Intrinsically unstructured proteins Totally Explained

Everything about Intrinsically Unstructured Proteins totally explained

Intrinsically unstructured proteins, often referred to as naturally unfolded proteins or disordered proteins, are proteins characterized by their lack of stable tertiary structure as isolated subunits. The discovery of intrinsically unfolded proteins challenged the traditional protein structure paradigm, which states that a specific well-defined structure was required for the correct function of a protein and that the structure defines the function of the protein. This is clearly not the case for intrinsically unfolded proteins that remain functional despite the lack of a well-defined structure.

Biological role of intrinsic disorder

Many disordered proteins have the binding affinity with their receptors regulated by post-translational modification, thus it has been proposed that the flexibility of disordered proteins facilitates the different conformational requirements for binding the modifying enzymes as well as their receptors.

Flexible linkers

Disordered regions are often found as flexible linkers connecting two globular domains. Linker sequences vary greatly in length and amino acid sequence, but are similar in amino acid composition (rich in polar uncharged amino acids). Flexible linkers allow the connecting domains to freely search the conformational space and to recruit their binding partners.

Coupled folding and binding

Many unstructured proteins undergo transitions to more ordered states upon binding to their targets. The coupled folding and binding may be locally, involving only a few interacting residues, or it might involve an entire protein domain. It was recently shown that the coupled folding and binding allows the burial of a large surface area that would only be possible for a fully structured proteins if they were much larger (Gunasekaran et al, 2003).
The ability of disordered proteins to bind, and thus to exert a function, shows that stability isn't a required condition.

Sequence signatures of disorder

Intrinsically unstructured proteins are characterized by a low content of bulky hydrophobic amino acids and a high proportion of polar and charged amino acids. Thus disordered sequences can't bury sufficient hydrophobic core to fold like stable globular proteins. In some cases, hydrophobic clusters in disordered sequences provide the clues for identifying the regions that undergo coupled folding and binding.
Many disordered proteins also reveal low complexity sequences, for example sequences with overrepresentation of a few residues. While low complexity sequences are a strong indication of disorder, the reverse isn't necessarily true, that is, not all disordered proteins have low complexity sequences.
Disordered proteins have a low content of predicted secondary structure.

Identification of intrinsically unstructured proteins

Intrinsically unfolded proteins, once purified, can be identified by various experimental methods. Folded proteins have a high density (partial specific volume of 0.72-0.74 mL/g) and commensurately small radius of gyration. Hence, unfolded proteins can be detected by methods that are sensitive to molecular size, density or hydrodynamic drag, such as size exclusion chromatography, analytical ultracentrifugation, Small angle X-ray scattering (SAXS), and measurements of the diffusion constant. Unfolded proteins are also characterized by their lack of secondary structure, as assessed by far-UV (170-250 nm) circular dichroism (esp. a pronounced minimum at ~200 nm) or infrared spectroscopy.
Unfolded proteins have exposed backbone peptide groups exposed to solvent, so that they're readily cleaved by proteases, undergo rapid hydrogen-deuterium exchange and exhibit a small dispersion (<1 ppm) in their 1H amide chemical shifts as measured by NMR. (Folded proteins typically show dispersions as large as 5 ppm for the amide protons.)
The primary method to obtain information on disordered regions of a protein is NMR spectroscopy. The lack of electron density in X-ray crystallographic studies may also be a sign of disorder.

De novo prediction of intrinsically unstructured proteins

Computational methods exploit the sequence signatures of disorder to predict whether a protein is disordered given its amino acid sequence. The table below, adapted from (Ferron et. al, 2006), shows the main features of softwares for disorder prediction. Note that different softwares use different definitions of disorder.

Predictor	What is predicted	Based on	Generates and uses multiple sequence alignment?
PONDR (External Link)	All regions that are not rigid including random coils, partially unstructured regions, and molten globules	Local aa composition, flexibility, hydropathy, etc	No
SEG (External Link)	Low-complexity segments that is, “simple sequences” or “compositionally biased regions”.	Locally optimized low-complexity segments are produced at defined levels of stringency and then refined according to the equations of Wootton and Federhen	No
Disopred2 (External Link)	Regions devoid of ordered regular secondary structure	Cascaded support vector machine classifiers trained on PSI-BLAST profiles	Yes
Globplot (External Link)	Regions with high propensity for globularity on the Russell/Linding scale (propensities for secondary structures and random coils)	Russell//Linding scale of disorder	No
Disembl (External Link)	LOOPS (regions devoid of regular secondary structure); HOT LOOPS (highly mobile loops); REMARK465 (regions lacking electron density in crystal structure)	Neural networks trained on X-ray structure data	No
NORSp (External Link)	Regions with No Ordered Regular Secondary Structure (NORS). Most, but not all, are highly flexible.	Secondary structure and solvent accessibility	Yes
FoldIndex (External Link)	Regions that have a low hydrophobicity and high net charge (either loops or unstructured regions)	Charge/hydrophaty analyzed locally using a sliding window	No
Charge/hydropathy method. See (Uversky et al, 2000).	Fully unstructured domains (random coils)	Global sequence composition	No
HCA (Hydrophobic Cluster Analysis) (External Link)	Hydrophobic clusters, which tend to form secondary structure elements	Helical visualization of amino acid sequence	No
PreLink (External Link)	Regions that are expected to be unstructured in all conditions, regardless of the presence of a binding partner	Compositional bias and low hydrophobic cluster content.	No
IUPred (External Link)	Regions that lack a well-defined 3D-structure under native conditions	Energy resulting from inter-residue interactions, estimated from local amino acid composition	No
RONN (External Link)	Regions that lack a well-defined 3D structure under native conditions	Bio-basis function neural network trained on disordered proteins	No

Since the methods above use different definitions of disorder and they were trained on different datasets, it's difficult to estimate their relative accuracy.

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