Order, Disorder, and Everything in Between

Abstract

In addition to the "traditional" proteins characterized by the unique crystal-like structures needed for unique functions, it is increasingly recognized that many proteins or protein regions (collectively known as intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs)), being biologically active, do not have a specific 3D-structure in their unbound states under physiological conditions. There are also subtler categories of disorder, such as conditional (or dormant) disorder and partial disorder. Both the ability of a protein/region to fold into a well-ordered functional unit or to stay intrinsically disordered but functional are encoded in the amino acid sequence. Structurally, IDPs/IDPRs are characterized by high spatiotemporal heterogeneity and exist as dynamic structural ensembles. It is important to remember, however, that although structure and disorder are often treated as binary states, they actually sit on a structural continuum.

Keywords: flexible; intrinsically disordered; multi-functionality; protein function; structural heterogeneity; unfolded; unstructured.

Figure 1

The usage of IDP terminology in PubMed abstracts. The occurrence of each IDP term was counted for each year in abstracts of articles in PubMed associated with 1127 known IDPs.

Figure 2

The fraction of PubMed IDs using IDP terminology by year. The fraction for each year is calculated by the number of PubMed IDs associated with IDPs that use IDP language, divided by the total number of PMIDs associated with the IDP proteins in the set. High confidence IDPs are those that have an extensive amount of experimental evidence verifying that the protein is intrinsically disordered.

Figure 3

The fraction of predicted disorder versus the fraction of PubMed IDs that use IDP language. Each blue dot represents a protein. The percent predicted disorder is plotted against the fraction of PubMed IDs that use intrinsic disorder language divided by all PubMed IDs associated with that protein search term. For each fraction of predicted disorder interval (0%–10%, 10%–20%, etc.), the fraction of the total proteins in that interval is plotted in red. The mean of the fraction of disorder PubMed IDs is plotted for each fraction of disorder interval in black.

Figure 4

Entropic chain functions. (A) Yck2 (in blue) uses a disordered interdomain linker to bind to two separate domains on Akr1 (in orange); (B) The disordered interdomain linker in Phototropin 2 (in green) becomes elongated when irradiated with blue light, causing the activating LOV2 domain to separate from the kinase domain.

Figure 5

Experimental and bioinformatics techniques work together to describe the properties of disorder in proteomes and proteins.

Figure 6

Amino acid scales and disorder and order promoting residues. (Top) Ranking of the 20 amino acids by the Kyte-Doolittle hydrophobicity scale from most to least hydrophobic; (Bottom) Ranking of the amino acids from most to least flexible by Vihinen’s flexibility scale.

Figure 7

A schematic representation of the secretion of adenylate cyclase toxin through the type 1 secretion system. Reprinted under the creative commons license from ref. [101].

Figure 8

A schematic representation of the effects of caffeine on the aggregation properties of α-synuclein. Reprinted with permission from ref. [103]. Copyright (2015) American Chemical Society.

Figure 9

A representative ensemble of 100 conformers for PTP1B. Reprinted with permission from Macmillan Publishers Ltd.: Nature Chemical Biology, part of Springer Nature. [104].

Figure 10

The number of papers per author for the search term in PubMed, plotted against the fraction of those papers that use IDP terminology. Each point represents an author on one or more papers associated with the given search term. The darker the dot, the larger the concentration of authors at that point. Blue dots are authors who have an IDP paper in the field in question (α-synuclein or tau, in this case), while the red dots are authors who have an IDP paper in the field in question and also have an IDP paper in a different field. The fraction of IDP papers is the number of papers by that author that use IDP terminology divided by all papers for that author and search term. The following search terms were used: (A) “alpha synuclein”; (B) “tau AND (protein OR Alzheimer’s OR tauopathies OR neuronal)”.

Figure 10

The number of papers per author for the search term in PubMed, plotted against the fraction of those papers that use IDP terminology. Each point represents an author on one or more papers associated with the given search term. The darker the dot, the larger the concentration of authors at that point. Blue dots are authors who have an IDP paper in the field in question (α-synuclein or tau, in this case), while the red dots are authors who have an IDP paper in the field in question and also have an IDP paper in a different field. The fraction of IDP papers is the number of papers by that author that use IDP terminology divided by all papers for that author and search term. The following search terms were used: (A) “alpha synuclein”; (B) “tau AND (protein OR Alzheimer’s OR tauopathies OR neuronal)”.