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Fehérjék 3. Simon Ist ván. Bound IUP structures. Tcf3. p27 Kip1. IA 3. FnBP. Bound IUPs – conformations. A1. A2. D. A1. IUPs – preformed elements. Prediction of protein disorder from the amino acid sequence. Dunker order promoting: W, C, F, I, Y, V, L, N
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Bound IUP structures Tcf3 p27Kip1 IA3 FnBP
Bound IUPs – conformations A1 A2 D A1
Prediction of protein disorder from the amino acid sequence • Dunker • order promoting: W, C, F, I, Y, V, L, N • disorder promoting: K, E, P, S, Q, G, R, G, A • 2. Uversky • High net charge/ low average hydrophobicity • Machine learning algorithms • (SVM, NN) • Datasets • PDB for ordered • short and long disorder
Estimation of pairwise energies from amino acid compositions To take into account that the contribution of amino acid i depends on its interaction partners, we need a quadratic form in the amino acid composition The connection between composition and energy is encoded by the 20x20 energy predictor matrix: Pij
Estimated energies correlate with calculated energies Corr coeff: 0.74
Estimated pairwise energies of globular proteins and IUPs IUPs Glob
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…..
Globular proteins are not representative of full genomes Human genome Probable IUPs TM ? GLOB
IUPs: high frequency in proteomes yeast coli
Barabási-Albert Erdős-Rényi Networks The yeast interactome
LM – average disorder profiles local drop in disorder
Distinct interfaces of disordered proteins • More hydrophobic • More residue-residue contacts • Less segments