Abstract
The rationale for replacing the old binary of structure–function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein–protein interactions in many regulatory processes, formation of membrane‐less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.
Keywords: arginine, binding promiscuity, glutamic acid, liquid–liquid protein phase separation, molten globules, moonlighting proteins, post‐translational modifications, proline, protein–protein interactions, serine
1. INTRODUCTION
The turn of the 20th century can be considered as a turning point in our understanding of protein function. It was the beginning of our realization that the binary of structure–function needs to be replaced with the trinity of structure, disorder, and function (Uversky & Kulkarni, 2021). The central dogma of molecular biology states that in the biological systems, the flow of genetic information is a mostly unidirectional DNA → RNA → Protein path (Crick, 1970), which, taken together with the classic Anfinsen's experiments (Anfinsen, 1973), implied that the end of the road was the unique native structure of a protein; sacrosanct for biological activity/function. It is clear now that not just structure but disorder of proteins also contains information (Kulkarni et al., 2022). The nascent synthesized protein chain has a third choice beyond folding and misfolding, that of the non‐folding; that is, become (or stay) unstructured (Uversky, 2003). While the protein may appear to be at the end of this short chain of information flow, the language changes, and the communication becomes even more vigorous. To start with, posttranslational modifications (PTMs) are not random, the sequence ultimately decides their locations and information flow about catalysis/regulation ensues. Intrinsic disorder, more than order, facilitates this communication in both intra‐ and intercellular situations. Disorder brings in high sensitivity even to the miniscule changes in the environment and smart (swift, reversible, and large) response to the need of the organism in spatiotemporal manner. There is a division of labor between structure and disorder in proteins but, with some intermingling of roles. At least in the vicinity of their catalytic sites, enzymes are mostly structured proteins with some exceptions like phosphoinositide 3‐kinase, whereas regulatory proteins invariably have significant level of disorder (Bondos et al., 2022; Davé & Uversky, 2023; DeForte & Uversky, 2017; Dunker et al., 2001; Dunker, Brown, Lawson, Iakoucheva, & Obradovic, 2002; Dunker, Brown, Lawson, Iakoucheva‐Sebat, et al., 2002; Dunker, Brown, & Obradovic, 2002; Dyson & Wright, 2005; Fink, 2005; Iakoucheva et al., 2002; Romero et al., 2006; Tompa, 2002; Uversky, 2002a, 2002b; Uversky et al., 2000, 2005, 2006; Uversky & Dunker, 1804; Vucetic et al., 2007; Wright & Dyson, 2015; Xie, Vucetic, Iakoucheva, Oldfield, Dunker, Obradovic, & Uversky, 2007).
This review reassesses why it makes sense to consider the structure–function continuum model based upon biological activity of proteins being a function of structure, conformational dynamics, and disorder (Fonin et al., 2019; Gupta & Uversky, 2023a; Uversky, 2020a, 2019, 2016a; Zheng et al., 2023). The rationale and advantages for doing so have increased considerably in recent years. This continuum model is an inclusive narrative, unifying and creating a seamless discussion on protein functions in terms of both structure and disorder. Including disorder in the protein structure–function paradigm also equips us better to deal with emerging insights about protein specificity and evolution of proteins. This review is an attempt to present an updated status of the aforementioned theme.
2. THE STRUCTURE–FUNCTION CONTINUUM MODEL
The continuum model inserts the functional importance of intrinsic disorder in proteins and conveys that disorder in proteins is a matter of degree. There are structured proteins with different conformational flexibilities, there are proteins with some intrinsically disordered regions (IDPRs) and there are intrinsically disordered proteins (IDPs) with high degree of structural disorder (Bondos et al., 2022; DeForte & Uversky, 2016; Uversky, 2002a, 2002b, 2019, 2016a, 2024; Uversky & Dunker, 1804; Wright & Dyson, 2015). As we will discuss later, the proteins with significant disorders have different amino acid compositions. IDPs can be relatively compact (resembling molten globules) or have more extended conformation (which is either native coils or resembles pre‐molten globules) (Bondos et al., 2022; DeForte & Uversky, 2016; Uversky, 2002a, 2002b, 2019, 2016a, 2024; Uversky & Dunker, 1804; Wright & Dyson, 2015). This leads to several functional advantages over structured proteins. Larger surface area means greater capture radius during interaction with other molecules, the term “fly‐casting” is often used to describe this. They have no pre‐formed binding sites, instead their many disordered regions are potential binding site, folding upon binding to the partner. These potential binding sites are promiscuous; that is, same site can bind to different partners. This enables these proteins to act as hub proteins and regulatory proteins. The latter feature is further amplified as greater accessibility to potential residues for post‐translational modifications exists because of their more open conformations (Bondos et al., 2022; DeForte & Uversky, 2016; Uversky, 2002a, 2002b, 2019, 2016a, 2024; Uversky & Dunker, 1804; Wright & Dyson, 2015).
