ryan m harrison, jeffrey j gray
DESCRIPTION
Prediction of pK a shifts in proteins using a discrete rotamer search and the Rosetta energy function. Ryan M Harrison, Jeffrey J Gray. Baltimore Polytechnic Institute Johns Hopkins University, Department of Chemical & Biomolecular Engineering. pH has profound effects on proteins. - PowerPoint PPT PresentationTRANSCRIPT
Prediction of pKa shifts in proteins using a discrete rotamer search and the Rosetta
energy functionRyan M Harrison, Jeffrey J Gray
Baltimore Polytechnic Institute
Johns Hopkins University, Department of Chemical & Biomolecular Engineering
Influenza Hemagglutinin protein
Conformational Change
Catalytic activity
Binding affinity
Stability
Red: pH-sensitive region of hemagglutinin
pH has profound effects on proteins
Harrison RM 2005
Rosetta Algorithm
Protein Folding
Protein Docking
Protein Design
Harrison RM 2005
Objective
Improve computational protein structure predictions by describing how proteins react to different pH environments DevelopDevelop and implement pH-sensitive modeling in Rosetta
PredictPredict pKa shifts in several model proteins
ModelModel pH-sensitive docking and folding
DesignDesign a protein with pH-sensitive activity Harrison RM 2005
Why model pH in Rosetta?
More accurate predictions…More accurate predictions… Enhanced description of protein energy landscape
More physically relevant protein electrostatics, especially __buried charges
Extended Capabilities…Extended Capabilities… Predict pH-sensitive conformational changes
Sidechain, Backbone, Rigid Body (?)
Predict docking and folding pH-optimums
Design novel pH-sensitive motifs and functions
Harrison RM 2005
Develop the framework
Harrison RM 2005
Improve computational protein structure predictions by describing how proteins react to different pH environments DevelopDevelop and implement pH-sensitive modeling in Rosetta
PredictPredict pKa shifts in several model proteins
ModelModel pH-sensitive docking and folding
DesignDesign a protein with pH-sensitive activity
pKa: The pH at which an amino acid equally occupies its protononated and deprotonated states
pKa shifts
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pH titration (Idealized)
IpKapKa pKa shift
:[ ] [ ]apK pH if HA A
Methodology
localG localG
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Procedure
Allow Rosetta to dynamically select most favorable amino acid protonation state
1. Introduce an energy function for protonation:
2. Allow Rosetta to sample alternate protonation states
3. Modify amino acid parameters for each state
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( ) ln10solutionprotonation aG zRT IpK pH
+
+
10.4aIpK
Rosetta Score Functions
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ε : energy well depth σij : atomic radii sums rij : interatom distanceGray JJ, et al. 2003 J. Mol. Biol.
12 6
12 62ij ijvdw
ij ijij ij
Gr r
van der Waals (Lennard-Jones 6-12 Potential)
ε : di-electric (ε = rij) q : atomic partial chargeWarshel A, Russel ST 1984 Quar. Rev. Bio. Phys.
332 i jelecij
ij
q qG
r
Electrostatics (Coulombic Distance Dependent di-
electric) Dunbrack RL, Cohen FE 1997 Protien Sci.
log ( | )duni i i
i
G P rot
Torsion Energies (Dunbrack rotamer frequencies)
Kortemme T, et al. 2003 J. Mol. Biol.1
ln( )hbondi
i
G kT hbprob
Hydrogen Bonding
(Orientation Dependent)
: Reference solvation free energy Lazaridis T, Karplus M 1999 Proteins: Struct. Funct. Genet.
j
ij
ijirefi
slvi VrfGG
)(
refiG
Solvation (Implicit Gaussian solvent-exclusion
model)
Predict pKa shifts
Harrison RM 2005
Improve computational protein structure predictions by describing how proteins react to different pH environments DevelopDevelop and implement pH-sensitive modeling in Rosetta
PredictPredict pKa shifts in several model proteins
ModelModel pH-sensitive docking and folding
DesignDesign a protein with pH-sensitive activity (?)
