Makromolekulak_2010_12_07

Simon Istvn

Prion protein

Bound IUP structuresp27Kip1IA3FnBPTcf3

Aminosav sszettelekRadivojac et al. Protein Sci. 2004;13:71-80. Rvid, hossz, N- s C- terminlis rgikban lv rszeknekms-ms aminosav sszettelk van

Dunker order promoting: W, C, F, I, Y, V, L, Ndisorder promoting: K, E, P, S, Q, G, R, G, A2. Uversky High net charge/ low average hydrophobicityMachine learning algorithms (SVM, NN)

Datasets PDB for ordered short and long disorderPrediction of protein disorder from the amino acid sequence

Pairwise energy calculated from structure

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 compositionThe connection between composition and energy is encoded by the 20x20 energy predictor matrix: PijEstimation of pairwise energies from amino acid compositions

Estimated energies correlate with calculated energiesCorr coeff: 0.74

Estimated pairwise energies of globular proteins and IUPsIUPsGlob

IUPred: http://iupred.enzim.hu

IUPred: http://iupred.enzim.huP53 Tumor antigen

IUPs: high frequency in proteomescoliyeast

Erds-RnyiThe yeast interactomeBarabsi-AlbertNetworks

The mediator complex

Hub proteins contain more disordered regions in all four genomes

Distinct interfaces of disordered proteins More hydrophobic More residue-residue contacts Less segments

Lack of segmentation of the interfaces of IUPsIUPsGlob

LM average disorder profileslocal drop in disorder

Predicting protein disorder - IUPredBasic 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..The algorithm:

Predicting protein disorder - IUPredBack to p53:The predicted interaction energy:E = 1.16*0.10+(-0.82)*0+=1.138

Predicting binding sites - ANCHOR3 Interaction with globular proteinsWe 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 % stbA 7.67%C 2.43%D 4.92 %E 5.43 %F 3.19 % stbComposition calculated on a large globular datasetThe thus gained energy:where

Predicting binding sites - ANCHORExample: N terminal p53Contains three binding sites:MDM2: 17-27RPA70N: 33-56RNAPII: 45-58The three quantities are combined optimally to best distinguish binding sites.This is converted into a p-value (probability of the residue forming a disordered binding site).P = p1*Saverage + p2*Eint + p3*Egain

Application: Segmented bindingExample: human p27

Inhibitor of CDK2-CyclinA complex.3 domains become ordered during binding:

D1 binds strongly LH forms a helix, binds weakly and steers the third domain to place D2 binds strongly but not evenly contains 3 subdomains that give the majority of binding energy

We are able to identify strongly interacting regions separately

Rendezetlensg predikci - IUPred

Ismeretlen szekvencia predikcik

Ismeretlen szekvencia predikcikANCHORPSIPRED

Ismeretlen szekvencia predikcikA modellnk:DNS kt, globulris domnrendezetlenrszekkthely, rszbena-helikliskthely, a-helikliskthely, nincsszerkezeti infoA valsg (p53):DNS kt, globulris domnMDM2 kthelyRPA70N s RNAPIIkthely (tfedek)regulcis kthely, 4 partner(klnbz konformcik)tetramerizcis rgi,a-heliklis