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SOME EXAMPLES. CHRISTOPH PFISTERER DAN MIHAILESCU JENNIFER REED. Does the gp120 recognition peptide have a similar structure in all clades of HIV-1 ?. 11 Sequences in 9 clades A1 LEU PRO CYS ARG ILE LYS GLN PHE ILE ASN MET TRP GLN GLU VAL +2 - PowerPoint PPT Presentation
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•SOME EXAMPLES
CHRISTOPH PFISTERER
DAN MIHAILESCU
JENNIFER REED
11 Sequences in 9 clades
• A1 LEU PRO CYS ARG ILE LYS GLN PHE ILE ASN MET TRP GLN GLU VAL +2• B1 LEU PRO CYS ARG ILE LYS GLN ILE VAL ASN MET TRP GLN GLU VAL +2• C1 ILE PRO CYS ARG ILE LYS GLN ILE ILE ASN MET TRP GLN GLU VAL +2• D2 LEU PRO CYS ARG ILE LYS PRO ILE ILE ASN MET TRP GLN GLU VAL +2• E2 LEU PRO CYS LYS ILE LYS GLN ILE ILE ASN MET TRP GLN GLY VAL +3• E3 LEU PRO CYS LYS ILE LYS GLN ILE ILE LYS MET TRP GLN GLY VAL +4• F1 LEU LEU CYS LYS ILE LYS GLN ILE VAL ASN LEU TRP GLN GLY VAL +2• G2 LEU PRO CYS LYS ILE LYS GLN ILE VAL ARG MET TRP GLN ARG VAL +5• 1A0 LEU PRO CYS LYS ILE LYS GLN ILE VAL ASN MET TRP GLN ARG VAL +4• 2A3 LEU GLN CYS ARG ILE LYS GLN ILE VAL ASN MET TRP GLN LYS VAL +4• OC4 ILE PRO CYS LYS ILE LYS GLN VAL VAL ARG SER TRP ILE ARG GLY +5
Does the gp120 recognition peptide have a similar structure in all clades of HIV-1 ?
Questions
Are the gp120 recognition sequence peptides structured in aqueous solution?
Threading of sequences on the peptide backbone
A1 oc4
LEU PRO CYS ARG ILE LYS GLN PHE ILE ASN MET TRP GLN GLU VAL
ILE PRO CYS LYS ILE LYS GLN VAL VAL ARG SER TRP ILE ARG GLY
Molecular Dynamics Simulation Setup
• Box dimensions: 53x40x40 Ǻ• Explicit water molecules (TIP3P)
(~8600 atoms)• Explicit ions
(Sodium and Chloride, 26 ions in total);physiological salt: 0.23M
• ~240 peptide atoms=> approx. 8900 atoms in total
• Uncharged system• NPT ensemble: 300K, 1atm• 5ns simulation time for each strain
=> 55ns total simulation time
Root Mean Square Coordinate Deviation
MT D
MD simulations
Convergence of gp120 peptide structurefrom three different experimental starting geometries
Questions
Are the gp120 recognition sequence peptides structured in aqueous solution?
Do the structures of peptides from different clades resemble each other?
Dihedral angles
Questions
Are the gp120 recognition sequence peptides structured in aqueous solution?
Do the structures of peptides from different clades resemble each other?
Does the consensus structure present a common shape/electrostatic surface?
Shape and electrostatic properties conserved.
Questions
Are the gp120 recognition sequence peptides structured in aqueous solution?
Do the structures of peptides from different clades resemble each other?
Does the consensus structure present a common shape/electrostatic surface?
Can the consensus shape/electrostatic surface be mimicked with a synthetic molecule?
Can this molecule be used as a lead for vaccine design?
Detection of Individual p53-Autoantibodies in Human Sera
Cancer Biotechnology.
Rhodamine 6G
O H
N
O
O
N
N
MR121
Fluorescence Quenching of Dyes by Trytophan
Dye
Quencher
Fluorescently labeled Peptide
?
