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Title: Proteinligand docking: A case study of DEF docking motif interactions in MAP kinases


1
Protein-ligand docking A case study of DEF
docking motif interactions in MAP kinases
  • Yong Kong
  • Bioinformatics Resource
  • Yale University

2
Outline
  • Available programs in Bioinformatics Resource
  • Introduction to molecular docking
  • Autodock 4 a free docking software
  • Substrate discrimination among MAP kinases
    through distinct docking motifs
  • Modeling DEF docking motif interactions in MAP
    kinases using Autodock 4

3
Available commercial software
  • DNA/protein sequence analysis
  • Lasergene
  • Gene Construction Kits
  • Microarray analysis
  • Genespring GX
  • Partek Genomics Suite
  • Pathway Analysis
  • Ingenuity Pathway Analysis
  • MetaCore
  • Genotyping analyses
  • Genespring GT
  • HelixTree

4
Available commercial software
  • Protein structure modeling and visualization
  • SYBYL 8
  • Pipelining programs
  • Pipeline Pilot
  • VIBE
  • Mass spectrometry data analysis
  • GPMAW

5
SYBYL
6
SYBYL
7
SYBYL
  • SYBYL Base Comprehensive tools for molecular
    modeling
  • structure building, optimization, and comparison
  • visualization of structures and associated data
  • annotation, hardcopy, and screen capture
    capabilities
  • a wide range of force fields

Electrostatic potential for inhibitor
methotrexate bound to dihydrofolate reductase
8
SYBYL
  • Receptor Based Design docking and de novo design
  • Ligand Based Design QSAR, ADME, pharmacophore,
    structure alignment, etc

Docked inhibitor (yellow) superimposed with
crystal structure (purple)
Left pharmacophore model right X-way structure
(CDK2 inhibitors)
9
SYBYL
  • Protein Modeling
  • A database of detailed structural profiles of all
    known protein families
  • Structural homologs identified by
    sequence-structure comparison
  • Comparative models built from a target sequence
    using single or multiple structural homologs

A set of structurally aligned oxidoreductase
structures of 8 sequence identity.
10
Molecular docking
  • Computationally predict
  • the structure (pose)
  • binding free energy
  • of the intermolecular complex formed between two
    or more constituent molecules

11
Questions and Goals
  • The questions we are interested in are
  • Do two biomolecules bind each other?
  • If so, how and where do they bind?
  • What is the binding free energy or affinity?
  • What chemical groups determine the binding?
  • The goals we have are
  • Searching for lead compounds
  • Estimating effect of modifications
  • General understanding of binding
  • Design directed libraries

12
Docking input data
  • The starting point
  • the atomic coordinates of the two molecules
  • Additional data
  • biochemical
  • mutational
  • conservational
  • These additional data can significantly improve
    the performance however, this extra information
    is not absolutely necessary

13
Docking two components
  • Two related components of docking
  • Search algorithm sample sufficiently and
    efficiently the degrees of freedom of the
    proteinligand system (position, orientation, and
    conformation)
  • Scoring function represent the thermodynamics of
    interactions so as to distinguish the true
    binding modes from all the other possible
    solutions, and to rank them accordingly

14
Flowchart of docking algorithms
15
Rigid or flexible molecules
  • Protein ligand
  • Rigid protein rigid ligand
  • Rigid protein flexible ligand
  • Flexible protein flexible ligand
  • Protein protein
  • Rigid protein rigid protein (still the
    standard)
  • Introducing flexibilities into protein-protein
    docking is challenging

16
Docking software total number of citations till
2005
Sousa, et. al (2006)
17
Docking programs citations per year
Sousa, et. al (2006)
18
Docking programs percentage of citations per year
freely available for academic users
Sousa, et. al (2006)
19
Autodock
  • Developed in Arthur Olsons lab in the Scripps
    Research Institute
  • Free academic license
  • The most used program for molecular docking
  • The latest version is Autodock 4

20
Autodock features
  • Pre-calculate atomic affinity potentials for each
    atom type in the ligand
  • Support different search methods
  • Lamarckian genetic algorithm (LGA)
  • traditional genetic algorithm (GA)
  • Monte Carlo simulated annealing
  • Reasonably accurate binding free energy the
    scaling factors are empirically calibrated from
    experimental data

21
Pre-calculated grid maps
  • A grid map consists of a three dimensional
    lattice of regularly spaced points, surrounding
    (either entirely or partly) and centered on some
    region of interest of the macromolecule under
    study.
  • The probe's energy at each grid point is
    determined by the set of parameters supplied for
    that particular atom type, and is the summation
    over all atoms of the macromolecule, within a
    non-bonded cutoff radius, of all pairwise
    interactions.

