 'partialCharge')
v0.center()
v1 = nglview.show_structure_file(output_vina_pdbqt, default=False)
-v1.add_representation(repr_type='ball+stick',
+v1.add_representation(repr_type='ball+stick',
selection=models)
v1.center()
-v0._set_size('500px', '')
-v1._set_size('500px', '')
+v0._set_size('500px', '')
+v1._set_size('500px', '')
def on_change(change):
- v1._set_camera_orientation(change['new'])
+ v1._set_camera_orientation(change['new'])
-v0.observe(on_change, ['_camera_orientation'])
+v0.observe(on_change, ['_camera_orientation'])
HBox([v0, v1])
-
-
from Bio.PDB import PDBParser
+
+from Bio.PDB import PDBParser
parser = PDBParser(QUIET = True)
-structure = parser.get_structure("protein", output_vina_pdbqt)
+structure = parser.get_structure("protein", output_vina_pdbqt)
models = []
for i, m in enumerate(structure):
- models.append(('model' + str(i), i))
+ models.append(('model' + str(i), i))
mdsel = ipywidgets.Dropdown(
options=models,
- description='Sel. model:',
+ description='Sel. model:',
disabled=False,
)
display(mdsel)
-
-
-
Extract a Docking Pose¶
Extract a specific docking pose from the docking outputs.
+
+
Extract a Docking Pose¶
Extract a specific docking pose from the docking outputs.
Building Blocks used:
- extract_model_pdbqt from biobb_vs.utils.extract_model_pdbqt
- +
+
from biobb_vs.utils.extract_model_pdbqt import extract_model_pdbqt
+
+from biobb_vs.utils.extract_model_pdbqt import extract_model_pdbqt
-output_pdbqt_model = "output_model.pdbqt"
+output_pdbqt_model = "output_model.pdbqt"
prop = {
- "model": 1
+ "model": 1
}
extract_model_pdbqt(input_pdbqt_path = output_vina_pdbqt,
output_pdbqt_path = output_pdbqt_model,
properties=prop)
-
-
-
Converting Ligand Pose to PDB format¶
Converting ligand pose to PDB format.
+
+
Converting Ligand Pose to PDB format¶
Converting ligand pose to PDB format.
Building Blocks used:
- babel_convert from biobb_chemistry.babelm.babel_convert
- +
+
from biobb_chemistry.babelm.babel_convert import babel_convert
+
+from biobb_chemistry.babelm.babel_convert import babel_convert
-output_pdb_model = "output_model.pdb"
+output_pdb_model = "output_model.pdb"
prop = {
- "input_format": "pdbqt",
- "output_format": "pdb",
- "binary_path": "obabel"
+ "input_format": "pdbqt",
+ "output_format": "pdb",
+ "binary_path": "obabel"
}
babel_convert(input_path = output_pdbqt_model,
output_path = output_pdb_model,
properties=prop)
-
-
-
Superposing Ligand Pose to the Target Protein Structure¶
Superposing ligand pose to the target protein structure, in order to see the protein-ligand docking conformation.
Building a new PDB file with both target and ligand (binding pose) structures.
+
+
Superposing Ligand Pose to the Target Protein Structure¶
Superposing ligand pose to the target protein structure, in order to see the protein-ligand docking conformation.
Building a new PDB file with both target and ligand (binding pose) structures.
Building Blocks used:
- cat_pdb from biobb_structure_utils.utils.cat_pdb
- +
+
from biobb_structure_utils.utils.cat_pdb import cat_pdb
+
+from biobb_structure_utils.utils.cat_pdb import cat_pdb
-output_structure = "output_structure.pdb"
+output_structure = "output_structure.pdb"
cat_pdb(input_structure1 = pdb_protein,
input_structure2 = output_pdb_model,
output_structure_path = output_structure)
-
-
Comparing final result with experimental structure¶
Visualizing and comparing the generated protein-ligand complex with the original protein-ligand conformation (downloaded from the PDB database), using NGL viewer.
Comparing final result with experimental structure¶
Visualizing and comparing the generated protein-ligand complex with the original protein-ligand conformation (downloaded from the PDB database), using NGL viewer.
- Licorice, element-colored representation: Experimental pose.
- Licorice, green-colored representation: Docking pose.
-
Note that outputs from AutoDock Vina don't contain all the atoms, as the program works with a united-atom representation (i.e. only polar hydrogens).
-view = nglview.NGLWidget()
+
+view = nglview.NGLWidget()
# v1 = Experimental Structure
-v1 = view.add_component(download_pdb)
+v1 = view.add_component(nglview.FileStructure(download_pdb))
v1.clear()
-v1.add_representation(repr_type='licorice',
- selection='STI',
+v1.add_representation(repr_type='licorice',
+ selection='STI',
radius=0.5)
# v2 = Docking result
-v2 = view.add_component(output_structure)
+v2 = view.add_component(nglview.FileStructure(output_structure))
v2.clear()
-v2.add_representation(repr_type='cartoon', colorScheme = 'sstruc')
-v2.add_representation(repr_type='licorice', radius=0.5, color= 'green', selection='UNL')
+v2.add_representation(repr_type='cartoon', colorScheme = 'sstruc')
+v2.add_representation(repr_type='licorice', radius=0.5, color= 'green', selection='UNL')
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
# align reference and output
-code = """
+code = """
var stage = this.stage;
var clist_len = stage.compList.length;
var i = 0;
@@ -15243,33 +8717,40 @@ Comparing final resu
s.push(stage.compList[i])
}
}
-NGL.superpose(s[0].structure, s[1].structure, true, ".CA")
+NGL.superpose(s[0].structure, s[1].structure, true, ".CA")
s[ 0 ].updateRepresentations({ position: true })
s[ 0 ].autoView()
-"""
+"""
view._execute_js_code(code)
view
-
-
+
Protein-ligand Docking tutorial using BioExcel Building Blocks (biobb)¶
-- PDBe REST-API Version --¶
+
This tutorial aims to illustrate the process of protein-ligand docking, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Mitogen-activated protein kinase 14 (p38-α) protein (PDB code 3LFA, https://doi.org/10.2210/pdb3LFA/pdb), a well-known Protein Kinase enzyme, +in complex with the FDA-approved Dasatinib, (PDB Ligand code 1N1, DrugBank Ligand Code DB01254), a small molecule kinase inhibitor used for the treatment of lymphoblastic or chronic myeloid leukemia with resistance or intolerance to prior therapy.
