new strategies for protein folding joseph f. danzer, derek a. debe, matt j. carlson, william a....

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New Strategies for Protein Folding h F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Godda Materials and Process Simulation Center California Institute of Technology

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Page 1: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

New Strategies for Protein Folding

Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III

Materials and Process Simulation CenterCalifornia Institute of Technology

Page 2: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

…-HIS-CYS-ALA-ALA-GLY-GLU-ASP-...

Protein Tertiary Structure Prediction

Given a Protein’s Primary Structure -- Amino Acid Sequence

Can We Determine It’s 3D Structure

What Local Structural Units Does It Form?-Helix (Cylinder)-Sheets (Ribbon)

How Do Those Structural Units Pack Together?

Page 3: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

With a 6 () state representation,

650 or 1038 states for a 50 residue protein

Assuming protein may sample 1state/ps,

1019 years to fold

•Conformational Search Problem

–Given the exponentially large number of possible states, how do we generate a correct state?

•Recognition Problem

–How do we differentiate correct from incorrect folds?

Structure Prediction is a Two Fold Problem

Page 4: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

Restrained Generic Protein (RGP)Direct Monte Carlo

Highly efficient, off-lattice residue buildup procedurefor generating ensembles of protein conformations that comply with a set of user defined distance restraints.

l

l = 3.8Å; = 120; Typically = 0, 60, 120, 180, 240, 300. (6 states per residue)

Generic Protein Model•Each residue is a 5.5 Å sphere•Fixed geometry connects residues

Page 5: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

Restraint Implementation

i-1 i

i+4

i+4

i+4

i+4

i+4

i+4i+4

i+4

i+4

i+4

i+4

z

r

At residue addition step i, the maximal position ofresidue i+n in the (z,r) plane is known.

Satisfies pairwiserestraints with>90% efficiencywith negligiblecomputational cost.

Leads to a simple set of trigonometric conditions for restraint satisfaction.

Page 6: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

RGP EnsembleGeneration

Inter-residuerestraints

Secondarystructure

prediction

Static Residue BurialSelection

<10 4 topologies

<500 topologies

Intact PeptideBackbone

DynamicResidue Burial

Selection

AdditionalRestraints

<20 topologies

AdditionalRefinement

<10 topologies

<5 topologies

Amino AcidSequence

Generate-and-Select Hierarchy

Local StructureRefinement

Page 7: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

RGP Ensemble Selected Set Sec. PredictionSa CRMSb sc Rankd CRMSe Rankf CRMSg

N/36 30,0000 6.85Å 395 24t 7.46Å 14t 6.67Å

N/24 5,000 6.57Å 209 6t 6.76Å 2t 6.11Å

N/12 500 6.28Å 271 1 6.43Å 7t 4.45Å

N/6 - - 44 2 6.13Å 1t 5.76Å

Secondary Structure Prediction-PHDBurkhard Rost & Chris Sander, J. Mol. Biol. 232, 584 (1993).

LexA Repressor

Page 8: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

RGP Ensemble Selected Set Sec. PredictionS CRMS s Rank CRMS Rank CRMS

N/12 50,000 8.95Å 117 11 8.77Å 5 7.01Å

N/6 - - 23 1 9.28Å 1 6.30Å

Myoglobin

Page 9: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

Inter-Residue Restraints

If tertiary structure is unknown, How can we generate distance restraints?•Experimentally determined disulfide bond connectivity•Use PHD prediction algorithm to generate loose restraints1

1. Burkhard Rost & Chris Sander, J. Mol. Biol. 232, 584 (1993).

PHD predicts whether each residue will be buried or exposed to solvent•Assume the residues with greatest burial form a hydrophobic core•Generate a few loose restraints (4-10 Å) between these residues

Tests on two proteins (3icb,1lea) using loose restraints were done

Protein # Restraints EnergyCut-Off

# SelectedStructures

# NearNative

BestCRMS

3icb 3 -26 463 4 7.7871 -23 460 2 7.827

1lea 3 -27 172 1 8.3008* -18 2242 1 8.4847** -30 110 3 7.001

-27 330 8 7.001*All restraints were picked so that they were incorrect**All restraints were picked so that they were correct

Page 10: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

Local Structure Refinement

•Dynamic Monte Carlo–Make small local deformations to the backbone structure–Overall topology must be kept intact –Use simple energy function to determine if deformation is accepted or rejected

•Fragment Sewing–Isites1 library is a database of structural fragments widely observed in the Protein Data Bank.–Based on sequence homology, Isites will generate a list of fragments whose structures are likely to be found in the protein–Local structure can be refined by sewing these fragments into the overall structure

1. C. Bystroff & D. Baker, J. Mol. Bol. 281, 565 (1998).

Page 11: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

Dynamic Monte Carlo

Local deformations are made by modifying the position of a single residue.

Energy function properly orients side chains. Hydrophilic groups point outward

and hydrophobic groups point inward.

Axis of rotation

Circle defines allowed movement based on fixed geometry of model

C- AtomsHydrophilic Side ChainHydrophobic Side Chain

Page 12: New Strategies for Protein Folding Joseph F. Danzer, Derek A. Debe, Matt J. Carlson, William A. Goddard III Materials and Process Simulation Center California

Fragment Sewing

Rest of protein

Segment’s original structure

New structure after sewing

Overall topology is still intact, but now local structure has -helical structure rather than a random coil.