From AutoDock manual
22
Pre-calculated grid maps
  • After the grid map is calculated, it can be used
    repeatedly in the docking calculations
  • The time to perform an energy calculation using
    the grids is proportional only to the number of
    atoms in the ligand, and is independent of the
    number of atoms in the receptor

23
Genetic Algorithm (GA)
  • Computational method based on the ideas and
    language of natural genetics and evolution
  • State variables (translation, orientation, and
    conformation of ligands) ?? genes
  • These genes make up the genotypes
  • Atomic coordinates are phenotypes
  • Fitness is the total interaction energy

Gene1
Gene2
Gene3
One for each torsion

x
y
z
q0
q1
q2
q3
t1
t2
t3
quaternion
chromosome
24
Genetic Algorithm (GA)
  • The evolution starts from a population of
    randomly generated individuals
  • Random individuals are mated randomly
  • New individuals inherit genes from either
    parent through crossover
  • ABC/abc ? AbC/aBc
  • Some offspring undergo random mutation (one
    gene is changed by a random amount)
  • Selection of offspring is based on fitness

25
Genetic Algorithm (GA)
Create a random population
Fitness evaluation
Selection best individuals to reproduce, and
their offspring
Crossover ABC/abc ? AbC/aBc
Mutation (based on Cauchy distribution)
Elitist select (top individuals survive into next
generation)
Termination generation? OR energy evaluation?
26
Lamarckian Genetic Algorithm
  • Most GAs mimic Darwinian evolution one-way
    transfer of information from genotype ? phenotype
    (right-side)
  • This corresponds to the global search of the
    minima

fitness
Darwinian
Lamarckian
27
Lamarckian Genetic Algorithm
fitness
  • One novel improvement of Autodock is the
    incorporation of local search (left-side)
  • This is called Lamarckian Genetic Algorithm
    (LGA), in allusion to Larmarcks discredited
    assertion that phenotype acquired can become
    heritable.

Darwinian
Lamarckian
28
Lamarckian Genetic Algorithm
  • Its only possible for LGA if the mapping
    function from genotype ? phenotype is invertible
    phenotype ? genotype
  • Genotype ?? Phenotype
  • Another novel feature of Autodock
  • the local search is done in the genotypic space
    rather than phenotypic space
  • So there is no need for the mapping to be
    inverted
  • Performance LGA gt GA gt SA

29
Autodock Scoring Function
Dispersion/repulsion
H-bond
  • The program uses a five-term force field-based
    function loosely based on the AMBER force field
  • The scaling factor for each of these five terms
    is empirically calibrated from a set of 30
    structurally known proteinligand complexes.

electrostatic
DGtor entropic term
DGsol intermolecular pairwise desolvation term
30
Protein kinases
  • Phosphorylation is the most common reversible
    post-translational protein modification in
    eukaryotes
  • Protein kinases are key players in signal
    transduction networks
  • Many cancers are characterized by uncontrolled
    kinase activity

31
The human kinome
32
Kinase specificity
  • Tight control of the specificity of protein
    kinases is required to maintain normal physiology
  • Specificity is determined in part through
    recognition of consensus sequences around the
    site of phosphorylation
  • However, active site alone is not enough short
    amino acid sequence motifs can occur at high
    frequency in proteomes
  • 700,000 potentially phosphorylatable residues

33
Ubersax and Ferrell (2007)
34
Docking interactions ensure specificity
  • Combinatorial docking interactions are a
    generally-used mechanism to ensure kinase
    specificity
  • The docking sites are distal from the
    phosphorylation site in the substrates
  • Outside the active site in the kinase