The tutorial will guide you through the process of identifying the active site cavity (pocket) and the final prediction of the protein-ligand complex.
Please note that docking algorithms, and in particular, AutoDock Vina program used in this tutorial, are non-deterministic. That means that results obtained when running the workflow could be diferent from the ones we obtained during the writing of this tutorial (see AutoDock Vina manual). We invite you to try the docking process several times to verify this behaviour.
--
Settings¶
Biobb modules used¶
-
+
- biobb_io: Tools to fetch biomolecular data from public databases.
- biobb_structure_utils: Tools to modify or extract information from a PDB structure file.
- biobb_chemistry: Tools to perform chemoinformatics processes.
- biobb_vs: Tools to perform virtual screening studies.
- jupyter: Free software, open standards, and web services for interactive computing across all programming languages. +
- jupyter: Free software, open standards, and web services for interactive computing across all programming languages.
- nglview: Jupyter/IPython widget to interactively view molecular structures and trajectories in notebooks.
- Input Parameters
- Fetching PDB Structure
- Extract Protein Structure @@ -14301,359 +7558,493 @@
- Questions & Comments
+
Settings¶
Biobb modules used¶
Auxiliary libraries used¶
-
-
Auxiliary libraries used¶
-
+
Conda Installation and Launch¶
-git clone https://github.com/bioexcel/biobb_wf_virtual-screening.git
+Conda Installation¶
git clone https://github.com/bioexcel/biobb_wf_virtual-screening.git
cd biobb_wf_virtual-screening
conda env create -f conda_env/environment.yml
conda activate biobb_VS_tutorial
jupyter-notebook biobb_wf_virtual-screening/notebooks/ebi_api/wf_vs_ebi_api.ipynb
-
-Pipeline steps¶
+
+Pipeline steps¶
Pipeline stepsComparing final result with experimental structure
-
-
-
-
+
+
+
+
Initializing colab¶
The two cells below are used only in case this notebook is executed via Google Colab. Take into account that, for running conda on Google Colab, the condacolab library must be installed. As explained here, the installation requires a kernel restart, so when running this notebook in Google Colab, don't run all cells until this installation is properly finished and the kernel has restarted.
+# Only executed when using google colab
+import sys
+if 'google.colab' in sys.modules:
+ import subprocess
+ from pathlib import Path
+ try:
+ subprocess.run(["conda", "-V"], check=True)
+ except FileNotFoundError:
+ subprocess.run([sys.executable, "-m", "pip", "install", "condacolab"], check=True)
+ import condacolab
+ condacolab.install()
+ # Clone repository
+ repo_URL = "https://github.com/bioexcel/biobb_wf_virtual-screening.git"
+ repo_name = Path(repo_URL).name.split('.')[0]
+ if not Path(repo_name).exists():
+ subprocess.run(["mamba", "install", "-y", "git"], check=True)
+ subprocess.run(["git", "clone", repo_URL], check=True)
+ print("⏬ Repository properly cloned.")
+ # Install environment
+ print("⏳ Creating environment...")
+ env_file_path = f"{repo_name}/conda_env/environment.yml"
+ subprocess.run(["mamba", "env", "update", "-n", "base", "-f", env_file_path], check=True)
+ print("🎨 Install NGLView dependencies...")
+ subprocess.run(["mamba", "install", "-y", "-c", "conda-forge", "nglview==3.0.8", "ipywidgets=7.7.2"], check=True)
+ print("👍 Conda environment successfully created and updated.")
+# Enable widgets for colab
+if 'google.colab' in sys.modules:
+ from google.colab import output
+ output.enable_custom_widget_manager()
+ # Change working dir
+ import os
+ os.chdir("biobb_wf_virtual-screening/biobb_wf_virtual-screening/notebooks/ebi_api")
+ print(f"📂 New working directory: {os.getcwd()}")
+Input parameters¶
Input parameters needed:
+Input parameters¶
Input parameters needed:
-
-
- pdb_code: PDB code of the experimental complex structure (if exists).
-In this particular example, the p38α structure in complex with the Dasatinib drug was experimentally solved and deposited in the PDB database under the 3LFA PDB code, https://doi.org/10.2210/pdb3LFA/pdb. The protein structure from this PDB file will be used as a target protein for the docking process, after stripping the small molecule. An APO structure, or any other structure from the p38α cluster 100 (sharing a 100% of sequence similarity with the p38α structure) could also be used as a target protein. This structure of the protein-ligand complex will be also used in the last step of the tutorial to check how close the resulting docking pose is from the known experimental structure.
+ - pdb_code: PDB code of the experimental complex structure (if exists).
+In this particular example, the p38α structure in complex with the Dasatinib drug was experimentally solved and deposited in the PDB database under the 3LFA PDB code, , https://doi.org/10.2210/pdb3LFA/pdb. The protein structure from this PDB file will be used as a target protein for the docking process, after stripping the small molecule. An APO structure, or any other structure from the p38α cluster 100 (sharing a 100% of sequence similarity with the p38α structure) could also be used as a target protein. This structure of the protein-ligand complex will be also used in the last step of the tutorial to check how close the resulting docking pose is from the known experimental structure.
+
-
-
- ligandCode: Ligand PDB code (3-letter code) for the small molecule (e.g. 1N1, DrugBank Ligand Code DB01254).
+ - ligandCode: Ligand PDB code (3-letter code) for the small molecule (e.g. 1N1, DrugBank Ligand Code DB01254).
In this particular example, the small molecule chosen for the tutorial is the FDA-approved drug Dasatinib (PDB Code 1N1, DrugBank Ligand Code DB01254), a tyrosine kinase inhibitor, used in lymphoblastic or chronic myeloid leukemia.
import nglview
+
+import nglview
import ipywidgets
-pdb_code = "3LFA" # P38 + Dasatinib
+pdb_code = "3LFA" # P38 + Dasatinib
-ligand_code = "1N1" # Dasatinib
+ligand_code = "1N1" # Dasatinib
-
-
-
Fetching PDB structure¶
Downloading PDB structure with the protein molecule from the PDBe database.