Rhodamine- Tryptophan complex MD simulations in water
• NPT 300K, 1 atm, explicit water (~1000 TI P3P waters)– TO periodic boundary conditions
• 7 ns production runs f or each starting structure (28 ns total)
• PME electrostatics
0 5 1 0 1 5 2 0
0
2 0
4 0
6 0
8 0
1 0 0
1 2 0
1 4 0
1 6 0
1 8 0
P M F
[ k c a l / m o l ]
r [ Å ]
[deg]
0
1 . 0
2 . 0
3 . 0
4 . 0
5 . 0
PMF Landscape R6G/ W
Quenching efficiency at 50 mM ~ 75%
Analysis
r
Analysis 2
0 5 1 0 1 5 2 0
0
2 0
4 0
6 0
8 0
1 0 0
1 2 0
1 4 0
1 6 0
1 8 0
P M F
[ k c a l / m o l ]
r [ Å ]
[deg]
0
1 . 0
2 . 0
3 . 0
4 . 0
5 . 0
Strategy:
Quenched Fluorescent
Results:
HealthyPersonSerum
CancerPatientSerum
Drug Design
Finding the Right Key for the Lock
Ligand Binding.
vibrational changes?
physicochemical understanding
Protein
Ligand
Complex
Bovine Pancreatic
Trypsin Inhibitor
Normal Mode Analysis
Vibrational Change onBurial of a Water Molecule
Frequency Shifts
STEFAN FISCHER
Dissecting the Vibrational Entropy Change on Protein/Ligand Binding: Burial of a Water Molecule in BPTI
Librational modes = 9.4 cal mol-1 K-1
Softening of protein = 4.0 cal mol-1 K-1
Change in Entropy due to Frequency Shifts
Frequency Shifts
Vibrational Change on Methotrexate Binding to Dihydrofolate Reductase
ERIKA BALOGTORSTEN BECKER
0 2 4 6 8 10 12 14 16 18 20
0.0
0.5
1.0
1.5
2.0
g(
) (m
ode
/cm
-1)
(cm-1)
0 40 80 1200
4
8
12
jVIBRATIONALFREQUENCYDISTRIBUTION
complexed uncomplexed
Vibrational Thermodynamics
Gvib = -4.0 1.0 kcal/mol-TSvib= -6.0 1.5 kcal/molHvib = +2.0 0.5 kcal/mol
High Throughput Screening
104 ligands per day
Drug Design
But: Hit Rate 10-6 per ligand
What is the binding free energy?
]][[
][
1
1
LP
C
k
kKbind
bindbind KRTΔG ln
ligand
protein
complex
water
polar and
non-polar
interactions with the solvent
polar and
non-polar
protein-ligand interactions
entropic effects
k1 k-1
FRAUKE MEYER
Electrostatics: Thermodynamic Cycle
+
+
)(PGsolv )(LGsolv )(CGsolv
)80( elG
)4( elG
80
4
Methods
• flexibility (Jon Essex)
• MD (Daan van Aalten)
• scoring functions, virtual screening (Martin Stahl, Qi Chen)
• prediction of active sites (Gerhard Klebe)
• active site homologies
Ligands: set n0
Fast Calculation of Absolute Binding Free Energies: Interaction of Benzamidine Analogs with Trypsin
Benzamidine-like Trypsin Inhibitors Energy Terms and Results
- van der Waals protein:ligand
- hydrophobic effect (surface area dependent)
- electrostatic interactions (continuum approach)
- translational, rotational, vibrational degrees of freedom
End ss 2004
Results: Binding free energies
Fig: Calculated versus experimental binding free energies
-16.0
-14.0
-12.0
-10.0
-8.0
-6.0
-4.0
-2.0
0.0
2.0
4.0
-12.0 -10.0 -8.0 -6.0 -4.0 -2.0 0.0
dG(exp) [kcal/mol]
dG
(ca
lc)
[kca
l/mo
l]
flexible system,CHARMM-AM1
fixed system,MAB
RMSD(flex)
= 1.3 kcal/mol
RMSD(fix)
= 3.2 kcal/mol
CONCLUSION: Including flexibility improves the prediction of
binding free energies
OUTLOOK: Introduction of polarisation energy
Automation of the free energy calculation protocol
THANKS! Jeremy, Stefan, Sonja, Bogdan, girls’ room
Results: Energy contributions
Fig: Range of calculated binding free energies and the contributing terms for the ligands of set n0 and n1
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
dGbind dGtr dGvib dGval dGqm dGsolv,p dGcoul dGvdw dGsolv,np
dG
[k
ca
l/mo
l]
<dG>
