Module 2: Structure Based Ph4 Design
MOE provides several applications to analyze protein information in absence
of ligands:
• The Site Finder (using the binding site of a receptor to generate the
query)
• Contact preferences
In part b) of the SBDD course:
• The MCSS algorithm for de-novo design
• Docking
Alpha Site Finder
Objective
The Site Finder screens the surface of a protein for potential binding sites. In
addition to locating cavities it also indicates preferred locations for
hydrophilic or non-hydrophilic interaction points.
Methodology
Site Finder considers the relative positions and
accessibility of the receptor atoms along with a
rough classification of chemical type. The
method applies alpha spheres. This is a special
case of a contact sphere that circumscribes 4 atoms on its boundary and
contain no internal atoms. Centers of alpha spheres are clustered into
hydrophobic and hydrophilic areas.
Binding Site Identification
Geometric analysis of a molecule
• Alpha spheres identify cavities
• Sphere size is related to degree of exposure
• Small spheres indicate "tight" cavities
• The sphere size is not reflected in the graphical representation of
centroids
• Centroids are clustered for display
• Hydrophilic contact points are marked
by red centroids
• Hydrophobic (defined as
non-hydrophilic) are colored white.
P33 Protein Kinase
Exercise: Query generation and Search from Receptor Site
- Binding Site Identification I
Use alpha spheres to predict ligand
positions
1. (MOE | File | Open) for the file
1ke6.moe
2. Open (MOE | Compute | Site
Finder)
3. Click “Apply” on the Site Finder
panel
17 sites are found …
Site Finder Panel
Atoms included in the
calculation
Display mode of alpha
spheres
Display mode of site(s);
Residue selection option
Creates dummy atoms
Minimum sphere radii to
detect (non-) LP-active
atoms
Settings for alpha
sphere clustering
Site list:
Site: Site number
Size: Number of
contributing spheres
Hyd: Number of
hydrophobic atoms
contacted in receptor
Side: Number of
sidechain contact
atoms
Residues: Residues at
local surface
Distance filter before
clustering
Exercise: Query generation and Search from Receptor Site
- Binding Site Identification II
4. Examine the different sites. The 2nd site has
more receptor contacts but fewer
hydrophobic contacts.
5. Select the first site. To restrict the view to the
immediate environment by selecting Isolate:
“Atoms” and enable SE Residues.
Ensure that (MOE | Selection | Synchronize)
is ON. Invert the selection (MOE | Selection |
Invert) and delete all hidden residues.
6. Keep the positions of the Alpha Centers by
pressing “Dummies” and close the panel.
7. To increase the size of the dummy atoms
<Ctrl>-click on one of the dummy atoms to
select all of them. Select (Render | Space
Filling).
Red: Potential hydrophilic contact
areas
Exercise: Query generation and Search from Receptor Site
- Binding Site Identification III
8. Create a surface for the pocket using
(MOE | Compute | Surfaces and
Maps).
9. In the panel, keep default settings but
select
Near: Dummy Atoms
Click: Apply
The colours of the surface displays those
regions of the receptor surface suitable for
a hydrogen bond or metal-lone-pair
interactions.
Try also different surface color schemes to
compare the results or modify the
transparency (TF, TB) settings.
10. Save the pocket as
1ke6_pocket.moe
Receptor Contact Preferences
Objective
This approach complements the site finder information by identifying
preferred areas for hydrophobic or hydrophilic interactions based on
statistical preferences derived from non-bonding contacts in high
resolution protein structures.
Methodology
Non-bonded protein-ligand interactions are
analyzed with respect to distance, angle and
out-of-plane preferences. The receptor and
ligand atoms are classified into atom types
and the experimental histograms of the
contacts are fitted by analytical functions.
Contour maps display likelihood ratios for
hydrophobic over hydrophilic preferences
(green) or vice versa (red).
