Feh rj k 4 simon istv n
This presentation is the property of its rightful owner.
Sponsored Links
1 / 18

Fehérjék 4 Simon István PowerPoint PPT Presentation


  • 47 Views
  • Uploaded on
  • Presentation posted in: General

Fehérjék 4 Simon István. Estimate the interaction energy between the residue and its sequential environment. A – 10% C – 0% D – 12 % E – 10 % F – 2 % etc …. Decide the probability of the residue being disordered based on this. Amino acid composition of environ-ment:.

Download Presentation

Fehérjék 4 Simon István

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Feh rj k 4 simon istv n

Fehérjék 4Simon István


Predicting protein disorder iupred

Estimate the interaction energy between the residue and its sequential environment

A – 10%

C – 0%

D – 12 %

E – 10 %

F – 2 %

etc…

Decide the probability of the residue being disordered based on this

Amino acid composition of environ-ment:

Predicting protein disorder - IUPred

  • Basic idea:

    If a residue is surrounded by other residues such that they cannot form enough favorable contacts, it will not adopt a well defined structureit will be disordered

  • The algorithm:

…..QSDPSVEPPLSQETFSDL

WKLLPENNVLSPLPSQAMDDLMLSP

D

DIEQWFTEDPGPDEAPRMPEAAPRVA

PAPAAPTPAAPAPA…..


Predicting protein disorder iupred1

Amino acid composition of the residue D:

Interaction energies:

A – 10%

C – 0%

D – 12 %

E – 10 %

F – 2 %

stb…

97%, that it is disordered

Predicting protein disorder - IUPred

  • Back to p53:

E =

1.16

*0.10

+

(-0.82)

*0

+…

The predicted interaction energy:

=1.138


Predicting binding sites anchor

Predicting binding sites - ANCHOR

  • 3 – Interaction with globular proteins

We consider the average amino acid composition of a globular dataset instead of the own environment:

A – 10%

C – 0%

D – 12 %

E – 10 %

F – 2 %

stb…

A – 7.67%

C – 2.43%

D – 4.92 %

E – 5.43 %

F – 3.19 %

stb…

Composition calculated on a large globular dataset

The thus gained energy:

where


Predicting binding sites anchor1

Predicting binding sites - ANCHOR

  • Example: N terminal p53

    Contains three binding sites:

    • MDM2: 17-27

    • RPA70N: 33-56

    • RNAPII: 45-58

P = p1*Saverage+ p2*Eint+ p3*Egain


Transzmembr n feh rj k

Anyagcsere folyamatok

Transzporterek

Ion csatornák

Hordozók

Információ csere

Receptorok

Transzmembrán fehérjék


Feh rj k 4 simon istv n

A transzmembrán fehérjék két formája


Feh rj k 4 simon istv n

E. Coli klorid csatorna fehérje


Feh rj k 4 simon istv n

Ismert szerkezetű transzmembrán fehérjék szerkezetét vizsgáló szerverek


Feh rj k 4 simon istv n

Hidrofobicitás


Aminosav helyettes t si m trix

Aminosav helyettesítési mátrix


Szerkezetbecsl s homol gia alapj n

Szerkezetbecslés homológia alapján


Az emberi rodopszin s a bakteriorodopszin aminosav sorrendjeinek sszehasonl t sa

Az emberi rodopszin és a bakteriorodopszin aminosav- sorrendjeinek összehasonlítása


A das szerver algoritmusa

A DAS szerver algoritmusa


Feh rj k 4 simon istv n

DAS profiles of a TM protein as function of residue number


Feh rj k 4 simon istv n

O

o

H

i

I

A HMMTOP algoritmus


Feh rj k 4 simon istv n

Ismert szegmensek lokalizációja


Feh rj k 4 simon istv n

Intracellular domain Q

Pfam

Prosite

Prints

Smart

Intracellular domain Q

Intracellular domain Q

Intracellular domain Q

C

Protein A

N

C

N

Protein B

S c a n n i n g

Protein C

TM selection of UniProtKB

N

C

?

?

C

TOPDOM

Unknown

Protein

N


  • Login