Model Systems
Turkey Ovomucoid Inhibitor (OMTKY3)
Ribonuclease A (RNaseA)
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Ribonuclease A
1:[ ] [ ]apK pH if HA A
pKa shift
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Turkey Ovomucoid Inhibitor
Rosetta predicts pKa shifts with 0.77 root mean squared (rms) accuracy
Red: Rosetta Prediction, Green: Experimental, Gray: IpKa (Null Value)
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Turkey Ovomucoid Inhibitor
CPK: Prediction, Green: Experimental
Rosetta under shifted pKa’s
ASP27
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LYS29
Ribonuclease A
Rosetta predicts pKa shifts with 0.62 rms accuracy
Red: Rosetta Prediction, Green: Experimental, Gray: IpKa (Null Value)
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Model rms εprotein
IpKa 0.95
Rosetta 0.62ε=r
SCCE 2.69 4
MCCE 0.99 4
MCCE 0.66 8
MCCE 0.44 20
Ribonuclease A
HIS12
CPK: Prediction, Green: Experimental
Rosetta predicted pKa preciselyHarrison RM 2005
Ribonuclease A
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ASP 121
ASP 83
Predicted pKa : 3.5
Experiment : 3.5
IpKa : 4.0
Low pH High pH
HIS 119
Conclusions
Rosetta can now estimate the local effects of pH (i.e. pKa shifts) in small globular proteins
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DevelopedDeveloped an approach to model pH
AccountedAccounted for significant pKa shifts using only side-chain movement
ExtendedExtended the modeling capabilities of Rosetta
IncreasedIncreased the overall accuracy of Rosetta(?)
Work in Progress
Optimization and calibration on a set of over 200 experimentally determined pKa shifts from 15 proteins
pH-sensitive Docking and Folding
Scientific and performance benchmark on 55 pKa’s from staphylococcal nuclease mutants (in collaboration with Garcia-Moreno lab)
Harrison RM 2005
Staph. Nuclease at pH 7.2
-helical nano-gel
pH-sensitive docking
Improve computational protein structure predictions by describing how proteins react to different pH environments DevelopDevelop and implement pH-sensitive modeling in Rosetta
PredictPredict pKa shifts in several model proteins
ModelModel pH-sensitive docking and folding in several model proteins
DesignDesign a protein with pH-sensitive activity (?)
Harrison RM 2005
Acknowledgements
Harrison RM 2005
National Institutes of HealthNational Institute of General Medical Sciences
Gray LabDr. Jeffrey J. Gray
Harden LabDr. James L. Harden
Baltimore Polytechnic Institute
The Ingenuity ProjectMs. Charlotte V. Saylor
Robert M HarrisonSharon A Harrison
Harrison RM 2005
Figure from: M Daily, Pymol
What could proteins do for you?
Drug DesignImagine targeted treatments for devastating diseases…
Blue: antibody, Red: prediction, Green: experimental
Antibody binding to ovine prion.
Rosetta Score Functions: Electrostatics
+
pKa ~ 4.40
Glutamate Partial Charges Lysine Partial Charges
+
pKa ~ 10.40
Electrostatics require electron density parameters
Predictions were made using both a Generalized Born (GB) and Coulombic electrostatic model.
GB electrostatics are more accurate than Coulombic electrostatics, but also more computationally expensive
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Rosetta Procedural Detail
Low Resolution Monte Carlo
Start Position
High-Resolution Refinement*
10n
Post-Processing*
Predictions*
Low Resolution _1. Rigid Body Move _ _2. Monte Carlo Minimization
High Resolution _1. Sample all side chain positions in ___Dunbrack rotamer set *2. Sample alternate protonation ___state rotamers _ _3. Monte Carlo Minimization
Post-Processing *1. External Scripts to determine side ___chain pKa values
Rosetta Rosetta FlowchartFlowchart
** Modified to introduce pH-sensitive side chain modeling or pKa predictions in RosettaHarrison RM 2005