Intrinsically Disordered Proteins: from lack of structure to

pleiotropy of functions

Lilia Iakoucheva

University of California, San Diego

OUTLINE

Characterization and properties of IDPs

Functional repertoire of IDPs

Post-translational modifications and disorder

Importance for molecular recognition

Disorder and diseases

Historical perspective1894 - Emil Fischer’s “lock-and-key” hypothesis:

1950 – Fred Karush “Configurational adaptability”

1958 – Daniel Koshland “Induced fit” theory

Amino Acid Sequence 3D Structure Function

Protein Structure-Function Paradigm

Tail of histone H5 (Aviles et al, Eur. J. Biochem. 1978) … and later tails of other histones

First examples of disorder:

95-residue long disordered segment of calcineurin (Kissinger et al, Nature, 1995)

Cyclin-dependent kinase inhibitor p21Waf1/Cip1/Sdi1 (Kriwacki et al, PNAS, 1996)

Etc…

Disorder examples

Some proteins/regions could function without being folded…= disordered

Re-assessing structure-function paradigm

Amino Acid Sequence 3D Structure Function

Amino Acid SequenceOrder

Disorder

Function

Protein regions (or entire proteins) lacking stable II and III structure and existing in the ensemble of conformations with dynamically changing Ramachandran angles

Disorder is experimentally detected by• X-ray crystallography• NMR spectroscopy• circular dichroism (CD)• limited proteolysis (LP)• hydrodynamic methods

What is disorder?

Bracken et al, Curr Opin Struct Biol. 2004, 570; Receveur-Bréchot et al, Proteins, 2006, 24

“I don’t know about hair care, Rapunzel, but I’m thinking a good cream rinse plus PROTEIN conditioner might just solve both our problems.”

DISORDER

Compositional bias

Properties of IDRs and IDPs

Order-promoting

Disorder-promoting

Dunker et al, 2001, JMGM; Radivojac et al, 2007, Biophys J

ResiduesC W Y I F V L H T N A G D M K R S Q P E

DisP

rot-

Ord

er/O

rder

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6DisProt 4.9 (2009) DisProt 3.4 (2006)

↓Aromatic,hydrophobic

↑Charged,hydrophilic

Charge-hydropathy plot

Uversky et al, 2000, Proteins 41:415-427

↑ Net charge↓ Hydrophobicity

↓ Net charge↑ Hydrophobicity

Disorder predictionAA sequence codes for protein structure…

Does AA sequence code for the lack of structure?Keith Dunker group – first Predictor Of Natural Disordered Regions PONDR

• amino acid composition• sequence complexity• net charge• hydrophobicity• flexibility• …and other features

Protein Disorder Predictors

The PONDR-FIT meta-predictor combines several methods. Use it and other predictors here. Xue, B., R. L. DunBrack, R.W. Williams, A.K. Dunker, and V. N. Uversky (2010) "PONDR-Fit: A meta-predictor of intrinsically disordered amino acids," Biochim. Biophys. Acta (in press) doi:10.1016/j.bbapap.2010.01.011

PONDR-FITTM

Linding R, Jensen LJ, Diella F, Bork P, Gibson TJ, Russell RB. "Protein disorder prediction: implications for structural proteomics." Structure. 2003;11(11):1453-9, PMID: 14604535

DisEMBLTM

Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT. "Prediction and functional analysis of native disorder in proteins from the three kingdoms of life." J Mol Biol. 2004;337(3):635-45, PMID: 15019783

DISOPRED2

MacCallum B. "Order/Disorder Prediction With Self Organising Maps." CASP 6 meeting, Online paper DRIPPRED

Cheng J, Sweredoski M, Baldi P. "Accurate Prediction of Protein Disordered Regions by Mining Protein Structure Data" Data Mining and Knowledge Discovery. 2005; 11(3):213-222, Online Paper