Noble (2024), while reviewing the recent “How Life Works: A User's Guide to the New Biology” book by Ball (2023), commented, “In fact, most genes don't have a set of pre‐set function that can be determined from their DNA sequence… Many proteins have disordered domains‐sections whose shape is not fixed but changes constantly”. We can add that it is not just shape but the function as well which often has spatiotemporal changes. Structure–function continuum model recognizes that structure, conformational dynamics, and intrinsic disorder seamlessly lead to the function, which does not necessarily have a one‐to‐one relationship with the proteoforms, which arise from the same gene (Smith & Kelleher, 2013; Uversky, 2019). The proteoforms are structurally and functionally different forms that arise from the same gene by changes at the DNA, mRNA, and protein levels (Smith & Kelleher, 2013). That expands the old structure–function relationship in proteins to the new proteoform–structure–disorder–function paradigm. This is the core of the structure–function continuum model (Uversky, 2019). As we will discuss later, hierarchies of protein structure proposed by Lindstrom–Lang coexist with the hierarchies of intrinsic disorder in a very large number of proteins and both are necessary for the biological functions or dysfunction as well. While usual folding pathway included only the options of misfolding or folding to a polypeptide chain, it actually also has a third possibility of remaining unfolded, at least in parts (Hsu et al., 2020). Furthermore, multi‐functionality of proteins quite often is enabled by the intrinsic disorder (Uversky, 2019).
As the disorder is the new entrant in the old structure–function relationship, let us first elaborate on what functions are dependent upon disorder.
3. FUNCTIONS ENABLED BY DISORDER
In the more inclusive new paradigm of structure/disorder–function, there are functions and cellular processes, which are enabled by disorder rather than structure. Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs also known as intrinsically disordered protein regions, IDPRs) can behave as native coils or pre‐molten globules with high solvent accessibility or of less conformational mobility in the form of collapsed dynamic structures exemplified by native molten globules. It is noteworthy that the concepts of molten globule and pre‐molten globule are very much parts of the protein structure narrative (Gupta & Uversky, 2023b). Also, just as structure can take many forms (α‐helices, β‐sheet, numerous designs of the oligomeric proteins), disorder should not be “othered” by simply putting it in a single bin. There are many variations or flavors of disorder (e.g., see Huang et al., 2012, 2014; Vucetic et al., 2003). These variations show up in the diverse functional repertoire of the disorder [see Figure 1, where the data about ordered proteins (ORDPs) are also included for comparison; Deiana et al., 2019].
FIGURE 1.
Over‐ (under‐) representation of the protein variants in the PANTHER protein classes. Bar charts of the normalized differential occurrence of ORDPs, IDPRs, and IDPs in various protein classes, with respect to the human proteome. Only statistically significant differences are reported (p‐value < 0.05). Reproduced from Deiana et al. (2019) under CC 4.0 attribution.
Figure 1 shows that ORDPs (proteins which have <30% of disordered residues) are often enzymes or proteins carrying storage, immune, transport, receptor, and calcium binding functions. IDPRs occur more often in transporters, cell‐junction proteins, receptors, cytoskeletal proteins or proteins which regulate enzyme functions. IDPs are generally skeletal proteins or transcription factors, or nucleic acid binding proteins. The picture which emerges is that disorder or structure participate in all kinds of biological functions but to different extents (Deiana et al., 2019).
Below is an update on some of the protein functions/biological processes which rely to a significant level on disorder. The list and the degree of coverage are subjective and are biased by more recent results/ideas and effort at including contrary viewpoints. The last represents the cracks in the edifice of current enzymology. And, as the song goes “There is a crack, a crack in everything, that's how the light gets in.” (Leonard Cohen, 1992 in the song Anthem in album “The Future”).
We now proceed to throw further light on some of the key functions enabled by the disorder.
4. INTERACTIONS OF IDPs/IDRs WITH OTHER PROTEINS AND SURFACES IN VITRO AND IN VIVO
Disorder has a key involvement in interactions of IDPs/IDRs with other proteins/nucleic acids (Alterovitz et al., 2020; Cheng et al., 2007; Dunker et al., 2001, 2005; Dunker, Brown, Lawson, Iakoucheva, & Obradovic, 2002; Hegyi et al., 2007; Hsu et al., 2012, 2013; Huang et al., 2012; Oldfield et al., 2005, 2008; Oldfield & Dunker, 2014; Peng et al., 2014; Toth‐Petroczy et al., 2008; Uversky et al., 2005; Vacic, Oldfield, et al., 2007; van der Lee et al., 2014). Being conformationally malleable and adaptable and being readily tunable by their structural and chemical context, IDPs/IDRs extend the repertoire of macromolecular interactions and serve as ideal responders to regulatory cues (Holehouse & Kragelund, 2023). Furthermore, the larger interacting surface area of IDPs/IDRs (as compared to structured proteins and domains of similar protein lengths) maybe a key importance of disorder in cellular biology. As estimated by Gunasekaran et al. “protein size would need to be 2–3 times larger… enlarge the size of the cell by 15–30%” if all proteins were just structured (Gunasekaran et al., 2003).