-Alternatively, a PDB file can be used as starting structure.
+
+
Fetching PDB structure¶
Downloading PDB structure with the protein molecule from the PDBe database.
+Alternatively, a PDB file can be used as starting structure.
Building Blocks used:
- Pdb from biobb_io.api.pdb
- +
+
from biobb_io.api.pdb import pdb
+
+from biobb_io.api.pdb import pdb
-download_pdb = "download.pdb"
+download_pdb = "download.pdb"
prop = {
- "pdb_code": pdb_code,
- "filter": ["ATOM", "HETATM"]
+ "pdb_code": pdb_code,
+ "filter": ["ATOM", "HETATM"]
}
pdb(output_pdb_path=download_pdb,
properties=prop)
-
-
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
+
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
Note (and try to identify) the Dasatinib small molecule (1N1) and the detergent (β-octyl glucoside) (BOG) used in the experimental reservoir solution to obtain the crystal.
view = nglview.show_structure_file(download_pdb, default=True)
+
+view = nglview.show_structure_file(download_pdb, default=True)
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
-
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Extract Protein Structure¶
Extract protein structure from the downloaded PDB file. Removing any extra molecule (ligands, ions, water molecules).
+
+
Extract Protein Structure¶
Extract protein structure from the downloaded PDB file. Removing any extra molecule (ligands, ions, water molecules).
The protein structure will be used as a target in the protein-ligand docking process.
+
Building Blocks used:
- extract_molecule from biobb_structure_utils.utils.extract_molecule
- +
+
from biobb_structure_utils.utils.extract_molecule import extract_molecule
+
+from biobb_structure_utils.utils.extract_molecule import extract_molecule
-pdb_protein = "pdb_protein.pdb"
+pdb_protein = "pdb_protein.pdb"
extract_molecule(input_structure_path=download_pdb,
- output_protein_path = pdb_protein)
+ output_molecule_path = pdb_protein)
-
-
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
+
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
Note that the small molecules included in the original structure are now gone. The new structure only contains the protein molecule, which will be used as a target for the protein-ligand docking.
view = nglview.show_structure_file(pdb_protein, default=False)
-view.add_representation(repr_type='cartoon',
- selection='not het',
- colorScheme = 'atomindex')
+
+view = nglview.show_structure_file(pdb_protein, default=False)
+view.add_representation(repr_type='cartoon',
+ selection='not het',
+ colorScheme = 'atomindex')
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
-
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Computing Protein Cavities (PDBe REST-API)¶
Identifying the protein cavities (pockets) using the PDBe REST-API.
These cavities will be then used in the docking procedure to try to find the best region of the protein surface where the small molecule can bind.
-Although in this particular example we already know the binding site region, as we started from a protein-ligand complex structure where the ligand was located in the same binding site as Dasatinib is binding, the PDBe REST-API can be used to automatically identify and extract the possible binding sites of our target protein from the PDB file annotations. This REST-API endpoint provides details on binding sites from the PDB files (or mmcif) information, such as ligands, residues in the site or description of the site.
+
+
Computing Protein Cavities (PDBe REST-API)¶
Identifying the protein cavities (pockets) using the PDBe REST-API.
These cavities will be then used in the docking procedure to try to find the best region of the protein surface where the small molecule can bind.
+Although in this particular example we already know the binding site region, as we started from a protein-ligand complex structure where the ligand was located in the same binding site as Dasatinib is binding, the PDBe REST-API can be used to automatically identify and extract the possible binding sites of our target protein from the PDB file annotations. This REST-API endpoint provides details on binding sites from the PDB files (or mmcif) information, such as ligands, residues in the site or description of the site.
Building Blocks used:
- api_binding_site from biobb_io.api.api_binding_site
- +
+
from biobb_io.api.api_binding_site import api_binding_site
+
+from biobb_io.api.api_binding_site import api_binding_site
-residues_json = "residues.json"
+residues_json = "residues.json"
prop = {
- "pdb_code": pdb_code
+ "pdb_code": pdb_code
}
api_binding_site(output_json_path=residues_json,
properties=prop)
-
-
Checking binding site output (json)¶
Checking the PDBe REST-API output from the json file. Every pocket has a separated entry in the json output, with information such as: residues forming the cavity, details of the cavity, and evidence used to detect the cavity.
- +Checking binding site output (json)¶
Checking the PDBe REST-API output from the json file. Every pocket has a separated entry in the json output, with information such as: residues forming the cavity, details of the cavity, and evidence used to detect the cavity.
+import json
+
+import json
with open(residues_json) as json_file:
data = json.load(json_file)
print(json.dumps(data, indent=4))
-
-
Select binding site (cavity)¶
Select a specific binding site (cavity) from the obtained list to be used in the docking procedure.
If the PDBe REST-API has successfully identified the correct binding site, which we know from the original protein-ligand structure, it just needs to be selected. In this particular example, the cavity we are interested in is the binding site number 1.
Select binding site (cavity)¶
Select a specific binding site (cavity) from the obtained list to be used in the docking procedure.
If the PDBe REST-API has successfully identified the correct binding site, which we know from the original protein-ligand structure, it just needs to be selected. In this particular example, the cavity we are interested in is the binding site number 1.