35
MAP kinases
  • Mediate cellular responses to a wide variety of
    extracellular stimuli growth factor, cytokines,
    UV, oxidative stress, etc.
  • Regulate many important cellular activities gene
    expression, mitosis, movement, metabolism, cell
    death, etc.
  • MAP kinases lie at the bottom of conserved
    three-component phosphorylation cascades

36
MAP Kinase cascade
37
MAPKs
Ramen, et. al (2007)
38
MAP kinases
  • Three major subfamilies
  • ERK (extracellular regulated kinases) ERK1 and
    ERK2
  • p38 p38a, p38b, p38g, p38d
  • JNK (c-Jun N-terminal kinases) JNK1-3
  • The different MAPK subfamilies phosphorylate a
    distinct set of protein substrates

39
Consensus sequence
  • Consensus sequence for ERK1, ERK2 and p38a
  • P-X-S/T-P
  • 700,000 potentially phosphorylatable residues
  • Needs other mechanisms to ensure specificity

40
MAPKs common phos-site
  • Positional scanning peptide library
    Systematically substitutions of 20 a.a pT pY
    at the 9 positions surrounding a central
    phosphorylation site (9 x 22)
  • Confirmed the P-X-S/T-P previously found for ERK2
    and p38a
  • No significant differences among any of the four
    representative MAPKs

Sheridan et. al
41
D-site
  • Two docking interactions D-site DEF site
  • The first one D-site (also referred to as the
    D-domain, d-domain, or DEJL domain)
  • Two or more basic residues followed by a short
    linker and a cluster of hydrophobic residues
  • Docking occurs along a groove on the opposite
    face of the active site of MAPK

42
D-site
  • Well-characterized
  • Mutagenesis
  • Hydrogen-exchange mass spectrometry (HX-MS)
  • X-ray crystallography

Lee, et. al (2004)
43
DEF site
  • DEF site (docking site for ERK FXF, also called
    the F-site)
  • Best characterized in ERK
  • F-X-F/Y-P
  • 6 and 20 amino acids C-terminal to the
    phosphorylation site

44
DEF motif
  • Peptide derived from Elk1 386-399 (phos-site
    DEF site)
  • 19 a.a. (excluding cys) substitutions at each
    four positions (Z)
  • The extent of phosphorylation was quantified

Sheridan et. al
45
DEF motif
aromatic
Selectivity gt 1.5 (bold when gt 3.0)
aliphatic
Sheridan et. al
No preference
46
DEF site selectivity
Phos-site
DEF site
p38a
p38d
Sheridan et. al
47
DEF interacting pocket - HX-MS
green decreased exchange rate upon DEF peptide
binding ? solvent protection
Lee, et. al (2004)
48
DEF interacting pocket - HX-MS
yellow surface hydrophobic residues
Strongest protected regions
Lee, et. al (2004)
pT183, pY185
49
Docking with autodock
  • Ligand a capped pentapeptide DEF site ligand
    acetyl-SFQFP-amide
  • Receptor published structure of diphosphorylated
    ERK2 (PDB code 2ERK)
  • Grid map 50 x 50 x 50 points with a spacing of
    0.375 Å, centered on the previously identified
    hydrophobic pocket on the ERK2 surface
  • 256 independent docking runs

50
Grid map
51
Autodock results model clusters
Clustering threshold RMSD 2 Å
52
Model of DEF site interaction
Orange peptide ligand Green hydrophobic pocket
53
Model of DEF site interaction
54
Model of DEF site interaction
55
Model of DEF site interaction
56
Structural determinants mutagenesis studies
Highlighted residues surrounding the DEF pocket
  • Alanine substitutions of key residues in the
    binding pocket significantly attenuate
    phosphorylation (except for L195A of p38d)

57
Mutagenesis studies
  • Mutants that swap DEF site specificity

WT aromatic ? DM aliphatic
WT aliphatic ? DM aromatic
Sheridan et. al
58
Mutagenesis studies
  • Collectively these mutagenesis experiments and
    molecular docking support a mode of binding
  • P1 residue contacts residues analogous to Ile196,
    Met197 and Leu198 of ERK2
  • P3 residue makes contact with Leu235

59
Acknowledgements
Dr. Turk Dr. Sheridan Department of Pharmacology,
Yale University
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