Transcript Lect 5 part 1 - BIDD - National University of Singapore

BL5203: Molecular Recognition & Interaction
Lecture 5: Drug Design Methods
Ligand-Protein Docking (Part I)
Prof. Chen Yu Zong
Tel: 6874-6877
Email: [email protected]
http://xin.cz3.nus.edu.sg
Room 07-24, level 7, SOC1,
National University of Singapore
What is Docking?
• Given two molecules find their correct
association:
T
=
+
2
General Protein–Ligand Binding
• Ligand
- Molecule that binds with a protein
- DNA, drug lead compounds, etc.
• Protein active site(s)
- Allosteric binding
- Competitive binding
• Function of binding
interaction
- Natural and artificial
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What is Protein-Ligand Docking?
• Definition:
Computationally predict the structures of protein-ligand
complexes from their conformations and orientations.
The orientation that maximizes the interaction reveals
the most accurate structure of the complex.
• Importance of complexes
- structure -> function
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Example: HIV-1 Protease
Active Site
(Aspartyl groups)
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Example: HIV-1 Protease
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Docking Strategy
PDB
files
Surface Representation
Patch Detection
Matching Patches
Scoring & Filtering
Candidate
complexes
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Issues Involved in Docking
• Protein Structure and Active Site
- Assumed knowledge (PDBs, Homology modeling etc.)
- PROCAT database: 3d enzyme active site templates
• Ligand Structure
- Pharmacophore (base fragment) in potential drug compound
- well known groups
• Rigid vs. Flexible
- In solution or in vaccume
- Structure fixed, partly fixed, modeling of flexibility
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Algorithmic Approaches to Docking
• Qualitative
– Geometric
– Shape complementarity and fitting
• Quantitative
– Energy calculations
– Determine global minimum energy
– Free energy measure
• Hybrid
– Geometric and energy complementarity
– 2 phase process: soft and hard docking
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Design of HIV-1 Protease Inhibitor
.
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Design of HIV-1 Protease Inhibitor
.
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Design of HIV-1 Protease Inhibitor
.
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Design of HIV-1 .Protease Inhibitor
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Scoring in Ligand-Protein Docking
Potential Energy Description:
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Preprocessing
• Determine internal representation
- Convert coordinates of both molecules from PDB files
- e.g. Michael Connolly’s MS program
(www.biohedron.com)
- dot surface
- AutoGrid
- 3d grid (array) with discrete values
- often used in rigid docking
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Some techniques
• Surface representation, that efficiently represents the
docking surface and identifies the regions of interest
(cavities and protrusions)
•
•
•
•
Connolly surface
Lenhoff technique
Kuntz et al. Clustered-Spheres
Alpha shapes
• Surface matching that matches surfaces to optimize a
binding score:
• Geometric Hashing
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Surface Representation
• Dense MS surface
(Connolly)
• Sparse surface (Shuo
Lin et al.)
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Surface Representation
• Each atomic sphere is
given the van der Waals
radius of the atom
• Rolling a Probe Sphere
over the Van der Waals
Surface leads to the
Solvent Reentrant
Surface or Connolly
surface
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Lenhoff technique
• Computes a “complementary” surface for the receptor
instead of the Connolly surface, i.e. computes possible
positions for the atom centers of the ligand
Atom centers of the ligand
van der Waals surface
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Kuntz et al. Clustered-Spheres
• Uses clustered-spheres to identify cavities on the receptor and
protrusions on the ligand
• Compute a sphere for every pair of surface points, i and j, with
the sphere center on the normal from point i
• Regions where many spheres overlap are either cavities (on the
receptor) or protrusions (on the ligand)
j
i
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Alpha Shapes
• Formalizes the idea of “shape”
• In 2D an “edge” between two points is “alpha-exposed” if
there exists a circle of radius alpha such that the two
points lie on the surface of the circle and the circle
contains no other points from the point set
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Alpha Shapes: Example
Alpha=infinity
Alpha=3.0 Å
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Surface Matching
• Find the transformation (rotation + translation) that will
maximize the number of matching surface points from
the receptor and the ligand
First satisfy steric constraints…
• Find the best fit of the receptor and ligand using only geometrical
constraints
… then use energy calculations to refine the docking
• Select the fit that has the minimum energy
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Design of HIV-1 Protease Inhibitor
.
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Docking Programs
More information in: http://www.bmm.icnet.uk/~smithgr/soft.html
The programs are:
• DOCK (I. D. Kuntz, UCSF)
• AutoDOCK (Arthur Olson, The Scripps Research Institute)
• RosettaDOCK (Baker, Washington Univ., Gray, Johns
Hopkins Univ.)
• INVDOCK (Y. Z. Chen, NUS)
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DOCK as an Example
DOCK works in 5 steps:
• Step 1 Start with 3D coordinates of target receptor
• Step 2 Generate molecular surface for receptor
• Step 3 Generate spheres to fill the active site of the
receptor: The spheres become potential locations for
ligand atoms
• Step 4 Matching: Sphere centers are then matched to
the ligand atoms, to determine possible orientations for
the ligand
• Step 5 Scoring: Find the top scoring orientation
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DOCK as an Example
1
2
- HIV-1 protease is
the target receptor
- Aspartyl groups are
its active side
3
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DOCK as an Example
4
5
• Three scoring schemes: Shape scoring, Electrostatic scoring
and Force-field scoring
• Image 5 is a comparison of the top scoring orientation of the
molecule thioketal with the orientation found in the crystal
structure
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The DOCK Algorithm
Two steps in rigid ligand mode:
Orienting the putative ligand in the site
Guided by matching distances, between predefined site points on the target to interatomic
distances of the ligand. The RT matrix is used for
the transform of the ligand.
Scoring the resulting orientation
Each orientation is scored for each quality fit. The
process is repeated a user-defined number of
orientations or maximum orientations
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1. Define the target
binding site points.
2. Match the distances.
N
F
H N
N
O
S
N
3. Calculate the
transformation matrix
for the orientation.
F
H N
N
O
S
N
F
H N
N
O
4. Dock the molecule.
S
N
F
H N
N
O
5. Score the fit.
S
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Site Points Generation in DOCK
• Program SPHGEN identifies the active site, and other
sites of interest.
• Each invagination is characterized by a set of
overlapping spheres.
• For receptors, a negative image of the surface
invaginations is created;
• For a ligand, the program creates
a positive image of the entire molecule.
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The Matching
Can be directed by 2 additional features:
• Chemical matching - labeling the site points such that
only particular atom types are allowed to be matched to
them.
• Critical cluster - subsets of interest can be defined as
critical clusters, so that at least one member of them
will be part of any accepted ligand “match”.
Increase in efficiency and speed due to elimination of
potentially less promising orientations!
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Other Docking programs
AutoDock
– AutoDock was designed to dock flexible ligands into receptor
binding sites
– The strongest feature of AutoDock is the range of powerful
optimization algorithms available
RosettaDOCK
– It models physical forces and creates a very large number of
decoys
– It uses degeneracy after clustering as a final criterion in decoy
selection
INVDOCK
– Docking strategy and algorithm similar to DOCK, but with the
capability of finding the receptors to which a molecule can bind
to.
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