Choose a binding site from the DropDown list:
-bindingSites = {}
+
+bindingSites = {}
bsites = []
for i, item in enumerate(data[pdb_code.lower()]):
bindingSites[i] = []
- bsites.append(('binding_site' + str(i), i))
- for res in item['site_residues']:
- bindingSites[i].append(res['author_residue_number'])
-# print('Residue id\'s for binding site %d: %s' % (i, ', '.join(str(v) for v in bindingSites[i])))
+ bsites.append(('binding_site' + str(i), i))
+ for res in item['site_residues']:
+ bindingSites[i].append(res['author_residue_number'])
+# print('Residue id\'s for binding site %d: %s' % (i, ', '.join(str(v) for v in bindingSites[i])))
mdsel = ipywidgets.Dropdown(
options=bsites,
- description='Binding Site:',
+ description='Binding Site:',
disabled=False,
)
display(mdsel)
-
-
view = nglview.show_structure_file(download_pdb, default=False)
+
+view = nglview.show_structure_file(download_pdb, default=False)
-view.add_representation(repr_type='cartoon',
- selection='not het',
+view.add_representation(repr_type='cartoon',
+ selection='not het',
opacity=.2,
- color='#cccccc')
+ color='#cccccc')
-view.add_representation(repr_type='surface',
- selection=', '.join(str(v) for v in bindingSites[mdsel.value]),
- color='pink',
+view.add_representation(repr_type='surface',
+ selection=', '.join(str(v) for v in bindingSites[mdsel.value]),
+ color='pink',
lowResolution= True,
# 0: low resolution
smooth=1 )
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
-
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Generating Cavity Box¶
Generating a box surrounding the selected protein cavity (pocket), to be used in the docking procedure. The box is defining the region on the surface of the protein target where the docking program should explore a possible ligand dock.
-An offset of 12 Angstroms is used to generate a big enough box to fit the small molecule and its possible rotations.
+
+
Generating Cavity Box¶
Generating a box surrounding the selected protein cavity (pocket), to be used in the docking procedure. The box is defining the region on the surface of the protein target where the docking program should explore a possible ligand dock.
+An offset of 12 Angstroms is used to generate a big enough box to fit the small molecule and its possible rotations.
Building Blocks used:
- box_residues from biobb_vs.utils.box_residues
- +
+
from biobb_vs.utils.box_residues import box_residues
+
+from biobb_vs.utils.box_residues import box_residues
-output_box = "box.pdb"
+output_box = "box.pdb"
prop = {
- "resid_list": bindingSites[mdsel.value],
- "offset": 12,
- "box_coordinates": True
+ "resid_list": bindingSites[mdsel.value],
+ "offset": 12,
+ "box_coordinates": True
}
box_residues(#input_pdb_path = pdb_single_chain,
@@ -14661,324 +8052,368 @@ Generating Cavity Boxoutput_pdb_path = output_box,
properties=prop)
-
-
Visualizing binding site box in 3D structure¶
Visualizing the protein structure, the selected cavity, and the generated box, all together using NGL viewer. Using the original structure with the small ligand inside (Dasatinib, 1N1, DrugBank Ligand Code DB01254), to check that the selected cavity is placed in the same region as the original ligand.
- +Visualizing binding site box in 3D structure¶
Visualizing the protein structure, the selected cavity, and the generated box, all together using NGL viewer. Using the original structure with the small ligand inside (Dasatinib, 1N1, DrugBank Ligand Code DB01254), to check that the selected cavity is placed in the same region as the original ligand.
+view = nglview.NGLWidget()
+
+view = nglview.NGLWidget()
-s = view.add_component(download_pdb)
-b = view.add_component(output_box)
+s = view.add_component(nglview.FileStructure(download_pdb))
+b = view.add_component(nglview.FileStructure(output_box))
atomPair = [
- [ "9999:Z.ZN1", "9999:Z.ZN2" ],
- [ "9999:Z.ZN2", "9999:Z.ZN4" ],
- [ "9999:Z.ZN4", "9999:Z.ZN3" ],
- [ "9999:Z.ZN3", "9999:Z.ZN1" ],
+ [ "9999:Z.ZN1", "9999:Z.ZN2" ],
+ [ "9999:Z.ZN2", "9999:Z.ZN4" ],
+ [ "9999:Z.ZN4", "9999:Z.ZN3" ],
+ [ "9999:Z.ZN3", "9999:Z.ZN1" ],
- [ "9999:Z.ZN5", "9999:Z.ZN6" ],
- [ "9999:Z.ZN6", "9999:Z.ZN8" ],
- [ "9999:Z.ZN8", "9999:Z.ZN7" ],
- [ "9999:Z.ZN7", "9999:Z.ZN5" ],
+ [ "9999:Z.ZN5", "9999:Z.ZN6" ],
+ [ "9999:Z.ZN6", "9999:Z.ZN8" ],
+ [ "9999:Z.ZN8", "9999:Z.ZN7" ],
+ [ "9999:Z.ZN7", "9999:Z.ZN5" ],
- [ "9999:Z.ZN1", "9999:Z.ZN5" ],
- [ "9999:Z.ZN2", "9999:Z.ZN6" ],
- [ "9999:Z.ZN3", "9999:Z.ZN7" ],
- [ "9999:Z.ZN4", "9999:Z.ZN8" ]
+ [ "9999:Z.ZN1", "9999:Z.ZN5" ],
+ [ "9999:Z.ZN2", "9999:Z.ZN6" ],
+ [ "9999:Z.ZN3", "9999:Z.ZN7" ],
+ [ "9999:Z.ZN4", "9999:Z.ZN8" ]
]
# structure
-s.add_representation(repr_type='cartoon',
- selection='not het',
- color='#cccccc',
+s.add_representation(repr_type='cartoon',
+ selection='not het',
+ color='#cccccc',
opacity=.2)
# ligands box
-b.add_representation(repr_type='ball+stick',
- selection='9999',
- color='pink',
+b.add_representation(repr_type='ball+stick',
+ selection='9999',
+ color='pink',
aspectRatio = 8)
# lines box
-b.add_representation(repr_type='distance',
+b.add_representation(repr_type='distance',
atomPair= atomPair,
labelVisible=False,
- color= 'black')
+ color= 'black')
# residues
-s.add_representation(repr_type='surface',
- selection=', '.join(str(v) for v in bindingSites[mdsel.value]),
- color='skyblue',
+s.add_representation(repr_type='surface',
+ selection=', '.join(str(v) for v in bindingSites[mdsel.value]),
+ color='skyblue',
lowResolution= True,
# 0: low resolution
smooth=1,
- surfaceType= 'av',
+ surfaceType= 'av',
contour=True,
opacity=0.4,
- useWorker= True,
+ #useWorker= True,
wrap= True)
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
-
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Downloading Small Molecule¶
Downloading the desired small molecule to be used in the docking procedure.
-In this particular example, the small molecule of interest is the FDA-approved drug Dasatinib, with PDB code 1N1.