While the phrase coupled binding and folding is quite frequently used while discussing protein functionality, it is important to keep in mind that even “folding” is best described as a part of continuum, in which the disorder of the protein is retained in the complex in a wide range with “fuzzy complexes” as one extreme end of the spectrum (Chowdhury et al., 2023; Freiberger et al., 2021; Fuxreiter, 2012, 2018, 2019, 2020; Fuxreiter & Tompa, 2012; Gruet et al., 2016; Miskei et al., 2020, 2017; Sharma et al., 2015, 2019; Tompa & Fuxreiter, 2008; Welch, 2012). A recent review by Chowdhury et al. comprehensively covers the insights on protein–protein interactions (involving IDPs/IDRs) from the single molecule Förster resonance energy transfer (FRET, also known as fluorescence resonance energy transfer) (Chowdhury et al., 2023). As IDPs/IDRs (free and even in most of their complexes) are a lot more dynamic; NMR and FRET constitute two powerful techniques for studying these interactions. In FRET, a change in the distance (of the two residues which are donor and acceptor of energy) of even 1 Å can be measured by change in the transfer efficiency of about 0.03 (Chowdhury et al., 2023). Besides single molecule, FRET can give information about rotational motion in the complexes and their hydrodynamic radii. Combining this technique along with microfluidics and temperature jump relaxation kinetics has made it even more versatile; for example, both high and low concentration ranges of the proteins(s) can be used (Chowdhury et al., 2023). An interesting observation is that one can detect formation of an encounter complex before a stable complex emerges in two systems. To sum up, single‐molecule FRET represents a very promising approach, which is yielding valuable insights into interaction of IDPs/IDRs with other surfaces (Chowdhury et al., 2023).
The protein–protein interactions (PPIs) mediated by intrinsic disorder play a critical role in cell signaling (Bondos et al., 2022; Dunker et al., 2005; Iakoucheva et al., 2002; Uversky et al., 2005), allostery (Berlow et al., 2018; Eginton et al., 2015; Ferreon et al., 2013; Garcia‐Pino et al., 2010; Hilser & Thompson, 2011; Huang et al., 2020; Li & Hilser, 2018; Motlagh et al., 2012, 2015; Motlagh & Hilser, 2012; Tee et al., 2020; Tompa, 2014; Wrabl et al., 2011), and can act as molecular switches (Berlow et al., 2022; Choi et al., 2019; Dennis, 2015; Hong et al., 2020; Kulkarni et al., 2018, 2023; Kulkarni & Kulkarni, 2019; Lin et al., 2019; Salladini et al., 2020; Taylor et al., 2019, 2021; van Roey et al., 2012). The short lifetimes and reversible nature of the complexes formed by IDPs/IDRs with partnering proteins have been discussed at length earlier by one of us (Uversky, 2020b). An illustrative example of disorder‐based multifunctionality is given by the MYC protooncogene, which is known to act as a universal amplifier of transcription through interaction with multiple factors and complexes regulating almost every cellular process (Das et al., 2023). It was suggested that this multifunctionality can be described using a “hand‐over model”, where differential partitioning and trafficking of the intrinsically disordered MYC results in the formation of a loose interaction network between various gene‐regulatory complexes and factors (Das et al., 2023).
While PPI involving IDPs/IDRs have been extensively studied, interaction of small ligands with IDRs has attracted lot less attention. An interesting result in this regard is that a binding site consisting of eight amino acids from MyC protein could be “ported” to another IDP though with some loss in the affinity to the small molecular weight ligands (Jaiprashad et al., 2022). We probably need greater experience to understand how this works, as any change in the flanking residue at either end of the binding site abolished the binding (Jaiprashad et al., 2022).
In fact, eukaryotic proteins abundantly contain numerous short linear motifs (SLiMs, or eukaryotic linear motifs ELMs), which are short segments of proteins, usually 3–10 amino acids long, possessing specific cellular functions, and which therefore represent a major arsenal governing their specific PPIs (Diella et al., 2008; Tompa et al., 2014; van Roey et al., 2012, 2014; Via et al., 2011). These functional motifs, which are recognized and/or posttranslationally modified by ordered domains of the interacting partners, are highly abundant, and human proteome is expected to contain over a million of SLiMs (Tompa et al., 2014). Furthermore, SLiMs are commonly affected by alternative splicing, alternative promoter usage, and RNA editing; that is, pretranslational modifications responsible for the production of multiple protein isoforms from a single gene. It was pointed out that the inclusion or removal of SLiMs by these pretranslational alterations have important functional outputs, as they “can switch the subcellular localization of an isoform, promote cooperative associations, refine the affinity of an interaction, coordinate phase transitions within the cell, and even create isoforms of opposing function”, thereby enabling the creation, modulation, and regulation of complex signaling and regulatory pathways (Weatheritt & Gibson, 2012).