DISpro

Prilusky J, Felder CE, Zeev-Ben-Mordehai T, Rydberg EH, Man O, Beckmann JS, Silman I, Sussman JL. "FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded." Bioinformatics. 2005;21(16):3435-8, PMID: 15955783

FoldIndex©

Linding R, Russell RB, Neduva V, Gibson TJ. "GlobPlot: Exploring protein sequences for globularity and disorder." Nucleic Acids Res. 2003;31(13):3701-8, PMID: 12824398 GlobPlot 2

Dosztanyi Z, Csizmok V, Tompa P, Simon I. "IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content." Bioinformatics. 2005;21(16):3433-4, PMID: 15955779

IUPred

Romero P, Obradovic Z, Li X, Garner EC, Brown CJ, Dunker AK. "Sequence complexity of disordered protein." Proteins. 2001;42(1):38-48, PMID: 11093259 PONDR®

Coeytaux K, Poupon A. "Prediction of unfolded segments in a protein sequence based on amino acid composition." Bioinformatics. 2005;21(9):1891-900, PMID: 15657106 PreLink

Yang ZR, Thomson R, McNeil P, Esnouf RM. "RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins." RONN

http://www.disprot.org/predictors.php

PONDRing XPA

XPA-MBD

Structure of the full-length XPA ???

Ikegami et al,1998, Nat.Struct.Biol.

PONDR in action

Iakoucheva et al, Prot Science 2001

Protein-protein interaction sites are mapped to

disordered XPA termini XPA’s phosphorylation site is located in

its disordered C-terminus Putative XPA nuclear localization signals

(NLS) are located in disordered regions

DNA BD

NLS NLS

RPATFIIHRPA

ERCC1

Functional importance

P-site

DDB2

Disorder and Functions

Function Description Examples

Protein modification

Phosphorylation, acetylation, glycosylation, methylation, ubiquitination, fatty acylation

histones, 4-E BP, CFTR, Bcl-2, neuromodulin, HMG-I(Y), p53

Molecular recognition

Protein-DNA, protein-RNA, protein-protein, protein-ligand interactions

p53, max, fos, jun, myc, α-synuclein, CDK inhibitors p21, p57, p27, TF

Macromolecular

assembly

Phages, viruses, bacterial flagellum, ribosome, spliceosome, nuclear pore

flagellin, SR proteins, ribosomal prot, Nups

Entropic chains

Flexible linkers, entropic springs, bristles

fd g3p, RPA, titin, neurofilament HDunker et al, 2002, Biochemistry

Advantages of being disordered

Low-affinity/high-specificity binding Broad binding diversity Ability to form large interaction surfaces

Greater capture radius (“fly-casting” mechanism) Facilitate alternative splicing Facilitate post-translational modifications

DisPhoshttp://core.ist.temple.edu/pred/

Phos-sites prefer IDRs

Gsponer et al, 2008, Science. 322(5906):1365-8

More kinases that target IDPs!

More kinase targets are IDPs!

Ubiquitination and disorder

IDPs are susceptible to proteasomal degradation

Unstructured initiation site is required for degradation (Prakash et al, 2004, Nat Struct Mol Biol.)

PEST motifs are disordered (Singh et al, 2006, Proteins)

Low coverage of known Ub sites by PDB

Examples of Ub sites in IDRs (p53, c-myc, cyclin B, securin, p21, p27, p57, α-synuclein, IκBα etc, various authors)

β-catenin peptide: 15 out of 26 aa are disordered

Wu et al, 2003, Molecular Cell, Vol. 11, 1445–1456

Hao et al, 2005, Molecular Cell, Vol. 20, 9-19

p27 peptide:14 out of 24 aaare disordered

Ub ligases

~60A° gap

Ub sites properties

net chargedisorder

B-factor D, E

hydrophobics

Mea

n Va

lue

-0.2

0.0

0.2

0.4

0.6

0.8Ub sites non- Ub sites

Negative chargeD and EK and hydrophobicsDisorderPredicted B-factors

Ub sites:

Identified 145 new Ub sites with MudPit, mass-spec SILAC and mutant (grr1Δ and cdc34tm) yeast strains to target short-lived proteins

UbPredhttp://www.UbPred.org

Radivojac et al, Proteins, 2010

Radivojac et al, Proteins, 2010

Structural Model of the Dynamic pSic1-Cdc4 Complex

Sic1 contains 9 phosphorylation sites, which interact with Cdc4 in a dynamic equilibrium

Directly interacting residues are transiently ordered, whereas the rest of Sic1 remains disordered even in the complex

The disorder of Sic1 helps to bridge the 64A gap between E2 (Cdc34) and the Sic1 bound to Cdc4 for ubiquitin transfer

Mittag et al, Structure, 2010

Dynamic disorder of Sic1 bound to Cdc4

Disorder and Functions

Function Description Examples

Protein modification

Phosphorylation, acetylation, glycosylation, methylation, ubiquitination, fatty acylation

histones, 4-E BP, CFTR, Bcl-2, neuromodulin, HMG-I(Y), p53

Molecular recognition

Protein-DNA, protein-RNA, protein-protein, protein-ligand interactions

p53, max, fos, jun, myc, α-synuclein, CDK inhibitors p21, p57, p27, TF

Macromolecular

assembly

Phages, viruses, bacterial flagellum, ribosome, spliceosome, nuclear pore

flagellin, SR proteins, ribosomal prot, Nups

Entropic chains

Flexible linkers, entropic springs, bristles

fd g3p, RPA, titin, neurofilament H

Molecular recognition

Disordered regions are commonly used for binding to multiple partners…

C-terminus of p53 NCBD domain of CBP/p300

Oldfield et al, 2008, BMC Genomics. 9 Suppl 1:S1 Wright and Dyson, 2009, Curr Opin Struct Biol.

Mechanisms of binding for IDPsHow do disordered proteins bind to their targets?

Induced folding(binding, … then folding)

Conformational selection(folding, … then binding)

Coupled/synergistic(folding and binding,

… or even binding without folding)(CFTR R and NBD1 domains, Baker et al, 2007, Nat Struct Mol Biol, 14:738)

>=30 >=40 >=50 >=60 >=70 >=80 >=90 >=1000

20

40

60

80 hubsendsorder

prot

eins

, %

length of predicted disordered region, aa

Are disordered proteins network hubs?

Hubs and disorder

Yeast PPICytoskeletal hubs subnetwork from the S.cerevisiae interactome

Haynes et al, 2006, PLoS CB

Ordered hubs – disordered partners14-3-3 proteins – signal transduction, apoptosis, cell cycle, cancer

>200 binding (mostly phosphorylated) targets

Three different predictors indicate that 14-3-3 TARGETS arehighly disordered (Bustos and Iglesias, 2006, Proteins, 63:35–42)

Peptides bind to essentially the same region of 14-3-3

Differences in 14-3-3 side chains conformations(e.g. induced fit mechanism)

Peptides are highly hydrated in the bound state(e.g. likely disordered in the unbound state)

Oldfield et al, BMC Genomics, 2008, 9(Suppl 1):S1

Disorder and disease

Individual examples of IDPs/IDRs involved in human diseases:

p53 (cancer), BRCA1 (cancer), a-synuclein (PD, AD, dementia, Down syndrome), amyloid b (AD), tau (AD), prion (TSEs), amylin (Type II diabetes), hirudin and thrombin (CVD), HPV (cancer)…

Increased amount of disorder in E6 proteins from high-risk HPVs

Human Papillomavirus (HPV)

Uversky et al, 2006, JPR, 5 (8), 1829-1842

Are disease proteins more disordered in general?