+
+
Downloading Small Molecule¶
Downloading the desired small molecule to be used in the docking procedure.
+In this particular example, the small molecule of interest is the FDA-approved drug Dasatinib, with PDB code 1N1.
Building Blocks used:
- ideal_sdf from biobb_io.api.ideal_sdf
- +
+
from biobb_io.api.ideal_sdf import ideal_sdf
+
+from biobb_io.api.ideal_sdf import ideal_sdf
-sdf_ideal = "ideal.sdf"
+sdf_ideal = "ideal.sdf"
prop = {
- "ligand_code": ligand_code
+ "ligand_code": ligand_code
}
ideal_sdf(output_sdf_path=sdf_ideal,
properties=prop)
-
-
-
Converting Small Molecule¶
Converting the desired small molecule to be used in the docking procedure, from SDF format to PDB format using the OpenBabel chemoinformatics tool.
+
+
Converting Small Molecule¶
Converting the desired small molecule to be used in the docking procedure, from SDF format to PDB format using the OpenBabel chemoinformatics tool.
Building Blocks used:
- babel_convert from biobb_chemistry.babelm.babel_convert
- +
+
from biobb_chemistry.babelm.babel_convert import babel_convert
+
+from biobb_chemistry.babelm.babel_convert import babel_convert
-ligand = "ligand.pdb"
+ligand = "ligand.pdb"
prop = {
- "input_format": "sdf",
- "output_format": "pdb",
- "binary_path": "obabel"
+ "input_format": "sdf",
+ "output_format": "pdb",
+ "binary_path": "obabel"
}
babel_convert(input_path = sdf_ideal,
output_path = ligand,
properties=prop)
-
-
-
Preparing Small Molecule (ligand) for Docking¶
Preparing the small molecule structure for the docking procedure. Converting the PDB file to a PDBQT file format (AutoDock PDBQT: Protein Data Bank, with Partial Charges (Q), & Atom Types (T)), needed by AutoDock Vina.
-The process adds partial charges and atom types to every atom. Besides, the ligand flexibility is also defined in the information contained in the file. The concept of "torsion tree" is used to represent the rigid and rotatable pieces of the ligand. A rigid piece ("root") is defined, with zero or more rotatable pieces ("branches"), hanging from the root, and defining the rotatable bonds.
+
+
Preparing Small Molecule (ligand) for Docking¶
Preparing the small molecule structure for the docking procedure. Converting the PDB file to a PDBQT file format (AutoDock PDBQT: Protein Data Bank, with Partial Charges (Q), & Atom Types (T)), needed by AutoDock Vina.
+The process adds partial charges and atom types to every atom. Besides, the ligand flexibility is also defined in the information contained in the file. The concept of "torsion tree" is used to represent the rigid and rotatable pieces of the ligand. A rigid piece ("root") is defined, with zero or more rotatable pieces ("branches"), hanging from the root, and defining the rotatable bonds.
More info about PDBQT file format can be found in the AutoDock FAQ pages.
+
Building Blocks used:
- babel_convert from biobb_chemistry.babelm.babel_convert
- +
+
from biobb_chemistry.babelm.babel_convert import babel_convert
+
+from biobb_chemistry.babelm.babel_convert import babel_convert
-prep_ligand = "prep_ligand.pdbqt"
+prep_ligand = "prep_ligand.pdbqt"
prop = {
- "input_format": "pdb",
- "output_format": "pdbqt",
- "binary_path": "obabel"
+ "input_format": "pdb",
+ "output_format": "pdbqt",
+ "binary_path": "obabel"
}
babel_convert(input_path = ligand,
output_path = prep_ligand,
properties=prop)
-
-
Visualizing small molecule (drug)¶
Visualizing the desired drug to be docked to the target protein, using NGL viewer.
Visualizing small molecule (drug)¶
Visualizing the desired drug to be docked to the target protein, using NGL viewer.
- Left panel: PDB-formatted file, with all hydrogen atoms.
- Right panel: PDBqt-formatted file (AutoDock Vina-compatible), with united atom model (only polar hydrogens are placed in the structures to correctly type heavy atoms as hydrogen bond donors).
from ipywidgets import HBox
+
+from ipywidgets import HBox
v0 = nglview.show_structure_file(ligand)
v1 = nglview.show_structure_file(prep_ligand)
-v0._set_size('500px', '')
-v1._set_size('500px', '')
+v0._set_size('500px', '')
+v1._set_size('500px', '')
def on_change(change):
- v1._set_camera_orientation(change['new'])
+ v1._set_camera_orientation(change['new'])
-v0.observe(on_change, ['_camera_orientation'])
+v0.observe(on_change, ['_camera_orientation'])
HBox([v0, v1])
-
-
-
Preparing Target Protein for Docking¶
Preparing the target protein structure for the docking procedure. Converting the PDB file to a PDBqt file, needed by AutoDock Vina. Similarly to the previous step, the process adds partial charges and atom types to every target protein atom. In this case, however, we are not taking into account receptor flexibility, although Autodock Vina allows some limited flexibility of selected receptor side chains (see the documentation).
+
+
Preparing Target Protein for Docking¶
Preparing the target protein structure for the docking procedure. Converting the PDB file to a PDBqt file, needed by AutoDock Vina. Similarly to the previous step, the process adds partial charges and atom types to every target protein atom. In this case, however, we are not taking into account receptor flexibility, although Autodock Vina allows some limited flexibility of selected receptor side chains (see the documentation).
Building Blocks used:
- str_check_add_hydrogens from biobb_structure_utils.utils.str_check_add_hydrogens
- +
+
from biobb_structure_utils.utils.str_check_add_hydrogens import str_check_add_hydrogens
+
+from biobb_structure_utils.utils.str_check_add_hydrogens import str_check_add_hydrogens
-prep_receptor = "prep_receptor.pdbqt"
+prep_receptor = "prep_receptor.pdbqt"
prop = {
- "charges": True,
- "mode": "auto"
+ "charges": True,
+ "mode": "auto"
}
str_check_add_hydrogens(
input_structure_path = pdb_protein,
output_structure_path = prep_receptor,
- properties=prop)
+ properties = prop)
-
-
-
Running the Docking¶
Running the docking process with the prepared files:
++
Running the Docking¶
Running the docking process with the prepared files:
- ligand
- target protein -
- binding site box
- binding site box
using AutoDock Vina.
