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Protein structure modelingProtein structure modeling

Department of Biochemistry and

Seaver Foundation Center for Bioinformatics

Albert Einstein College of MedicineNew York, USA

AndrAndrss FiserFiser

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Why is it useful to know the structure of a

protein not only its sequence?

The 3D structure is more informative than sequence because patterns inspace are frequently more recognizable than patterns in sequence

Evolution tends to conserve function and

function depends more directly on structthan on sequence, structure is more

conserved in evolution than sequence.

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Why Protein Structure Prediction?

Y 2005

29,000Structures

2,300,000Sequences

We know the experimental 3D structure for~1% of the protein sequences

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Principles of Protein Structure

GFCHIKAYTRLIMVG

An

abaena7120

Anacystisnidulans

Condruscrispus

Desulfovibriovulgaris

Ab initio prediction Fold Recognition

Com arative Modelin

folding evolution

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Protein structure modeling

Ab initio prediction Comparative Modeling

pplicable to any sequence

ot very accurate (>4 Ang RMSD),

ttempted for proteins of

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A small difference in the sequence makes a small

ifference in the structure

I Protein structures are clustered into fold families

a ma es compara ve mo e ng poss e

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Structural Genomics

The number of families is

much smaller than the numberof proteins

haracterize most protein sequences (red) based on related

nown structures (green).

S G

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Structural Genomics

efinition: The aim of structural genomics is to put every protein sequence withinmodeling distance of a known protein structure.

ize of the problem:

There are a few thousand domain fold families.There are ~20,000 sequence families (30% sequence id).

olution:Determine protein structures for as many different families as possible.

Model the rest of the family members using comparative modeling

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Comparative Protein Structure Modeling

COMPARATIVE

MODELING

0 (100)2 (50) 1 (80)

Ca RMSD (% EQV)

20 50 100

Anabaena 7120

Anacystis nidulans

Condrus crispus

Desulfovibrio vulgaris

Clostridium mp.

KIGIFFSTSTGNTTEVA

Flavodoxinfamily

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teps in Comparative Protein Structure Modeli

MSVIPKRLYGNCEQTSEEAIRIEDSPIV---TADLVCLKIDEIPERLVGE

ASILPKRLFGNCEQTSDEGLKIERTPLVPHISAQNVCLKIDDVPERLIPE

ASILPKRLFGNCEQTSDEGLK

IERTPLVPHISAQNVCLKIDD

VPERLIPERASFQWMNDK

TARGET TEMPLATE

No

Target TemplateAlignment

Model Building

START

Template Search

OK?

Model Evaluation

ENDYes

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Steps in Comparative Protein Structure Modeling

No


Model Building

START

Template Search

OK?

Model Evaluation

END

Yes

Pattern recognition, heuristic searches

(e.g. BLAST, FastA)

Profile and iterative alignment methods(e.g. HMMs, PSI-BLAST)

Structure based threading

(e.g. THREADER, FUGUE, 3DPSSM)

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No


Model Building

START

Template Search

OK?

Model Evaluation

END

Yes

Dynamic Programming, Pairwise Alignme

Multiple Alignments, Profiles, HMMs Structure based approaches (Threading)

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No


Model Building

START

Template Search

OK?

Model Evaluation

END

Yes

Rigid Body Assembly (COMPOSER)

Segment Matching (SEGMOD, 3DPSSM)

Satisfaction of Spatial Restraints (MODELLE

Integrated (NEST)

loop modeling, side chain modeling

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teps in Comparative Protein Structure Modelin

No


Model Building

START

Template Search

OK?

Model Evaluation

END

Yes

Stereochemistry (PROCHECK, WHATCHE

Environment (Profiles3D, Verify3d)

Statistical potentials based methods (PROS

Is the model reliable?

A model is reliable when it is based on a

correct template and on an approximatelycorrect alignment.

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Typical Errors in Comparative Models

Distortion in correctly

aligned regionsRegion without a

template Side chain packing

Incorrect template

MODELX RAYTEMPLATE

Misalignment

mpar ng accurac es o exper men a an eore ca approac

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mpar ng accurac es o exper men a an eore ca approac

Some Models Can Be Surprisingly Accurateome o e s an e urpr s ng y ccurate

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24 sequence identity

YJL001W1rypH

25 sequence identityYGL203C

1ac5

Ser 176

His 488

Asp 383

Some Models Can Be Surprisingly Accurateome o e s an e urpr s ng y ccurate(in Some Regions)(in Some Regions)

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in Zebrafish forkhead transcription factor Foxi1

RMSD

re-modelled wild type segments(6 and 7aa) and NMR: 1.78 and 1.82modelled mutated segments with each other (6 and 7aa): 1.19

wild type and mutated segments (6 and 7 aa): 3.65 and 3.75

ere su un commun ca on n su am es o ases

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phila m. H. sapiens

li Eq. inf. virus

Predicting features that are not present in the template

1. Active form usually is a trimer,each active site is formed by all threemonomers.

2. Comparison of models and X-raystructures reveals two subclasses

of dUTPases with different type of

subunit interfaces.

3.Altered character of subunitinterfaces correlates with the

suggested different functional

mechanism: polar/charged surface

is better adjusted for allosterism.

ere su un commun ca on n su am es o ases

Convergent evolution of Trichomonas vaginalis lactate

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Designing new enzyme specificity with the aid of comparative models

1. Sequences are identi

from the Trichomona

genome project

2. Mutations were

designed using the

constructed 3D mode

to switch specificity.

Convergent evolution of Trichomonas vaginalis lactatedehydrogenase from malate dehydrogenase.

Core histones of the amitochondriate protist Giardia lambli

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Confirming fold by energy evaluation of comparative model

-5.23/-4.42-2.74/-2.39-3.98/-4.05-5.41/-5.09X-ray

-4.79-0.26-2.82-2.29H4

-0.41-2.38-0.61-1.35H3

-1.70-0.41-4.34-1.15H2B

-2.77-0.64-3.42-4.74H2A

1aoiB/F1aoiA/E1aoiD/H1aoiC/GG.Lamblia

Core histones of the amitochondriate protist, Giardia lambli

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