dill et al, 2007 the protein folding problem when will it be solved?

Dill et al, 2007

The Protein Folding ProblemWhen will it be solved?

What is protein folding?

Why is it a problem?

What are some approaches to understanding it?

How far have we come?

What does the future hold?

Protein folding is how an amino acid sequence (a polypeptide) folds into its native structure.

A native structure is the functional form of a protein.

The overall protein folding problem is to understand the

relationship between amino-acid sequence and protein structure.

The protein design problem is to synthesize a stable amino-acid

sequence towards a target conformation.

Three ‘Easy’ Pieces

• Understanding how inter-atomic forces contribute to a protein’s native structure.What is the driving force behind protein folding? Does understanding the problem have other levels of applicability?

• Prediction of native structure from a given amino acid sequence.Can we input a polypeptide sequence and output the ‘correct’ protein? How accurate would this simulation be?

• The kinematic question of folding speedJust how do proteins fold so fast? Can we attain this speed and accuracy with synthetic, de novo proteins?

Piece OneUnderstanding Folding

• Before mid-1980s, overall folding process was seen as sum of small, local interactions.Like hydrogen-bonds, van der Waal’s interactions, ion pairs.

• Statistical mechanical modeling after mid-80s changed this view.• Big component is reducing exposed hydrophobic sidechains. I.e.,

non-local interactions are the ‘driving force’.• Folding process is distributed locally and non-locally• Free Energy Equation

• Effects of cytosol cannot be ignored.• Composition (solvent, other macromolecules, pH)• Temperature

Hydrophobic Interactions

What is the applicability?

• Design of foldamersSynthetic molecules which mimic folding ability of proteins (e.g. peptoids in pharmaceutics)

• Design of lung surfactant replacements• Cytomegalovirus inhibitors• Antimicrobials• siRNA delivery agents• Synthetic proteins from “broadened

alphabets”

Piece TwoAb initio Structure Prediction

• Long-standing goal.Amino-acid sequence in → 3-D Native Structure out

• Makes drug discovery faster.Simulate drug interactions without costly studies.

• Makes it cheaper.Replace experimental structural determination with accurate computer simulation.

Bioinformatics-based approach

CASP

• Critical Assessment of Techniques for Structure Prediction (Moult, 1994)

• Social experiment• Prediction of native state from amino-acid

sequence alone• Approaches are homology modeling and

protein threading

• Use only the laws of Physics to model folding processes and resulting native structures.

• Aim to not use statistical energy functions or secondary structure predictors.Like Homology Modeling, Protein Threading.

• Now being combined with some database information.

Physics-based approach

• Can predict conformational changesInduced-fit theory: important in computational drug discovery

• Predict conformational transitionsMaybe those based on environmental factors

• Design synthetic proteinsFoldable polymers for non-biological backbones

Physics-based approach – Advantages

Induced-fit theory

• Inaccuracies in “force-fields”

• Really, really high computational requirementsAt least right now

Physics-based approach – Problems

Empirical Force-Fields

Physical time for simulation 10-4 Seconds

Typical time-step size 10-15 Seconds

Number of MD time steps 1011

Atoms in a typical protein and water simulation 32,000

Approximate number of interactions in force calculation 109

Machine instructions per force calculation 1000

Total number of machine instructions 1023

Planned supercomputer capacity in 2009: 1 petaflop 1015

Computational Cost

One year to simulate folding of small proteinapproximately…

Recent Advances

• 36-residue villin folded in 1μs– Explicit solvent, initially unfolded– Duan, Kollman (1998)– 4.5A RMSD

• 20-residue Trp-cage folded in 92ns– Implicit solvent– Around 1A RMSD

• Folding@Home folded villin to 1.7A RMSD

Root Mean Square Deviation

If molecular orientation changes in arbitrary way, lRMSD or Least RMSD is used to find optimal alignment using the Kabsch Algorithm or

Quaternions

Problem ThreeUnraveling Folding Kinematics

Some important ideas

• Afinsen’s Paradigm (1957)All the information required to make a 3-D native structure is contained in the amino-acid sequence

• Levinthal’s Paradox (1968)If a protein sampled all possible conformations, time to reach ‘correct’ one would be more than age of universe

• Protein Sequence SpaceWith 20 amino acids as ‘alphabet’, how many theoretical proteins are possible? What about evolution?

• Baldwin ConjectureUnderstanding protein folding can lead us to devise better algorithms to predict native structures from amino-acid sequences

Folding speed

• Two decades ago, could not measure anything faster than few milliseconds.

• Technology exists now.– Laser temperature-jump methods– Mutational methods to identify amino-acids

controlling folding speed– Förster resonance energy transfer (FRET) methods to

‘watch’ formation of contacts– Hydrogen-exchange methods to ‘see’ structural

events– Extensive studies on protein models

Cytochrome c, barnase, chymotrypsin inhibitor 2

Now what about Levinthal’s speed principle?

What we know

• Folding does not happen in a single microscopic pathway– “Funnel-shaped” landscapes– Going from non-native state to native state is

different for each conformation of same sequence

• Folding processes are heterogenous– Observations see averages and not distributions,

variations

What we don’t know

• How do folding rates change with specific mutations?

• How to characterize kinetic heterogeneity?– Single-molecule experiments• Master-equation theories

What about Baldwin’s Conjecture?

Question

• How to design simulations which can arrive at native state faster and more accurately than Monte Carlo or molecular dynamics?Need to know microscopic folding routes

A possible answer

• Zipping and Assembly (ZA)– Proteins do not reach all their degrees of freedom

at the same time– Fold over a range of timescales.– Fast timescale (nano to pico): Small peptide pieces

explore conformations independently. – Formed local structure “zips”, includes more

surrounding chain.– Further assembly on slower timescale.

Does it work?

• ZA speeds up conformational searching.• Physics-only models can find approximately

correct folds for 25-75 monomers.– Ozkan et al, 2006– Used AMBER96 force-field, implicit solvent– Tested 9 proteins from PDB– Eight were within 2.2A (avg.) RMSD

• Gives a good overall sense of folding mechanism

Difficulty

Can we know the conformations the overall protein does not search?Important in understanding proteopathies and hence drug design.

Conclusions

• Sophisticated problem– Protein-protein interactions, cofactors, multi-

domain protein behavior, cytosolic interactions and effects unknown .

• But some headway is being made– Small proteins’ native structures and folding codes

are being determined accurately– What we know is sufficient to design new proteins

and polymers (foldamers)– Good contributions to novel drug discovery and

proteomics

• Good sense of Levinthal’s optimization puzzle

Questionsor

Comments?

Thank you

What happens if a polypeptide does not fold properly?

Structure is related to function

• Resulting protein is rendered biologically, functionally inactive• Simpler forms can be degraded by cell machinery

• Amyloid accumulation (Proteopathies)Alzheimer’s, Parkinson’s

• Can re-fold other normal proteins (Prions)Creutzfeld-Jakob Disease

Sources• http://www3.interscience.wiley.com/journal/66000862/

abstract?CRETRY=1&SRETRY=0

• http://opa.faseb.org/pdf/protfold.pdf

• http://www.biozentrum.unibas.ch/~schwede/Teaching/BixII-SS05/FR-HM.pdf

• http://dasher.wustl.edu/bio5476/reading/curropstrbio-14-76-04.pdf

• http://arxiv.org/ftp/q-bio/papers/0402/0402039.pdf

• http://www.biostat.jhsph.edu/~iruczins/presentations/ruczinski.04.04.retreat.pdf