+
using AutoDock Vina.
Building Blocks used:
- autodock_vina_run from biobb_vs.vina.autodock_vina_run
- +
+
from biobb_vs.vina.autodock_vina_run import autodock_vina_run
+
+from biobb_vs.vina.autodock_vina_run import autodock_vina_run
-output_vina_pdbqt = "output_vina.pdbqt"
-output_vina_log = "output_vina.log"
+output_vina_pdbqt = "output_vina.pdbqt"
+output_vina_log = "output_vina.log"
prop = { }
autodock_vina_run(input_ligand_pdbqt_path = prep_ligand,
@@ -14986,251 +8421,286 @@ Running the Dockinginput_box_path = output_box,
output_pdbqt_path = output_vina_pdbqt,
output_log_path = output_vina_log,
- properties=prop)
+ properties = prop)
-
-
Visualizing docking output poses¶
Visualizing the generated docking poses for the ligand, using NGL viewer.
Visualizing docking output poses¶
Visualizing the generated docking poses for the ligand, using NGL viewer.
- Left panel: Docking poses displayed with atoms coloured by partial charges and licorice representation.
- Right panel: Docking poses displayed with atoms coloured by element and ball-and-stick representation.
models = 'all'
+
+models = 'all'
v0 = nglview.show_structure_file(output_vina_pdbqt, default=False)
-v0.add_representation(repr_type='licorice',
+v0.add_representation(repr_type='licorice',
selection=models,
- colorScheme= 'partialCharge')
+ colorScheme= 'partialCharge')
v0.center()
v1 = nglview.show_structure_file(output_vina_pdbqt, default=False)
-v1.add_representation(repr_type='ball+stick',
+v1.add_representation(repr_type='ball+stick',
selection=models)
v1.center()
-v0._set_size('500px', '')
-v1._set_size('500px', '')
+v0._set_size('500px', '')
+v1._set_size('500px', '')
def on_change(change):
- v1._set_camera_orientation(change['new'])
+ v1._set_camera_orientation(change['new'])
-v0.observe(on_change, ['_camera_orientation'])
+v0.observe(on_change, ['_camera_orientation'])
HBox([v0, v1])
-
-
from Bio.PDB import PDBParser
+
+from Bio.PDB import PDBParser
parser = PDBParser(QUIET = True)
-structure = parser.get_structure("protein", output_vina_pdbqt)
+structure = parser.get_structure("protein", output_vina_pdbqt)
models = []
for i, m in enumerate(structure):
- models.append(('model' + str(i), i))
+ models.append(('model' + str(i), i))
mdsel = ipywidgets.Dropdown(
options=models,
- description='Sel. model:',
+ description='Sel. model:',
disabled=False,
)
display(mdsel)
-
-
-
Extract a Docking Pose¶
Extract a specific docking pose from the docking outputs.
+
+
Extract a Docking Pose¶
Extract a specific docking pose from the docking outputs.
Building Blocks used:
- extract_model_pdbqt from biobb_vs.utils.extract_model_pdbqt
- +
+
from biobb_vs.utils.extract_model_pdbqt import extract_model_pdbqt
+
+from biobb_vs.utils.extract_model_pdbqt import extract_model_pdbqt
-output_pdbqt_model = "output_model.pdbqt"
+output_pdbqt_model = "output_model.pdbqt"
prop = {
- "model": mdsel.value + 1
+ "model": mdsel.value + 1
}
extract_model_pdbqt(input_pdbqt_path = output_vina_pdbqt,
output_pdbqt_path = output_pdbqt_model,
properties=prop)
-
-
-
Converting Ligand Pose to PDB format¶
Converting ligand pose to PDB format.
+
+
Converting Ligand Pose to PDB format¶
Converting ligand pose to PDB format.
Building Blocks used:
- babel_convert from biobb_chemistry.babelm.babel_convert
- +
+
from biobb_chemistry.babelm.babel_convert import babel_convert
+
+from biobb_chemistry.babelm.babel_convert import babel_convert
-output_pdb_model = "output_model.pdb"
+output_pdb_model = "output_model.pdb"
prop = {
- "input_format": "pdbqt",
- "output_format": "pdb",
- "binary_path": "obabel"
+ "input_format": "pdbqt",
+ "output_format": "pdb",
+ "binary_path": "obabel"
}
babel_convert(input_path = output_pdbqt_model,
output_path = output_pdb_model,
properties=prop)
-
-
-
Superposing Ligand Pose to the Target Protein Structure¶
Superposing ligand pose to the target protein structure, in order to see the protein-ligand docking conformation.
Building a new PDB file with both target and ligand (binding pose) structures.
+
+
Superposing Ligand Pose to the Target Protein Structure¶
Superposing ligand pose to the target protein structure, in order to see the protein-ligand docking conformation.
Building a new PDB file with both target and ligand (binding pose) structures.
Building Blocks used:
- cat_pdb from biobb_structure_utils.utils.cat_pdb
- +
+
from biobb_structure_utils.utils.cat_pdb import cat_pdb
+
+from biobb_structure_utils.utils.cat_pdb import cat_pdb
-output_structure = "output_structure.pdb"
+output_structure = "output_structure.pdb"
cat_pdb(#input_structure1 = pdb_single_chain,
input_structure1 = download_pdb,
input_structure2 = output_pdb_model,
output_structure_path = output_structure)
-
-
Comparing final result with experimental structure¶
Visualizing and comparing the generated protein-ligand complex with the original protein-ligand conformation (downloaded from the PDB database), using NGL viewer.
Comparing final result with experimental structure¶
Visualizing and comparing the generated protein-ligand complex with the original protein-ligand conformation (downloaded from the PDB database), using NGL viewer.
- Licorice, element-colored representation: Experimental pose.
- Licorice, green-colored representation: Docking pose.
-
Note that outputs from AutoDock Vina don't contain all the atoms, as the program works with a united-atom representation (i.e. only polar hydrogens).