Importantly, infection agents, bacteria (Samano‐Sanchez & Gibson, 2020), and viruses (Davey et al., 2011; Elkhaligy et al., 2021; Franzosa & Xia, 2011), are known to successfully utilize the SLiM mimicry to hijack the host proteins and thereby “slave” the host cellular machinery for their purposes. Since such transient mimicry‐driven pathogen–host interactions depend on the proteomic context of the host cell, they can generate complex diversity in virulence, pathogenicity, and transmissibility (Elkhaligy et al., 2021). Such SLiM mimicry might originate in viral and bacterial proteins due to convergent evolution (Franzosa & Xia, 2011), with the existence of the conserved SLiM‐mimicry‐based motifs within the same virus family reflecting the presence of functionally important pathogen–host protein interactions (Elkhaligy et al., 2021). Furthermore, viral proteins can also utilize their globular domains for binding to SLiMs and longer intrinsically disordered domains (IDDs) present in host or viral proteins (Madhu et al., 2022).
In addition to the disorder‐driven PPIs, the interaction of IDPs/IDRs with membranes is important in autophagy (Popelka & Uversky, 2022). The PPI involving disorder are in fact drive endocytosis and membrane remodeling (Wade et al., 2023). The bacterial tubulin‐like GTPase FtsZ that serves as the foundation for the cytokinetic ring at the nascent division site uses its intrinsically disordered C‐terminal domain for interaction with the membrane and modulation of the interactions both between FtsZ subunits and between FtsZ and modulatory proteins in the cytoplasm (Buske et al., 2015). Similarly, functions of SNARE (N‐ethylmaleimide‐sensitive factor (NSF) attachment protein (SNAP) receptor) in various forms of the intracellular membrane trafficking responsible for the membrane and biocargo shuffling between multiple compartments within the cell and extracellular environment are dependent on the self‐assembly of its IDRs (Khvotchev & Soloviev, 2022). Disordered regions found in the modular nonreceptor protein tyrosine kinase Src (the prototype of Src family kinases, SFKs) are crucial for interaction of this mediator of pleiotropic molecular signaling with lipid membranes and proteins (Kato, 2022). IDRs play crucial roles in remodeling of the plasma membrane by the surface‐bound protein monomers and oligomers (Araya et al., 2022). IDPs/IDRs are also involved in synaptic vesicle trafficking and exocytosis and in overall synaptic organization (Snead & Eliezer, 2019). Intrinsically disordered dehydrins are important for cryoprotection of membranes (Murray & Graether, 2022). Overall, because of a crucial importance of a dynamic cross‐talk and complex interplay between the IDPs/IDRs and the membranes, where disorder plays a number of essential roles in membrane modulation, lipid and curvature sensing, phase separation events, transduction of signal across membranes, protein scaffolding, and in the coupling of enzymatic activity to these processes, it was claimed: “Far from being a marriage of convenience, intrinsically disordered regions and membranes are a match made in heaven for cell signalling” (Cornish et al., 2020).
An update on how disorder in turn is affected during interaction with biological surfaces in general is available (Di Bartolo & Masone, 2023). Lately, there has been a vigorous renewal of interest in understanding protein interactions with surfaces of nanoparticles which has, again, importance in both in vivo and in vitro (Gupta & Roy, 2020; Mukherjee & Gupta, 2016a; Sousa et al., 2021). This also includes binding of IDRs to nanoparticles (Lima et al., 2023; Mahapatra et al., 2020; Munari et al., 2020). Viola et al. reported that interaction of tau protein with ultrafine gold nanoparticles led to multimolecular assembly via hot spots of binding sites as in PPI interactions (Viola et al., 2022). The fate of IDPs during corona formation at binding to silica nanoparticles has been investigated by Vitali et al. (2018) who found that most of the IDPs remain unstructured with few showing marginal increase in α‐helicity. A very informative paper in this regard is by Xie et al. (2018) who used NMR to look at the interaction of four IDPs with silica nanoparticles at atomic resolution level. Their approach allows to estimate binding affinities of IDPs from binding affinities of individual amino acids involved in the binding to the nanoparticles with the help of “free residue interaction model” (Xie et al., 2018).
The PPI interactions play a number of critical roles in many biological processes including cell cycle dynamics and its regulation.
5. CELL CYCLE DYNAMICS AND REPROGRAMMING OF CELLS
The importance of IDPs/IDRs for the regulation of cell cycle is illustrated by the well‐established roles of the intrinsically disordered p21Cip1 (p21) and p27Kip1 (p27) in the control of the mammalian cell division cycle by inhibiting cyclin‐dependent kinases (Cdks; Galea et al., 2008; Mitrea et al., 2012; Yoon et al., 2012). Recently, p27Kip1, a gatekeeper of G1/S transition, a regulator of cell motility and migration, controller of cell differentiation program, and an activator of apoptosis/autophagy, was described as an IDP with scaffold properties, whose multifunctionality is modulated by its cellular levels and localization, as well as by a wide range of PTMs, such as acetylation, O‐linked N‐acetylglicosylation, phosphorylation, SUMOylation, and ubiquitination (Bencivenga et al., 2021).
