Protein Structure Prediction - PowerPoint Presentation

Slide1

Protein Structure PredictionSlide2

Why do we want to know protein structure?

Classification

Functional PredictionSlide3

What is protein structure?

Primary - chains of amino acids

Secondary - interaction between groups of amino acids

Tertiary - the organization in three dimensions of all the atoms in a polypeptide

Quaternary - the conformation assumed by a multimeric proteinSlide4

Proteins are chains of amino acids joined by peptide bonds

The N-C



-C sequence is repeated throughout the protein, forming the backbone

The bonds on each side of the C



atom are free to rotate within spatial constrains,

the angles of these bonds determine the conformation of the protein backbone

The R side chains also play an important structural role

Polypeptide chain

The structure of two amid acids

Primary StructureSlide5

Interactions that occur between the C=O and N-H groups on amino acids

Much of the protein core comprises



helices and



sheets, folded into a three-dimensional configuration:

- regular patterns of H bonds are formed between neighboring amino acids

- the amino acids have similar angles

- the formation of these structures neutralizes the polar groups on each amino acid

- the secondary structures are tightly packed in a hydrophobic environment

- Each R side group has a limited volume to occupy and a limited number of interactions

with other R side groups



helix



sheet

Secondary StructureSlide6



helix



sheet

Secondary StructureSlide7

Other Secondary structure elements

(no standardized classification)

- loop

- random coil

- others (e.g. 3

10

helix, -hairpin, paperclip)

Super-secondary structure

- In addition to secondary structure elements that apply to all proteins

(e.g. helix, sheet) there are some simple structural motifs in some proteins

- These super-secondary structures (e.g. transmembrane domains, coiled

coils, helix-turn-helix, signal peptides) can give important hints about

protein function

Secondary StructureSlide8

Structural classification of proteins (SCOP)

Class 1:

mainly alpha

Class 4:

few secondary structures

Class 2:

mainly beta

Class 3:

alpha/beta

ClassificationSlide9

Alternative SCOP

Class



:

only



helices

Class



:

antiparallel

 sheets

Class

/

 : mainly

 sheetswith intervening 

helices

Class

+



:

mainly

segregated



helices with

antiparallel



sheets

Membrane structure:

hydrophobic



helices with

membrane bilayers

Multidomain:

contain

more than one class

More ClassificationSlide10

Q: If we have all the Psi and Phi angles in a protein, do we then have enough

information to describe the 3-D structure?

Tertiary structure

A: No, because the detailed packing of the amino acid side chains is not

revealed from this information. However, the Psi and Phi angles do

determine the entire secondary structure of a protein

Protein Structure ReviewSlide11

Secondary-Structure Prediction Programs

* PSI-

pred

*

JPRED

Consensus prediction (includes many of the methods given

below)

* DSC * PREDATOR

* PHD * ZPRED

* nnPredict * BMERC PSA

* SSPSlide12

The

tertiary structure

describes the organization in three dimensions of all the atoms in the polypeptide

The tertiary structure is determined by a combination of different types of bonding (covalent bonds, ionic bonds, h-bonding, hydrophobic interactions, Van der Waal’s forces) between the side chains

Many of these bonds are very week and easy to break, but hundreds or thousands working together give the protein structure great stability

If a protein consists of only one polypeptide chain, this level then describes the complete structure

Tertiary StructureSlide13

Proteins can be divided into two general classes based on their tertiary structure:

-

Fibrous proteins

have elongated structure with the polypeptide chains arranged

in long strands. This class of proteins serves as major structural component of cells

Examples: silk, keratin, collagen

-

Globular proteins

have more

compact, often irregular structures.

This class of proteins includes most

enzymes and most proteins involved

in gene expression and regulation

Tertiary StructureSlide14

The

quaternary

structure

defines the conformation assumed by a multimeric protein.

The individual polypeptide chains that make up a multimeric protein are often referred to

as

protein subunits

. Subunits are joined by ionic, H and hydrophobic interactions

Example:

Haemoglobin

(4 subunits)

Quaternary StructuresSlide15

Common displays are (among others)

cartoon

,

spacefill

, and

backbone

cartoon

spacefill

backbone

Structure DisplaysSlide16

Software

RasMol

Cn3D

Jmol (Chime)Slide17

Classic Approach to Determining Structure?