-view = nglview.NGLWidget()
+
+view = nglview.NGLWidget()
# v1 = Experimental Structure
-v1 = view.add_component(download_pdb)
+v1 = view.add_component(nglview.FileStructure(download_pdb))
v1.clear()
-v1.add_representation(repr_type='licorice',
- selection='[1N1]',
+v1.add_representation(repr_type='licorice',
+ selection='[1N1]',
radius=0.5)
# v2 = Docking result
-v2 = view.add_component(output_structure)
+v2 = view.add_component(nglview.FileStructure(output_structure))
v2.clear()
-v2.add_representation(repr_type='cartoon', colorScheme = 'sstruc')
-v2.add_representation(repr_type='licorice', radius=0.5, color= 'green', selection='UNL')
+v2.add_representation(repr_type='cartoon', colorScheme = 'sstruc')
+v2.add_representation(repr_type='licorice', radius=0.5, color= 'green', selection='UNL')
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
# align reference and output
-code = """
+code = """
var stage = this.stage;
var clist_len = stage.compList.length;
var i = 0;
@@ -15240,33 +8710,39 @@ Comparing final resu
s.push(stage.compList[i])
}
}
-NGL.superpose(s[0].structure, s[1].structure, true, ".CA")
+NGL.superpose(s[0].structure, s[1].structure, true, ".CA")
s[ 0 ].updateRepresentations({ position: true })
s[ 0 ].autoView()
-"""
+"""
view._execute_js_code(code)
-
view
-
-
+
Protein-ligand Docking tutorial using BioExcel Building Blocks (biobb)¶
-- Fpocket Version --¶
+
This tutorial aims to illustrate the process of protein-ligand docking, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Mitogen-activated protein kinase 14 (p38-α) protein (PDB code 3HEC, https://doi.org/10.2210/pdb3HEC/pdb), a well-known Protein Kinase enzyme, +in complex with the FDA-approved Imatinib, (PDB Ligand code STI, DrugBank Ligand Code DB00619), a small molecule kinase inhibitor used to treat certain types of cancer.
The tutorial will guide you through the process of identifying the active site cavity (pocket) without previous knowledge, and the final prediction of the protein-ligand complex.
Please note that docking algorithms, and in particular, AutoDock Vina program used in this tutorial, are non-deterministic. That means that results obtained when running the workflow could be diferent from the ones we obtained during the writing of this tutorial (see AutoDock Vina manual). We invite you to try the docking process several times to verify this behaviour.
--
Settings¶
Biobb modules used¶
-
+
- biobb_io: Tools to fetch biomolecular data from public databases.
- biobb_structure_utils: Tools to modify or extract information from a PDB structure file.
- biobb_chemistry: Tools to perform chemoinformatics processes.
- biobb_vs: Tools to perform virtual screening studies.
- jupyter: Free software, open standards, and web services for interactive computing across all programming languages.
- nglview: Jupyter/IPython widget to interactively view molecular structures and trajectories in notebooks.
- Input Parameters
- Fetching PDB Structure
- Extract Protein Structure @@ -14302,224 +7559,336 @@
- Questions & Comments
+
Settings¶
Biobb modules used¶
Auxiliary libraries used¶
-
+
Auxiliary libraries used¶
Conda Installation and Launch¶
-git clone https://github.com/bioexcel/biobb_wf_virtual-screening.git
+Conda Installation¶
git clone https://github.com/bioexcel/biobb_wf_virtual-screening.git
cd biobb_wf_virtual-screening
conda env create -f conda_env/environment.yml
conda activate biobb_VS_tutorial
jupyter-notebook biobb_wf_virtual-screening/notebooks/fpocket/wf_vs_fpocket.ipynb
-
-Pipeline steps¶
+
+Pipeline steps¶
Pipeline stepsComparing final result with experimental structure
-
-
-
-
+
+
+
+
Initializing colab¶
The two cells below are used only in case this notebook is executed via Google Colab. Take into account that, for running conda on Google Colab, the condacolab library must be installed. As explained here, the installation requires a kernel restart, so when running this notebook in Google Colab, don't run all cells until this installation is properly finished and the kernel has restarted.
+# Only executed when using google colab
+import sys
+if 'google.colab' in sys.modules:
+ import subprocess
+ from pathlib import Path
+ try:
+ subprocess.run(["conda", "-V"], check=True)
+ except FileNotFoundError:
+ subprocess.run([sys.executable, "-m", "pip", "install", "condacolab"], check=True)
+ import condacolab
+ condacolab.install()
+ # Clone repository
+ repo_URL = "https://github.com/bioexcel/biobb_wf_virtual-screening.git"
+ repo_name = Path(repo_URL).name.split('.')[0]
+ if not Path(repo_name).exists():
+ subprocess.run(["mamba", "install", "-y", "git"], check=True)
+ subprocess.run(["git", "clone", repo_URL], check=True)
+ print("⏬ Repository properly cloned.")
+ # Install environment
+ print("⏳ Creating environment...")
+ env_file_path = f"{repo_name}/conda_env/environment.yml"
+ subprocess.run(["mamba", "env", "update", "-n", "base", "-f", env_file_path], check=True)
+ print("🎨 Install NGLView dependencies...")
+ subprocess.run(["mamba", "install", "-y", "-c", "conda-forge", "nglview==3.0.8", "ipywidgets=7.7.2"], check=True)
+ print("👍 Conda environment successfully created and updated.")
+# Enable widgets for colab
+if 'google.colab' in sys.modules:
+ from google.colab import output
+ output.enable_custom_widget_manager()
+ # Change working dir
+ import os
+ os.chdir("biobb_wf_virtual-screening/biobb_wf_virtual-screening/notebooks/fpocket")
+ print(f"📂 New working directory: {os.getcwd()}")
+Input parameters¶
Input parameters needed:
+Input parameters¶
Input parameters needed:
-
-
- pdb_code: PDB code of the experimental complex structure (if exists).
-In this particular example, the p38α structure in complex with the Imatinib drug was experimentally solved and deposited in the PDB database under the 3HEC PDB code, https://doi.org/10.2210/pdb3HEC/pdb. The protein structure from this PDB file will be used as a target protein for the docking process, after stripping the small molecule. An APO structure, or any other structure from the p38α cluster 100 (sharing a 100% of sequence similarity with the p38α structure) could also be used as a target protein. This structure of the protein-ligand complex will be also used in the last step of the tutorial to check how close the resulting docking pose is from the known experimental structure.