In budding yeast, the cell cycle progression is driven by the precise temporal sequence of activation and deactivation events of cyclin‐dependent kinases (Cdk1/Clb) controlled by interaction with the intrinsically disordered Sic1 protein, which achieves its inhibitory function by cooperative binding, with different Sic1 regions stretching over the Cdk1/Clb surface (Barberis, 2012). The activation of DNA damage checkpoint kinase Mec1/ATR, which is important for a tightly controlled response to various genotoxic stresses, is regulated by the intrinsically disordered C‐terminal tails of the specific activator proteins, Dpb11 in S. cerevisiae or TopBP1 in the vertebrates (Navadgi‐Patil & Burgers, 2009).
Recently, an example of how SLiMs in IDRs can regulate the cell cycle dynamics was described (Faustova & Loog, 2021; Hossain et al., 2021). It was shown that cyclin‐CDK‐dependent and independent protein–protein interactions are mediated by multiple SLiMs within IDRs of the origin recognition complex‐1 (ORC1) and CDC6 in a cell cycle phase‐dependent manner (Hossain et al., 2021). The authors indicated: “A domain within the ORC1 IDR is required for interaction between the ORC1 and CDC6 AAA+ domains in G1, whereas the same domain prevents CDC6–ORC1 interaction during mitosis. Then, during late G1, this domain facilitates ORC1 destruction by an SKP2‐cyclin A‐CDK2‐dependent mechanism. During G1, the CDC6 Cy motif cooperates with cyclin E‐CDK2 to promote ORC1–CDC6 interactions. The CDC6 IDR regulates self‐interaction by ORC1, thereby controlling ORC1 protein levels. Protein phosphatase 1 binds directly to a SLiM in the ORC1 IDR, causing ORC1 de‐phosphorylation upon mitotic exit, increasing ORC1 protein, and promoting pre‐RC assembly” (Hossain et al., 2021).
Intrinsic disorder is also crucial for the reaction of all organisms to the day/night cycle, as proteins forming the circadian clock network display a significant amount of intrinsic disorder (Pelham et al., 2020). In fact, it was demonstrated that the levels and peculiarities of disorder distribution are conserved in the core clock of the key eukaryotic circadian model organisms Drosophila melanogaster, Neurospora crassa, and Mus musculus, indicating that intrinsic disorder is crucial for optimal circadian timing (Pelham et al., 2020). These are important observations, since as much as 80% of mammalian genes are expected to be under circadian transcriptional regulation across all mammalian tissue types (Akhtar et al., 2002; Hughes et al., 2012; Hurley et al., 2014; Mure et al., 2018).
The Yamanaka factors which can reprogram a somatic cell to a pluripotent stem cells were found to possess a high degree of disorder (Xue et al., 2012). Deng et al. (2021) have discussed the usefulness of these transcription factors in obtaining cells which can be useful for modeling diseases and in regenerative medicine. Recently, these transcription factors have been found to show promise in treatment of some cancers and neurodegenerative diseases (Aguirre et al., 2023).
Having looked at the cellular level, let us now consider the finer details of the designs at the molecular level, which lead to intrinsic disorder enabling protein functions that cannot be facilitated by structure alone.
6. FUNCTIONAL PROTEIN DESIGN
A good example of how a holistic view of protein design can pay dividends are two recent articles that describe how hinge‐mediated domain motions and “loop dynamics” (Corbella et al., 2023; St‐Jacques et al., 2023) play important roles in function. The first paper describes variants of an aminotransferase which are conformationally selected by a non‐native substrate (to engineer substrate promiscuity; St‐Jacques et al., 2023), whereas the second one is a review where importance of conformational plasticity of loops is highlighted in a number of enzymes (Corbella et al., 2023). Often, the loops and hinges are relatively less structured parts of otherwise structured proteins (Corbella et al., 2023; St‐Jacques et al., 2023).
Even more disordered than loops and hinges are peptides known as entropic bristles, which can enhance solubility of a protein by their presence and thus decrease its vulnerability to aggregation (Grana‐Montes et al., 2014; Michiels et al., 2020; Santner et al., 2012; Uversky, 2015a). Copying this strategy, it has been shown that the protein solubility can be enhanced by inserting these as fusion tags (Santner et al., 2012). Translational fusion of entropic bristles (EBs); that is, highly charged intrinsically disordered tails, to a set target proteins was shown to cause efficient solubilization of recalcitrant proteins (Santner et al., 2012). Such EBs acted as effective solubilizers by creating both a large favorable surface area for water interactions and large excluded volumes around the partner (Santner et al., 2012). They were more efficient solubilizers compared to frequently used fusions such as maltose‐binding protein, glutathione S‐transferase, thioredoxin, and N utilization substance A. Since artificial EBs, being characterized by a low level of sequence complexity and a high net charge, can be diversified by means of distinctive amino acid compositions and lengths, this technology can be adopted to any difficult‐to‐solubilize protein (Santner et al., 2012). This work represented “the first de novo design of disordered domains that carry out a prespecified, biologically useful function, namely solubility enhancement” (Santner et al., 2012). In line with these observations, Jo (2022) has shown recently that a 53‐amino acid long disordered peptide named NEXT improved both expression and solubility of target proteins, which included carbonic anhydrase and polyethylene terephthalate‐degrading enzyme.