BRCA1Mark et al, J Mol Biol. 2005, 345(2):275-87

CD and NMR of fragments-all disordered

CH plot of BRCA1 fragmentsBRCA1 fragmentsFull-length BRCA1

Disordered proteins

Ordered proteins

Length of disordered region

>=30 >=40 >=50 >=60 >=70 >=80 >=90 >=100

Prot

eins,

%

0

20

40

60

80cancer- associated proteinsdisease- related proteinstypical eukaryotic proteinsordered

Disease-related SW keywords arestrongly associated with predicted disorder (p>0.95)

Disorder and disease

Xie et al, 2007, JPR

Disease-associated mutations

Structure: - Folding - Oligomerization - Stability - Activity

…

Function:- Post-translational

modifications- Binding to partners- Intracellular localization …

Disease mutations impact protein

Many predictors of the functional impact of SNPs are available (SIFT, POLYPHEN, SNP3D etc)

Majority rely on known protein 3D structure and evolutionary conservation

Do disease mutations even occur in the regions of disorder?

Disordered regions:

Do not fold into 3D structure

Are generally less evolutionary conserved than ordered regions

Do current predictors make errors in predictingimpact of disease mutations in IDRs?

Disease-associated mutations

DatasetTotal

mutations number

DM 15459 3356 21.7% 12103 78.3%

Poly 24220 9790 40.4% 14430 59.6%

NES 60339 26927 44.6% 33372 55.3%

IDR Mutations OR Mutations

Disease-associated mutations

Disease mutations are prevalent in ORDERED regions

Dataset I DR Mutations D- >D D- >O OR

Mutations O- >O O- >D

DM 3356 80.0% 20.0% 12103 95.1% 4.9%

Poly 9790 88.5% 11.5% 14430 95.1% 4.6%

NES 26927 92.7% 7.3% 33372 94.4% 5.6%

Disorder-to-Order transition

Some disease mutations in disordered regions cause Disorder-> Order transition

(may disrupt disordered structure? induce order?)

p=1.06E-32p=5.47E-105

Substitution D→O disease mutations, % Substitution O→D disease

mutations, %R→W 13.1 L→P 11.9R→C 10.3 C→R 6.6R→H 7.6 G→R 6.1E→K 6.7 W→R 4.1R→Q 6.3 F→S 3.6

44% 32.2%

D→O and O→DD→O O→D

C W Y I F V L H T N A G D M K R S Q P E0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17SW_DAMUSW_POLYSW_CONTROLALL_SW

Residue

% a

ll m

utat

ed r

esid

ues

Arginine is often mutated

Hypothetical mechanism?

Codons for Arginine:

CpG methylationCGGCGTCGCCGAAGAAGG

TGGTGTTGCTGAAGAAGG

R-> WR-> CR-> CR-> StopN/AN/A

R-> W and R-> C are among the most frequent mutations in the disease dataset

Disease ModelsDisorder-centric vs Structure-centric view at disease mutations

IDRs summary Proteins can carry intrinsically disordered regions

These regions can be predicted from sequence

IDRs perform important functional roles: PTMs, molecular recognition, involvement in diseases

Disease mutations could occur in IDRs, and ORand IDR mutations could lead to diseases via different mechanisms

Acknowledgements

Rockefeller University:Jurg Ott

Chad HaynesFei Ji

PNNL:Eric Ackerman

Richard D. Smith

Columbia University:Vladimir Vacic

Indiana University Predrag Radivojac

Mark GoeblKeith Dunker Funding:

Disordered Proteins Database DisProthttp://www.DisProt.org

List of Disorder Predictorshttp://www.disprot.org/predictors.php

Phos Sites Predictor DisPhoshttp://www.ist.temple.edu/disphos/

Ub Sites Predictor UbPredhttp://www.ubpred.org/

lilyak@ucsd.edu – Lilia Iakoucheva

Prevalence of IDPs in nature

Kingdom

# Genomes

% Sequences L > 40*

Bacteria

22 7 - 33Archaea

7 9 - 37Eukaryota

5 52 - 67

16 - 4521 - 51

35 - 51

% Sequences L > 40**

* VL-XT Predictor, order ~ 78%, disorder ~ 65%** VL2 Predictor, order ~ 83%, disorder ~ 75%