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Predicting Protein Disorder and Binding Sites: IUPred and ANCHOR Approaches

This document explores the interaction energy between residues and their sequential environments, emphasizing the prediction of protein disorder and binding sites. It utilizes the IUPred algorithm, which assesses the structural probability of residues based on their surroundings. The manuscript also covers the interaction energies of specific amino acids and offers an example using the p53 protein, identifying key binding sites. Additionally, it discusses methods for estimating transmembrane protein structures, emphasizing hydrophobicity and amino acid substitution matrices.

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Predicting Protein Disorder and Binding Sites: IUPred and ANCHOR Approaches

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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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