Fehérjék 4 Simon István. Predicting protein disorder - IUPred Basic idea: If a residue is surrounded by other residues such that they cannot form enough.

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1 Fehérjék 4 Simon István

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

3 Predicting protein disorder - IUPred Back to p53: A – 10% C – 0% D – 12 % E – 10 % F – 2 % stb… Amino acid composition of the residue D: The predicted interaction energy: E = Interaction energies: 1.16*0.10+(-0.82)*0+… = 1.138 97%, that it is disordered

4 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

5 Predicting binding sites - ANCHOR Example: N terminal p53 Contains three binding sites: –MDM2: 17-27 –RPA70N: 33-56 –RNAPII: 45-58 P = p1*S average + p2*E int + p3*E gain

6 Transzmembrán fehérjék Anyagcsere folyamatok Transzporterek Ion csatornák Hordozók Információ csere Receptorok

7 A transzmembrán fehérjék két formája

8 E. Coli klorid csatorna fehérje

9 Ismert szerkezetű transzmembrán fehérjék szerkezetét vizsgáló szerverek

10 Hidrofobicitás

11 Aminosav helyettesítési mátrix

12 Szerkezetbecslés homológia alapján

13 Az emberi rodopszin és a bakteriorodopszin aminosav- sorrendjeinek összehasonlítása

14 A DAS szerver algoritmusa

15 DAS profiles of a TM protein as function of residue number

16 H i I o O A HMMTOP algoritmus

17 Ismert szegmensek lokalizációja

18 Pfam Prosite PrintsSmart S c a n n i n g TM selection of UniProtKB TOPDOM Protein A Protein B Protein C Unknown Protein Intracellular domain Q N C N C N C N C ? ?