Determine

biochemical

and cellular

role of protein

Purify protein

Experimentally

determine

3D structure

Clone cDNA

encoding

protein

Obtain protein

By expression

Infer function,

mechanism of

actionSlide18

Structural Genomics Approach?

genomic

DNA

sequences

predict

protein-

coding

genes

Obtain protein

by expression

Obtain protein

In silico

Experimentally

determine

3D structure

Predict

3D structure

Determinebiochemical

andcellular roleof protein

homology searches (PSI-BLAST)Slide19

3-D macromolecular structures stored in databases

The most important database: the Protein Data Bank (PDB)

The PDB is maintained by the Research Collaboratory for Structural Bioinformatics (RCSB) and can be accessed at three different sites (plus a number of mirror sites outside the USA):

- http://rcsb.rutgers.edu/pdb (Rutgers University)

- http://www.rcsb.org/pdb/ (San Diego Supercomputer Center)

- http://tcsb.nist.gov/pdb/ (National Institute for Standards and Technology)

It is the very first “bioinformatics” database ever build

Sources of Protein Structure Information?Slide20

Researches have been working for decades to develop procedures for predicting protein structure that are not so time consuming and not hindered by size and solubility constrains.

As protein sequences are encoded in DNA,

in

principle

, it should therefore be possible to translate a gene sequence into an amino acid sequence, and to

predict the three-dimensional structure of the resulting chain from this amino acid sequence

Computational Modeling

Structural PredictionSlide21

How to predict the protein structure?

Ab initio

prediction of protein structure from sequence:

not yet

.

Problem: the information contained in protein structures lies essentially in the

conformational torsion angles. Even if we only assume that every amino-acid residue

has three such torsion angles, and that each of these three can only assume one

of three "ideal" values (e.g., 60, 180 and -60 degrees), this still leaves us with 27

possible conformations per residue.

For a typical 200-amino acid protein, this would give 27

200

(roughly 1.87 x 10

286)possible conformations!

If we were able to evaluate 10

9

conformations per second, this would still keep us busy 4 x 10259 times the current age of the universe

There are optimized

ab initio

prediction algorithms available as well as fold recognition algorithms that use

threading

(compares protein folds with know fold structures from databases), but the results are still

very poor

Q: Can’t we just generate all these

conformations, calculate their energy

and see which conformation has the

lowest energy?

Computational ModelingSlide22

Homology (comparative) modeling

attempts to predict structure on

the strength of a protein’s sequence similarity to another protein of known

structure

Basic idea:

a significant alignment of the query sequence with a target sequence from PDB is evidence that the query sequence has a similar 3-D structure (current threshold ~ 40% sequence identity). Then multiple sequence alignment and pattern analysis can be used to predict the structure of the protein

Homology ModelingSlide23

Computational modeling: summary

Partial or full sequences

predicted through gene

finding

Similarity search

against proteins

in PDB

Alignment can be used to position the

amino acids of the query sequence in

the same approximate 3-D structure

Find structures that have a significant

level of structural similarity (but not

necessarily significant sequence similarity)

If member of a family with a

predicted structural fold,

multiple alignment can be used

for structural modeling

Infer structural information (e.g.

presence of smallamino acid motifs; spacing and arrangement of

amino acids;

certain typical

amino acid combinations

associated with certain types of secondary structure)

can provide clues as to the presence of active sites and

regions of secondary structure

Structural analyses in the lab

(X-ray crystallography, NMR)

How do we

do this?Slide24

3D Comparative Modeling

Profile Methods - match sequences to folds by describing each fold in terms of the environment of each residue in the structure

Threading Methods - match sequences to structure by considering pairwise interactions for each residue, rather than averaging them into an environmental class

HMM Methods - the equivalent state corresponds to one structurally aligned position in a structural fold, including gapsSlide25

Structural HMM