Receptor Atom Classification
• For each receptor atom, A, define a coordinate system
– Define vectors u and v derived from hybridization and heavy neighbors
– Some atom types do not have a u or a v (taken to be zero)
u
A
v
v
u
A
u
A
v taken from pi system
• Define polar coordinate system from u and v
– Distance from atom A
r
“distance”
– Angle with u vectora
“lone pair angle”
– Angle with u in u-v plane p
“out-of-plane angle”
v
u
p
a
• A contact atom, B, is mapped to (r,a,p) local coordinates
A
r
B
Receptor Atom Classification - Atom Typing
0,16
T_nQ2: HYD (50%) LPA (50%)
r
0,12
0,08
0,04
0
1,5
1,74
1,98
2,22
2,46
2,7
2,94
3,18
3,42
3,66
3,9
4,14
4,38
0,32
a
0,24
0,16
0,08
r
a
p
HYD
lognorm
gamma
gamma
LPA
12-6
cauchy
cauchy
0
2,5
22,5
42,5
62,5
82,5
102,5
122,5
142,5
162,5
N
0,32
NH
p
0,24
0,16
O
HN
N
0,08
0
2,5
17,5
32,5
47,5
62,5
77,5
NH
Exercise: Query generation and Search from Receptor Site
- Contact Preferences
Contact preferences can be used to generate or refine a Ph4 query.
1. Hide the molecular surface from the
previous exercise in (MOE | Window |
Graphic Objects) to concentrate on contact
potentials.
2. Select Surface: “Contact Preference” in the
Surface and Maps panel and press Apply.
3. Play with different contour levels and display
styles.
Exercise: Query generation and Search from Receptor Site
- Pharmacophore Query Editor I
The suggestions for preferred interactions in the binding site may be used to
derive a Ph4 query in absence of any known ligands.
1.
2.
3.
4.
Open (MOE | File | New | Pharmacophore Query),
select an Ph4 scheme, e.g. PPCH_all.
Features are created in clusters of hydrophilic or
hydrophobic groups.
Select individual dummy atoms to place the new
feature. In the Query Editor, press Feature. A
generic ‘Any’ feature will be created.
Adjust the feature positions by using
<Shift><Alt><middle mouse button>.
Furthermore modify and reassign the feature types
adjusting the radii, expressions, etc. according to
chemical intuition.
Exercise: Query generation and Search from Receptor Site
- Pharmacophore Query Editor II
5. Once finished creating features, an excluded volume
may be added.*)
Use a surface representation to guide the adjustment
of tolerances for the excluded volume.
Exercise: Query generation and Search from Receptor Site
- Pharmacophore Search
Save and use this query in the same way as the ones
generated in the previous exercises.
6.
Save the query as PPCH_ALL_sitefindV.ph4
7.
Press Search and define the databases to be
searched, consecutively double clicking on them,
or select and then press Add.*)
8.
Once the list is complete, press OK
9.
The Search panel will reflect multiple databases.
Continue with search process as previous
exercises.
10. Note that the databases should be pre-annotated
with the ph4 scheme
Case Studies in Pharmacophore Search
Module 3: Structure-based design with known actives and structural
binding site details
Case studies
Small molecules
Yes
no
No
Protein
structure
Module 1
Yes
Module 3
Module 2
Module 3: Structure Based Ph4 Design
If structural information about both proteins and their ligands is available, the
essential (conserved) protein ligand interactions (e.g. H-bonds) can be
identified and used to focus on the key Ph4 features. Since those interactions
include “projected” protein interaction sites, the results should be more
meaningful than a small molecule alignment in itself.*)
MOE provides several applications to analyze protein-ligand information:
• Alignment and superposition of proteins
• Ph4 consensus analysis
• Surface properties and contact preferences
In the Protein course:
• Homology modeling (if only the amino acid
sequence of a protein is available)
Workflow of Structure Based Ph4 Design
1. Align a set of proteins with their co-crystallized ligands.
• Ligands should already be docked in the binding site
2. Generate the relevant pharmacophore features based on SAR
• Identify conserved Ph4 features with a Ph4 consensus analysis
• Define the features based on biological/chemical knowledge of
interactions
• Identify key features based on interactions using Contact Statistics,
Molecular Surfaces or Hydrogen Bonding interactions
3. Save pharmacophore model
• Refine using Excluded volumes, or
Interior Volumes for SMILES strings
4. Search conformational database(s) for
ligands that contain the relevant pharmacophores
5. Re-design the pharmacophore model, if
necessary and search again