IV. Protein Structure Prediction and Determination

• Methods of protein structure determination

• Critical assessment of structure prediction

• Homology modelling

• Threading

• Prediction of novel folds

• Protein design

Methods to determine protein structure

• X-Ray and NMR methods allow to determine the structure of proteins and protein complexes

• These methods are expensive and difficult– Could take several work months to process one

proteins

• A centralized database (PDB) contains all solved protein structures– XYZ coordinate of atoms within specified precision– ~19,000 solved structures

X-ray crystallography and NMR are the two major techniques for determining protein structures

Protein isolation

Protein Purification

Protein Crystallisation

X-ray crystallography:

Crystal

X-ray

Phases of diffracted rays

Electron density

Protein model

Liquid nitrogen is used to freeze the crystal which allows for increased reliability of information gathered from testing. The area detector, which collects the diffracted x-rays once they pass through the crystal, is the black plate located behind the nitrogen stream, (right) sample x-ray diffraction pattern.

X-ray crystallography

The phase problem:

Isomorphous Replacement: combination of diffraction data from the native crystal with data from other crystals containing the same protein packed in the same way but adding a heavy atom

Molecular Replacement: placement of a known relative structure in different positions and orientations, providing approximate phases

Multiwavelength Anomalous Dispersion: Measurements of the variation of the intensity distribution in the diffraction pattern over a range of wavelengths

Direct Methods: Knowledge of electron density distributions in crystals permits calculation of phases directly from experimental data

Phase determined

Model built over itExperimental data:

Three dimentional coordinatesRelative mobility of atoms

Refinement of the model comparing with empirical data

Optimised protein structure

Limitations

• An extremely pure protein sample is needed.

• The protein sample must form crystals that are relatively large without flaws. Generally the biggest problem.

• Many proteins aren’t amenable to crystallization at all (i.e., proteins that do their work inside of a cell membrane).

X-ray crystallography

Measures of structural quality

R-factor is a measure of how well the model reproduces the experimental intensity data, the lower this factor the better the structure.

R = 0% There is no experimental error (ideal)

R = 60% Atoms placed randomly in the crystal

R 20 Good structure prediction

The free R-factor is an unbiased measure of the agreement between the model and a subset of experimental data withheld during the refinement process

Good protein structures:

1. Are compact as measured by their surface area and packing density

2. Have hydrogen bonds with a reasonable geometry, and with all the hydrogen bonds determined

3. Their backbone conformation angles are confined to the allowed areas of the Sasikharan-Ramakrishnan-Ramachandran diagram

Nuclear Magnetic Resonance

Nuclear magnetic resonance (NMR) spectra measure the energy level of the magnetic nuclei in atoms

This energy depends on the effect transmitted between atoms affecting the precise frequency of the signal from an atom (chemical shift). This chemical shift can define secondary structures

NMR can determine the value of conformational angles

Interactions between spatially proximal atoms (< 5Å) can be used by NMR to determine the closeness of atoms in the structure (Nuclear Overhauser effect (NOE)

Peaks correspond to the interaction of pairs of atoms

The spectroscopists has first to correlate peaks with amino acids in the sequence (Assign the spectrum)

The data generated provide a set of distance constraints and determine the secondary structure and some indications of the tertiary interactions

• Solving an NMR structure means producing a model or set of models that manage to satisfy all known NMR distance constraints (generated by the experiment).

• NMR models are often released in groups of 20-40 models because the solution to NMR structure determination is much more ambiguous than x-ray.

• NMR is limited to small, soluble proteins only.

