Supporting online material

 

TOC for Supporting Online Material

 

 

Synopsis for Supporting Online Material

Many methods that are optimized to predict natively unstructured regions in proteins are trained and tested on residues that are missing from X-ray structures. Although this definition has some advantages (for instance, the definition is more or less unified among different researchers and can be easily interpreted), missing residues do not necessarily represent a biological phenomenon. In fact, it has been shown that residues in these regions are similar in amino acid composition and secondary structure content to flexible structure loops (1). Therefore, these methods cannot always distinguish between loops that are structured and loops that arenÕt. Here, we show one example in which the secondary structure prediction by PSIPRED (2) (Fig. App_1) is highly correlated with DISOPRED2 (3) output (Fig. 5A) (DISOPRED2 prediction depends on PSIPRED output among other properties); the locations of the peeks of the prediction are correlated with loops location. NORSnet, however, is optimized to make the distinction between natively unstructured loops and structured loops. Since both NORSnet and DISOPRED2 use predicted secondary structure information (which can reach about 80% accuracy), they can distinguish whether two homologues proteins are ÔloopyÕ or not and overcome the high similarity of the amino acid compositions (Fig. App_2). Conversely, methods that use only amino acid composition cannot always make that distinction.


Figures for Supporting Online Material

Fig. App_1

 

 

Fig. App_1: PSIPRED prediction for Kappa-casein precursor. The protein is predicted to have several long loops (residues 24-42, 89-125 and 130-171). Note that the location of the loops is correlated with high scores predicted by NORSnet and DISORPED2 that use this information.


Fig. App_2

 

 Fig. App_2:  Secondary structure predictions of the N-termini domains of DFF45, DFF40 and CIDE-B.  Although the N-term domain of DFF45 is unstructured PSIPRED predicts secondary structure elements within that region (A). DFF40 and CIDE-B, homologues of DFF45, however, do not have natively unstructured N-termini (B-C). Interestingly, to an extent this is reflected in the predicted secondary structure prediction of these proteins as DFF45 is predicted more residues to be in coil.


Fig. App_3

 

 

Fig. App_3:  Unstructured regions over-represented in protein-protein hubs of worm. Similarly to Fig. 7, we ran IUPred on worm proteins that are involved in protein-protein interactions. NORSnet data is identical to the one presented in Fig. 7. The number of proteins that are predicted to be either unstructured or well-structured is plotted against the number of interacting partners for two different thresholds of reliability of the two methods: A+B were compiled for thresholds at which both methods maintained 100% accuracy for the NESG data (Fig. 4), while graphs C+D were compiled for 100% accuracy on DisProt (Fig. 3). Since the number of observed interaction partners falls off dramatically, we had to group the data into bins of roughly equal sizes (x-axes). A+C show the results for the number of proteins predicted in each bin of interaction partners, while B+D show the normalized ratios to zoom into the difference between unstructured and structured proteins in each bin. These ratios were compiled as Ratio(bin)={#unstructured(bin)/#structured(bin)} / {#unstructured(1)/#structured(1)}. As all ratios are above 1, proteins with more than one interaction partners have more unstructured regions than proteins with one partner. For the thresholds at which both methods achieved 100% accuracy on the DisProt dataset, both IUPred and NORSnet identified unstructured regions in 98 proteins that interact with seven partners or more. IUPred predicted 37 proteins with unstructured regions that NORSnet did not identify and NORSnet predicted 17 proteins with unstructured regions that IUPred had missed.

 

Tables

Table App_1

 

Number

NESG ID a

Sequence length

Disorder signal b

1

AR2242

107

Largely

2

BhR21

117

Partly

3

CvR16

205

Partly

4

FR254

163

Largely

5

HR1506

79

Largely

6

HR1538

62

Largely

7

HR1821

157

Partly

8

HR1974

120

Largely

9

HR2078

170

Largely

10

HR2130

173

Largely

11

HR224

87

Largely

12

HR2299

113

Largely

13

HR36

115

Partly

14

HR8

76

Largely

15

HR919

208

Largely

16

HR922

154

Largely

17

HR997

189

Largely

18

KR12

231

Largely

19

LmR11

103

Partly

20

MaR51

125

Partly

21

MhR22

75

Largely

22

MhR41

206

Partly

23

MrR47

128

Partly

24

PsR51

76

Largely

25

SR128

193

Partly

26

SmR3

62

Largely

27

SpR5

62

Largely

28

WR46

193

Partly

29

XR5

50

Largely

30

YR8

155

Largely

 

Table S1: Dataset of unstructured proteins from NorthEast Structural Genomics Consortium

a          NESG id referred to  identifiers given by the NESG consortium.

b          Disorder signal referred to different levels of signal of a protein to be unstructured from NMR experiments. Largely marked largely unstructured proteins, e.g., (i) their HSQC has high signal to noise and very low dispersion and (ii) their HetNOE data is clear negative; partly marked partly unstructured proteins, which have some local structure but overall obey the same criteria; 20 proteins were identified as largely unstructured and 10 proteins were identified as partly unstructured.  

 

 

 

 

References for Supporting Online Material

REFERENCES BEGIN

 

1.         Radivojac, P., Obradovic, Z., Smith, D.K., Zhu, G., Vucetic, S., Brown, C.J., Lawson, J.D. and Dunker, A.K. (2004) Protein flexibility and intrinsic disorder. Protein Science, 13, 71-80.

2.         McGuffin, L.J., Bryson, K. and Jones, D.T. (2000) The PSIPRED protein structure prediction server. Bioinformatics, 16, 404-405.

3.         Ward, J.J., Sodhi, J.S., McGuffin, L.J., Buxton, B.F. and Jones, D.T. (2004) Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. Journal of Molecular Biology, 337, 635-645.