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CZ5226: Advanced Bioinformatics Lecture 8: Molecular Modeling Method Prof. Chen Yu Zong Tel: 6874-6877 Email: csccyz@nus.edu.sg http://xin.cz3.nus.edu.sg Room 07-24, level 7, SOC1, National University of Singapore References on Modeling of MHC Binding Peptide

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slide1

CZ5226: Advanced BioinformaticsLecture 8: Molecular Modeling Method Prof. Chen Yu ZongTel: 6874-6877Email: csccyz@nus.edu.sghttp://xin.cz3.nus.edu.sgRoom 07-24, level 7, SOC1, National University of Singapore

references on modeling of mhc binding peptide
References on Modeling of MHC Binding Peptide
  • Protein Sci. 2004 Sep;13(9):2523-32
  • J Am Chem Soc. 2004 Jul 14;126(27):8515-28
  • Proteins. 2004 Feb 15;54(3):534-56
  • Hum Immunol. 2003 Dec;64(12):1123-43
  • Immunity. 2003 Oct;19(4):595-606
  • Mol Med. 2003 Sep-Dec;9(9-12):220-5
  • Nature. 2002 Aug 1;418(6897):552-6
  • Eur J Immunol. 2002 Aug;32(8):2105-16
  • Immunol Cell Biol. 2002 Jun;80(3):286-99
  • Ann N Y Acad Sci. 2002 Apr;958:317-20
  • Mol Immunol. 2002 May;38(14):1039-49
  • J Pept Res. 2002 Mar;59(3):115-22
  • Mol Immunol. 2002 Feb;38(9):681-7
  • Tissue Antigens. 2002 Feb;59(2):101-12
  • J Comput Aided Mol Des. 2001 Jun;15(6):573-86
  • J Mol Biol. 2000 Jul 28;300(5):1205-35
  • J Comput Aided Mol Des. 2000 Jan;14(1):71-82
  • J Comput Aided Mol Des. 2000 Jan;14(1):53-69
  • J Mol Graph Model. 1999 Jun-Aug;17(3-4):180-6, 217
what is docking

T

Complex

Receptor

Ligand

What is Docking?
  • Given two molecules find their correct association:

=

+

general protein ligand binding
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

what is protein ligand docking
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

example hiv 1 protease
Example: HIV-1 Protease

Active Site

(Aspartyl groups)

docking strategy
Docking Strategy

PDB

files

Surface Representation

Patch Detection

Matching Patches

Scoring & Filtering

Candidate

complexes

issues involved in docking
Issues Involved in Docking
  • Protein Structure and Active Site

- assumed knowledge (PDBs, etc.)

- PROCAT database: 3d enzyme active site templates

  • Ligand Structure

- pharmacophore (base fragment) in potential drug compound

- well known groups

  • Rigid vs. Flexible

- solution or vacum

- structure

algorithmic approaches to docking
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
slide11
.

Design of HIV-1 Protease Inhibitor

slide12
.

Design of HIV-1 Protease Inhibitor

slide13
.

Design of HIV-1 Protease Inhibitor

slide14
.

Design of HIV-1 Protease Inhibitor

scoring in ligand protein docking
Scoring in Ligand-Protein Docking

Potential Energy Description:

preprocessing
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

some techniques
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
surface representation19
Surface Representation
  • Each atomic sphere is giventhe 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
lenhoff technique
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

kuntz et al clustered spheres
Kuntz et al. Clustered-Spheres
  • Uses clustered-spheres to identify cavities on the receptor andprotrusions on the ligand
  • Compute a sphere for every pair of surface points, i and j, withthe sphere center on the normal from point i
  • Regions where many spheres overlap are either cavities (on thereceptor) or protrusions (on the ligand)

j

i

alpha shapes
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
alpha shapes example
Alpha Shapes: Example

Alpha=infinity

Alpha=3.0 Å

surface matching
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

      • Selet the fit that has the minimum energy
slide25
.

Design of HIV-1 Protease Inhibitor

docking programs
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)
dock as an example
DOCK as an Example

DOCK works in 5 steps:

  • Step 1 Start with crystal 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
dock as an example28
DOCK as an Example

1

2

  • HIV-1 protease is
  • the target receptor
  • Aspartyl groups are
  • its active side

3

dock as an example29
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
the dock algorithm
The DOCK Algorithm

Two steps in rigid ligand mode:

Orienting the putative ligand in the site

Guided by matching distances, between pre-defined 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

slide31
Define the target binding site points.
  • Match the distances.
  • Calculate the transformation matrix for the orientation.
  • Dock the molecule.
  • Score the fit.
site points generation in dock
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.
the matching
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!

other docking programs
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.
conformational ensembles docking36
Conformational Ensembles Docking

Observations:

  • Generating an orientation of a ligand in a binding site may be separated from calculating a conformation of the ligand in that particular orientation.
  • Multiple conformations of a given ligand usually have some portion in common (internally rigid atoms such as ring systems), and therefore, contain redundancies.
conformational ensemble docking38
Conformational Ensemble Docking
  • Conformational ensembles are generated by overlaying all conformations of a given molecule onto its largest rigid fragment.
  • Only atoms within this largest rigid fragment are used during the distance matching step. The RT matrix is defined.
  • Each of the conformers is oriented into the site and scored. The score measures steric and electrostatic complementarity.
  • One matching steps - all the conformers are docked and scored in the selected orientation.
advantages of conformational ensemble docking
Advantages of Conformational Ensemble Docking

Speed increase due to:

  • One matching step for all the conformers.
  • The largest rigid fragment usually has fewer atoms (less potential matches are examined).
disadvantages of conformational ensemble docking
Disadvantages of Conformational Ensemble Docking
  • Loss of information when the orientations are guided only by a subset of the atoms in molecule. Orientations may be missed because potential distance matches from non-rigid portions of the molecule are not considered.
  • The ensemble method will fail for ligands that lack internally rigid atoms.
  • The use of chemical matching and critical clusters is limited.
results of docking studies
Results of Docking Studies

The docked (blue) and crystal (yellow) structure of ligands in some PDB ligand-protein complexes. The PDB Id of each structure is shown.

dataset and testing results
Dataset and Testing Results

Protein-Proteincases from protein-protein docking benchmark [6]:

Enzyme-inhibitor – 22 cases

Antibody-antigen – 16 cases

Protein-DNAdocking: 2 unbound-bound cases

Protein-drugdocking: tens of bound cases (Estrogen receptor, HIV protease, COX)

Performance:Several minutes for large protein molecules and seconds for small drug molecules on standard PC computer.

Estrogen receptor

Estradiol molecule from complex

docking solution

DNA

endonuclease

Estrogen receptor with estradiol (1A52). RMSD 0.9Å, rank 1, running time: 11 seconds

docking solution

Endonuclease I-PpoI (1EVX) with DNA (1A73). RMSD 0.87Å, rank 2

results enzyme inhibitor docking
Results Enzyme-Inhibitor docking

1 Number of highly penetrating residues in unbound structures superimposed to complex

results antibody antigen docking
Results Antibody-Antigen docking

1 Number of highly penetrating residues in unbound structures superimposed to complex

quality of invdock algorithm proteins 1999 36 1

Description of Docking Quality

Molecule

Docked Protein

PDB Id

RMSD

Energy

(kcal/mol)

Match

Indinavir

HIV-1 Protease

1hsg

1.38

-70.25

Match

Xk263 Of Dupont Merck

HIV-1 Protease

1hvr

2.05

-58.07

Match

Vac

HIV-1 Protease

4phv

0.80

-88.46

One end match, the other in different orientation

Folate

Dihydrofolate Reductase

1dhf

6.55

-46.02

Match

5-Deazafolate

Dihydrofolate Reductase

2dhf

1.48

-65.49

Match

Estrogen

Estrogen Receptor

1a52

1.30

-45.86

Complete overlap, flipped along short axis

4-Hydroxytamoxifen

Estrogen Receptor

3ert

5.45

-55.15

Match

Guanosine-5'-[B,G-Methylene] Triphosphate

H-Ras P21

121p

0.94

-80.20

Overlap, flipped along short axis

Glycyl-*L-Tyrosine

Carboxypeptidase A a

3cpa

3.56

-40.63

Quality of INVDOCK AlgorithmProteins. 1999; 36:1
identification of the n terminal peptide binding site of grp94
Identification of the N-terminal peptide binding site of GRP94
  • GRP94 - Glucose regulated protein 94
  • VSV8 peptide - derived from vesicular stomatitis virus

Gidalevitz T, Biswas C, Ding H, Schneidman-Duhovny D, Wolfson HJ, Stevens F, Radford S, Argon Y. J Biol Chem. 2004

biological motivation
Biological motivation
  • The complex between the two molecules highly stimulates the response of the T-cells of the immune system.
  • The grp94 protein alone does not have this property. The activity that stimulates the immune response is due to the ability of grp94 to bind different peptides.
  • Characterization of peptide binding site is highly important.
grp94 molecule
GRP94 molecule
  • There was no structure of grp94 protein. Homology modeling was used to predict a structure using another protein with 52% identity.
  • Recently the structure of grp94 was published. The RMSD between the crystal structure and the model is 1.3A.
docking
Docking
  • PatchDock was applied to dock the two molecules, without any binding site constraints.
  • Docking results were clustered in the two cavities:
grp94 molecule51
GRP94 molecule
  • There is a binding site for inhibitors between the helices.
  • There is another cavity produced by beta sheet on the opposite side.