Nuclear Magnetic Resonance

Sample

RMN spectra

Spectra procession

Sequential assignation

Conformational restrictions

3D structure calculation

Refinment

Analysis

Nuclear Magnetic Resonance

NMR models An X-Ray liquid crystal

NMR vs. X-ray crystallography

Protein Structures

• in theory, a protein structure can solved computationally

• a protein folds into a 3D structure to minimizes its potential energy

• the problem can be formulated as a search problem for minimum energy– the search space is defined by psi/phi angles of backbone and side-chain

rotamers– the search space is enormous even for small proteins!– the number of local minima increases exponentially of the number of residues

Protein Structure Prediction

• ab initio folding methods– use first principles to computationally fold proteins– not practical (yet) due to its high computational complexity

• Comparative modeling– Protein threading – make structure prediction through

identification of “good” sequence-structure fit

– Homology modeling – identification of homologous proteins through sequence alignment; structure prediction through placing residues into “corresponding” positions of homologous structure models

Protein Threading

• the basic idea

– placing a protein sequence onto a structural template “optimally”

– assessing how good the structure is energetically

• key components:

– a structural template database

– an “energy” function for measuring quality of a placement (alignment)

– an algorithm for finding an optimal placement

– a capability for assessing the reliability of prediction

query sequenceMTYKLILNGKTKGETTTEAVDAATAEKVFQYANDNGVDGEWTYTE

template set

PROSPECT Predictions

actual predicted actual

actual actual

predicted

predicted predicted

t49

t68

t57

t70

How and Why Threading?

The idea of threading came from the observation that most of the proteins adopt one of a limited number of folds:

Just 10 folds account for the 50% of similarities between protein superfamilies

Rather than trying to predict the correct structure from the unlimited number of possible structures, the protein structure might have been surely determined before for other proteins

In case that our protein shares obvious similarity with other protein with a known 3D structure the folding problem is trivial

It is desired, however, that threading might be able to detect structural similarities that are not accompanied by any detectable similarity

1. Library of protein structures (fold library)all known structuresrepresentative subset (seq. similarity filters) structural cores with loops removed

2. Binary alignment algorithm with Scoring functioncontact potentialenvironmentsInstead of aligning a sequence to a sequence, align strings of descriptors that represent 3D structual features.Usual Dynamic Programming: score matrix relates two amino acidsThreading Dynamic Programming: relates amino acids to environments in 3D structure

3. Method for generating models via alignments

Algoritmos de threading. General.

ALMVWTGH.........

................

Threading AlgorithmsPuntuation function

ALMVWTGH.........

................

-Amino acids are in similar environments to those where known structures are found

- Solvatation potentials

-Contact potentials

-Coincidence of predicted and real secondary structures and calculation of accessibilities

-Homology matrices obtained from alignment of structures

- HMMs

Count pairs of each residue type at different separations

Threading algorithmsContact potential

Energy of interaction = -KT ln (frequency of interactions) Boltzmann principle

d

Eco

unts

d

Jones, 1992; Sippl, 1995

Threading algorithmsSequence profiles + secundary structure

Kelley et al., 2000http://www.bmm.icnet.uk/~3dpssm

threading. Examples

threading. Examples

threadingPost-processing of the results

Combining with additional information

De Juan et al., 2001

threadingPost-processing of the results

Filtering models

threadingEvaluation of methods

I) CASP 94, 96, 98, 00, 02

DatabasesAlgorithm

Computer evaluation

MA

KE

FG

IPA

AV

AG

TV

LN

VV

EA

GG

WV

TT

IVS

ILT

AV

GS

GG

LS

LL

AA

AG

RE

SIK

AY

LK

KE

I K

KG

KR

AV

IAW

1/3 correct fold (ali?)

MODEL(S)

EVALUATION

http://PredictionCenter.llnl.gov/casp4/

PROSPECT Predictions

actual predicted actual

actual actual

predicted

predicted predicted

t49

t68

t57

t70

Why engineer proteins?

• 1) Engineered macromolecules could have experimental use as experimental tools, or for development and production of therapeutics

• 2) During the process of said engineering, new techniques are developed which expand options available to research community as whole

• 3) By approaching macromolecule as engineer, better understanding of how native molecules function

(Doyle, Chem & Bio, 1998)

Ligand Binding – protein flexibility“In this study, we set out to elucidate the cause for the discrepancy in affinity of a range of serine proteinase inhibitors for trypsin variants designed to be structurally equivalent to factor Xa.”(Rauh, J. Mol. Biol., 2004)

Def: Ligand

Any molecule that binds specifically to a receptor site of another molecule; proteins embedded in the membrane exposed to extracellular fluid.