In yet another example where intrinsic disorder has been exploited in protein engineering, Sormanni et al. (2015) proposed a disorder‐based protocol for rational design of antibodies capable of binding to almost any chosen disordered epitope in a protein, where complementary peptides targeting a selected disordered epitope are designed and grafted on an antibody scaffold. Using examples of three disease‐related IDPs, α‐synuclein, Aβ42, and IAPP, antibodies designed in this way were shown to bind their targets with good affinity and specificity (Sormanni et al., 2015). The team of Bogdan Melnik revealed that the outputs of the per‐residue disorder predictors can be used to find the weakened sites in proteins, evaluate the effects of single mutations on protein stability (Melnik et al., 2011; Nagibina et al., 2019), and to design stabilizing cysteine bridges (Melnik et al., 2012; Nagibina et al., 2019, 2020, 2016). Schnatz et al. (2020) showed that an allosteric ligand‐ and counterion‐gated conformational molecular switch could be created from a protein by greatly increasing its net charge using surface supercharging. Resulting designed highly charged proteins were capable of reversible unfolding at low ionic strength and underwent the ligand‐induced folding, thereby acting as heterotropically activated allosteric conformational switches, where binding of one ligand activated the binding of different ligand or substrate (Schnatz et al., 2020).
Besides these outcomes of exploitation of disorder in vivo and in vitro; disorder is also behind the strategy that cells employ to create micro‐reactors temporarily; these are called membrane‐less organelles (MLOs) to distinguish these from the permanent cellular organelles enclosed by the biomembranes, which have been known since much longer times.
7. LIQUID–LIQUID PHASE SEPARATION, MEMBRANE‐LESS ORGANELLES, AND BIOMOLECULAR CONDENSATES
It is now well established that cells have numerous membrane‐less organelles (MLO), which exist as liquid droplets or biomolecular condensates. Important examples of such organelles include nucleoli, centrosomes, Cajal bodies, and stress granules to name a few (Brocca et al., 2020; Hyman et al., 2014;Ross & Cascarina, 2023; Shapiro et al., 2021; Uversky, 2022). These condensates are formed by liquid–liquid phase separation (LLPS) largely driven by IDPs because their multivalent weak interactions with other molecules drive this process. These interactions compensate for the decrease in entropy due to demixing leading to the liquid–liquid phase separation. LLPS is initiated by the changes in the concentration of the molecules in the cytoplasm/nucleoplasm. The biogenesis of most MLOs is a reversible and tightly regulated process (Ross & Cascarina, 2023; Shapiro et al., 2021; Uversky, 2022).
The importance of biological liquid–liquid phase separation (LLPS) has been recently discussed in two books (Ross & Cascarina, 2023; Uversky, 2022). Another excellent review on LLPS, which includes engineering disorder for useful functional applications of LLPS is also available (Shapiro et al., 2021). As the authors list, LLPS is important in the contexts of “homeostasis, stress responses, cell differentiation and disease”. The review is also valuable for its projection of emerging and futuristic applications of engineering capability of LLPS in proteins (Shapiro et al., 2021).
Schumbera et al. (2023) by looking at the sequences of Rho protein from Bacteroides thetaiotaomicron (involved in transcription termination by binding RNA) suggested that during evolution, bacteria can gain IDRs in some of their proteins to better respond to the environmental cues, such as starvation. In this specific case, by gaining IDRs, the Rho protein became capable of LLPS, with phase separation being accompanied by increase in its activity during starvation (Krypotou et al., 2023; Schumbera et al., 2023). Based on these observations, the authors concluded that “a highly conserved protein can acquire new regulatory properties in evolution by gaining an IDR that leads to protein phase separation” (Schumbera et al., 2023).