Successes and failures in
structure-based drug design
Mercedes L. Dragovits
The drug discovery and development pipeline
Choice of a target
• Link to a human disease
• Binds a small molecule to carry out a function
• The drug competes with the natural molecule
Theiterative process
of SBDD
Overview of the process:
first
cycle • Cloning, purification, structure determination of the target
– X-ray-crystallography
– NMR
• Compounds or fragments of compounds are placed in selected regions of the target using computer algorithms
• Test the best compounds with biochemical assays
Overview of the process:
second cycle
• Structure of the target in complex with a lead from the first cycle
Several additional cycles:
• Synthesis of optimized lead
• Structure determination of the new complex
• Further optimization of the lead compound
X-ray crystallography
• About 80 percent of the protein structures that are known have been
determined using X-ray crystallography
X-Ray Beam Crystal Scattered X-Rays Detector Computed Image of atoms in crystal
X-ray crystallography
I. Protein expression
II. Purification
III. crystallization
X-ray crystallography
• High resolution
• Wide range of proteins
• Ordered H2O molecules are visible
• Information might be ambiguous
NMR• Conc. nucleic acid or
protein in solution (½ ml)
NMR
• No limitation to molecules that crystallize well
• Flexibility of molecules and their interaction with other
compounds
• Size limitation
• NMR is 20 years younger than X-ray crystallography
NMR vs. X-ray crystallography
• Both methods have their advantages and disadvantages
• Ideally, these two techniques complement one another
Drug Design methods
1) Inspection
2) Virtual screening
3) De novo generation
Drug lead evaluation
• Computer graphics
• Is the drug lead orally bioavailable?
• Chemical and metabolic stability
• Ease of synthesis
• Biochemical evaluation in the lab
Pharmaceutical companies
• „Syrrx“
Robotics in several parts of the process
Pharmaceutical companies
• „Vertex Pharmaceuticals“
„chemogenomic approach“-> gene families
• „Ariad Pharmaceuticals“
Successful in finding inhibitors for Src
Pharmaceutical companies
• „Triad Therapeutics“
Biligand enzymes
Druglike mimic for the cofactor
Enzyme inhibitors
Nelfinavir
Amprenavir
Enzyme inhibitors
Zanamivir (Relenza)
Outlook
• Presently only a few drugs on market
• Availability of X-ray derived information is increasing
• Advances in structural genomics and bioinformatics
Sources of information
• „The process of structure-based drug Design“-Amy C. Anderson, Chemistry & Biology, Vol. 10, 787-797, September 2003
• „Structure-based drug Design“-Celia M. Henry, Science & Technology, June 4, 2001, Vol. 79, Number 23
• “Application and Limitations of X-ray Crystallographic Data in Structure-Based Ligand and Drug Design”-Andrew M. Davis,* Simon J. Teague, and Gerard J. Kleywegt, Angewandte Chemie, Ed. 2003, 42, 2718-2736
• „A virtual space odyssey“-Cath O´Driscoll, Charting chemical space, May 2004
• The structures of life, CHAPTER 4: Structure-Based Drug Design: From the Computer to the Clinic http://www.nigms.nih.gov/news/science_ed/structlife/chapter4.html
• “Disarming Flu Viruses” By W. Graeme Laver , Norbert Bischofberger and Robert G. Webster, January 06, 1999 http://www.sciam.com/print_version.cfm?articleID=00023064-8039-1CD6-B4A8809EC588EEDF