+ - pdb_code: PDB code of the experimental complex structure (if exists).
+In this particular example, the p38α structure in complex with the Imatinib drug was experimentally solved and deposited in the PDB database under the 3HEC PDB code, https://doi.org/10.2210/pdb3HEC/pdb. The protein structure from this PDB file will be used as a target protein for the docking process, after stripping the small molecule. An APO structure, or any other structure from the p38α cluster 100 (sharing a 100% of sequence similarity with the p38α structure) could also be used as a target protein. This structure of the protein-ligand complex will be also used in the last step of the tutorial to check how close the resulting docking pose is from the known experimental structure.
+
-
-
- ligandCode: Ligand PDB code (3-letter code) for the small molecule (e.g. STI, DrugBank Ligand Code DB00619).
+ - ligandCode: Ligand PDB code (3-letter code) for the small molecule (e.g. STI, DrugBank Ligand Code DB00619).
In this particular example, the small molecule chosen for the tutorial is the FDA-approved drug Imatinib (PDB Code STI, DrugBank Ligand Code DB00619), a type of cancer growth blocker, used in diferent types of leukemia.
+
- pockets_dir: Name of a folder to write temporary files.
import nglview
+
+import nglview
import ipywidgets
-pdb_code = "3HEC" # P38 + Imatinib
+pdb_code = "3HEC" # P38 + Imatinib
-ligand_code = "STI" # Imatinib
+ligand_code = "STI" # Imatinib
-pockets_dir = "pockets"
+pockets_dir = "pockets"
-
-
-
Fetching PDB structure¶
Downloading PDB structure with the protein molecule from the PDBe database.
-Alternatively, a PDB file can be used as starting structure.
+
+
Fetching PDB structure¶
Downloading PDB structure with the protein molecule from the PDBe database.
+Alternatively, a PDB file can be used as starting structure.
Building Blocks used:
- Pdb from biobb_io.api.pdb
- +
+
from biobb_io.api.pdb import pdb
+
+from biobb_io.api.pdb import pdb
-download_pdb = "download.pdb"
+download_pdb = "download.pdb"
prop = {
- "pdb_code": pdb_code,
- "filter": ["ATOM", "HETATM"]
+ "pdb_code": pdb_code,
+ "filter": ["ATOM", "HETATM"]
}
pdb(output_pdb_path=download_pdb,
properties=prop)
-
-
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
+
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
Note (and try to identify) the Imatinib small molecule (STI) and the detergent (β-octyl glucoside) (BOG) used in the experimental reservoir solution to obtain the crystal.
view = nglview.show_structure_file(download_pdb, default=True)
+
+view = nglview.show_structure_file(download_pdb, default=True)
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Extract Protein Structure¶
Extract protein structure from the downloaded PDB file. Removing any extra molecule (ligands, ions, water molecules).
+
+
Extract Protein Structure¶
Extract protein structure from the downloaded PDB file. Removing any extra molecule (ligands, ions, water molecules).
The protein structure will be used as a target in the protein-ligand docking process.
+
Building Blocks used:
- extract_molecule from biobb_structure_utils.utils.extract_molecule
- +
+
from biobb_structure_utils.utils.extract_molecule import extract_molecule
+
+from biobb_structure_utils.utils.extract_molecule import extract_molecule
-pdb_protein = "pdb_protein.pdb"
+pdb_protein = "pdb_protein.pdb"
extract_molecule(input_structure_path=download_pdb,
- output_protein_path = pdb_protein)
+ output_molecule_path = pdb_protein)
-
-
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
+
Visualizing 3D structure¶
Visualizing the downloaded/given PDB structure using NGL.
Note that the small molecules included in the original structure are now gone. The new structure only contains the protein molecule, which will be used as a target for the protein-ligand docking.
view = nglview.show_structure_file(pdb_protein, default=False)
-view.add_representation(repr_type='cartoon',
- selection='not het',
- colorScheme = 'atomindex')
+
+view = nglview.show_structure_file(pdb_protein, default=False)
+view.add_representation(repr_type='cartoon',
+ selection='not het',
+ colorScheme = 'atomindex')
view.center()
-view._remote_call('setSize', target='Widget', args=['','600px'])
+view._remote_call('setSize', target='Widget', args=['','600px'])
view
-
-
-
Computing Protein Cavities (fpocket)¶
Computing the protein cavities (pockets) using the well-known fpocket tool.
-These cavities will be then used in the docking procedure to try to find the best region of the protein surface where the small molecule can bind.
-Although in this particular example we already know the binding site region, as we started from a protein-ligand complex structure where the ligand was located in the same binding site as Imatinib is binding, this is not always the case. In the cases where we do not know these regions, fpocket will help us identifying the possible binding sites of our target protein.
fpocket input parameters, such as minimum and maximum radius (in Angstroms) the alpha spheres might have in a binding pocket can be adjusted (min_radius, max_radius) . Parameters used in this particular example are 3Å for the minimum radius and 6Å for the maximum radius. The minimum number of alpha spheres a pocket must contain in order to figure in the results is also adjusted to 35. See the fpocket manual for more information.
-
+
+
Computing Protein Cavities (fpocket)¶
Computing the protein cavities (pockets) using the well-known fpocket tool.
+These cavities will be then used in the docking procedure to try to find the best region of the protein surface where the small molecule can bind.
+Although in this particular example we already know the binding site region, as we started from a protein-ligand complex structure where the ligand was located in the same binding site as Imatinib is binding, this is not always the case. In the cases where we do not know these regions, fpocket will help us identifying the possible binding sites of our target protein.
fpocket input parameters, such as minimum and maximum radius (in Angstroms) the alpha spheres might have in a binding pocket can be adjusted (min_radius, max_radius) . Parameters used in this particular example are 3Å for the minimum radius and 6Å for the maximum radius. The minimum number of alpha spheres a pocket must contain in order to figure in the results is also adjusted to 35. See the fpocket manual for more information.
+
Building Blocks used:
- fpocket_run from biobb_vs.fpocket.fpocket_run
- +
+