A recent bioinformatics study of amino acid sequences of folded proteins, IDPs/IDRs, and phase‐separating proteins along with the behavior of some homo‐ and heteropolymers of amino acids concluded that both hydrophobic and hydrophilic interactions contribute to phase separation (Ibrahim et al., 2023). The authors pointed out that “This result is similar to conclusions from analyses of protein structures…, where Trp, Cys, Phe, Ile, Tyr, Val, Leu, and Asn are enriched in folded proteins (order promoting), while Ala, Arg, Gln Pro, Glu, Lys, Gly, and Ser are enriched in IDPs (disorder promoting), and His, Met, Thr, and Asp are ‘ambiguous’” (Ibrahim et al., 2023). On the other hand, Poudyal et al. (2023) find that disorder is not always necessary to drive phase separation. Using PEG 8000 as a crowder with 23 proteins/peptides of diverse sequences and structure/disorder, they observed that all could form liquid droplets but at different minimum protein concentrations (Poudyal et al., 2023). They point out that while cellular concentrations of individual protein are time‐dependent, most proteins in human proteome exist at the concentrations near to their solubility limits. While it does not rule out that disorder can facilitate LLPS, it does reinforce that binary of structure vs. disorder even in the context of LLPS is on shaky grounds (Poudyal et al., 2023). Strictly viewed as a property of proteins, both structured and disordered proteins can display LLPS. This work also highlights that classical enzymology based on results obtained with dilute protein solutions in aqueous buffers may have been a good start but we need studies under conditions closer to cellular conditions (Poudyal et al., 2023). However, this might represent a challenging task, as even simulating crowded conditions of the cell can be challenging (Gupta & Uversky, 2023c). In fact, the intracellular environments of proteins are quite crowded, and this results in their structures and functions being different from those observed in their dilute solutions, which are often used in enzymology. This macromolecular crowding affects both structured proteins, their IDRs (if present), and IDPs (Gupta & Uversky, 2023c).
A recent paper by Arora et al. (2023) shows again that structure and disorder actually may have synergy in LLPS. SUMO (small ubiquitin‐like modifier) itself is a compact and fairly rigid protein that can efficiently act as an LLPS regulator. Post‐translational tagging of SUMO to IDPs actually regulates their LLPS efficiency and formation of membrane‐less condensates (Arora et al., 2023). This work found that under crowded conditions, SUMO1 with an N‐terminal IDR displayed efficient LLPS leading to the formation of micrometer‐sized liquid‐like condensates in the presence of inert crowders under physiological conditions (Arora et al., 2023). What was remarkable was that even without the IDR, SUMO1 exhibited LLPS, showing that crowded conditions (which anyway prevail in intracellular environments) can drive LLPS even for structured proteins (Arora et al., 2023).
A recent pre‐print reported that IDRs found in proteomes of the two yeasts (Saccharomyces cerevisiae and Neurosporra crassa), made their host proteins more refoldable from the denatured state (To et al., 2023). Furthermore, almost all yeast proteins that contain IDRs and form condensates during heat shock were shown to refold after dissociation from the assembly. The authors also found that Hsp104, the unfoldase, plays the key role in dis‐assembly of condensates and refolding of the proteins (To et al., 2023).
The excellent review by Teilum et al. (2021) made a strong case for intrinsic disorder not being a necessary requirement for LLPS. Supported by examples, these authors suggested that the structural flexibility of a protein and its propensity for multivalent interactions, and not necessarily intrinsic disorder per se (that represents an extreme case of flexibility), which are key to LLPS (although disordered linkers play additional roles in this process; Harmon et al., 2017). According to these authors, LLPS has the following opposing consequences for the specificity of protein–protein interactions, which is partly based on the availability of competing ligands. On the one hand, compartmentalization in a spatiotemporal manner makes many potential competing ligands inaccessible to the protein inside the condensate. On the other hand, the increase in the effective concentration of the partnering ligand(s) in the confined space increases the specificity (Teilum et al., 2021).
More recently, Otis and Sharpe (2022) have investigated the effect of ions ranked according to the Hofmeister series on the LLPS propensity of the polypeptides derived from the pro‐resilin, an insect protein with LLPS‐driven thermo‐responsive self‐assembly leading to the formation of an elastic material resilin. The authors showed that the LLPS efficiency is controlled by the complex interplay between the solvent, sequence syntax, structure, and dynamics (Otis & Sharpe, 2022). In fact, the LLPS efficiency of the studied resilin‐like‐polypeptides (RLPs) derived from the domains 1 and 3 of D. melanogaster pro‐resilin, was promoted by acidic pH and kosmotropic salts, whereas chaotropic salts showed more complex effects (Otis & Sharpe, 2022). Considering the effect of ions in the Hofmeister series on protein solubility/precipitation, stability and behavior in different contexts continue to be an active area of interest, such observations again are useful in looking at structure and disorder in a holistic manner (Bruce et al., 2020; Luong, 2021). Slowly, increasing understanding of how salts affect IDPs/IDRs and their function is emerging (Wicky et al., 2017; Wohl et al., 2021).
Having discussed examples of how disorder (often in synergy with structure) affects function and physico‐chemical properties of proteins, it is time to look at how disorder actually results from the amino acid compositions of IDP/IDRs.
8. SOME AMINO ACIDS ENABLE INTRINSIC DISORDER IN PROTEINS
The folding of a globular protein proceeds through three well‐identified intermediates called pre‐molten globule (PMG), wet molten globule (WMG), and dry molten globule (DMG) (Gupta & Uversky, 2023b). DMG is closest to the native structure of an ordered globular protein and has the hydrophobic core well shielded from solvation in place. This highlights the importance of the kind of amino acids, which often are part of such hydrophobic cores in the formation of the structured proteins.
