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Fehérjék 4 Simon István

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:.

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Fehérjék 4 Simon István

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  1. Fehérjék 4Simon István

  2. 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…..

  3. 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

  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*Saverage+ p2*Eint+ p3*Egain

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

  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. O o H i I A HMMTOP algoritmus

  17. Ismert szegmensek lokalizációja

  18. 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

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