When we talk about the low sequence complexity of IDPs/IDRs (especially those with extended disorder), we imply that their sequences are deficient in hydrophobic amino acids, such as Ile, Leu, Val, Phe, and Trp. IDPs/IDRs are indeed found to be depleted in these as well as Cys and Asn (Bhowmick et al., 2023; Campen et al., 2008; Dunker et al., 2001; Radivojac et al., 2007; Vacic, Uversky, et al., 2007; Williams et al., 2001). On the other hand, comprehensive computational analysis revealed that even well‐folded ordered proteins do not always use the whole set of 20 amino acids, being characterized by the lower bounds for the alphabet size and Shannon's information entropy of 10 and ~2.9, respectively (Romero et al., 1999). Despite their noticeable amino acid compositional biases, IDPs and IDRs were shown to be very different from randomly generated sequences, with their deviations from random distributions being at least as great as that of ordered domains, indicating strong evolutionary pressure for disorder‐based functionality (Teraguchi et al., 2010). This idea is further supported by the observation that the amino acid sequences of IDPs/IDRs are characterized by the presence of nonrandom binary patterns (Cohan et al., 2022). The lack of universality of the amino acid compositions of IDPs and IDRs is illustrated by the presence of noticeable differences in the amino acid compositions of long and short IDRs (Radivojac et al., 2004; Romero et al., 1997), as well as differences between fully disordered proteins, short IDRs, long IDRs, and binding IDRs (Zhao & Kurgan, 2022).
It was indicated that ordered (or compact) proteins and IDPs with extended disorder (i.e., native coils and native PMGs) can be reliably discriminated based on their charge and hydropathy, with such IDPs being characterized by a combination of low hydrophobicity and high net charge (Uversky et al., 2000). Therefore, this compositional bias represents a simple first‐principle‐based prerequisite for intrinsic unfoldedness, as high net charge leads to charge–charge repulsion, and low hydrophobicity means less driving force for protein compaction (Uversky et al., 2000). However, it was also emphasized that the average size and shape of IDPs can be noticeably affected by the distribution of charged residues within their sequences (Bianchi et al., 2022; Das & Pappu, 2013; Holehouse et al., 2017; Mao et al., 2010). It was shown that since the net charge per residue modulates conformational ensembles of IDPs, polymeric phase behavior of proteins can be predicted from simple sequence characteristics in a form of the schematic phase diagram, with the three axes being mean hydrophobicity (⟨H⟩) and the fraction of positively and negatively charged residues, f +, and f −, respectively (Mao et al., 2010). Furthermore, the conformational preferences of strong polyampholytes (i.e., IDPs with sequences that include large quantities of both positively and negatively charged residues) are determined by a combination of fraction of charged residues values and the linear sequence distributions of oppositely charged residues (Das & Pappu, 2013). The proposed patterning parameter κ has low values for well‐mixed sequences, whereas its high values reflect segregation of oppositely charged residues within linear sequences (Das & Pappu, 2013). IDPs with sequences characterized by low κ‐values are expected to behave as either self‐avoiding random walks or generic Flory random coils, whereas sequences with high κ‐values form hairpin‐like conformations caused by long‐range electrostatic attractions induced by conformational fluctuations (Das & Pappu, 2013). The authors indicated that “that naturally occurring strong polyampholytes have low κ‐values, and this feature implies a selection for random coil ensembles” (Das & Pappu, 2013).
The importance of aromatic residues and cysteine for structure of proteins is supported by the results of the comprehensive computational analysis of PDB and 817 proteomes from all domains of life, which revealed that proteins that do not contain cysteine and aromatic residues (CFYWH‐depleted), being relatively rare (they account for about 0.05% of proteomes), are virtually never found in PDB (Yan et al., 2020). These observations indicated that structure of monomeric proteins is crucially dependent on the presence of cysteine and aromatic residues (Yan et al., 2020). On the other hand, interfaces of the three subtypes of the disorder‐based binding sites known as molecular recognition features (MoRFs), which are IDRs undergoing binding‐induced folding into α‐helices (α‐MoRFs), β‐strands (β‐MoRFs), or irregular structures without a regular pattern of backbone hydrogen bonds (ι‐MoRFs), were shown to be generally enriched in residues that are typically buried within structured proteins and depleted in residues that are typically exposed (Vacic, Oldfield, et al., 2007). Based on these observations it was concluded that these compositional peculiarities of MoRF interfaces define high propensity of these segments to form complexes and thereby bury these residues (Vacic, Oldfield, et al., 2007).
Curiously, it was pointed out that ordered globular proteins capable of forming compact intermediate state(s) under equilibrium conditions in vitro can be differentiated from the globular proteins that do not have such intermediates by their position within the sequence charge‐hydrophobicity space, with proteins that do not have equilibrium intermediates being less hydrophobic and more charged than proteins forming equilibrium intermediate states (Uversky, 2002c). These observations suggested that the ability of a globular protein to form equilibrium partially folded states is likely to be defined by its content of hydrophobic and charged residues rather than by the specific positioning of amino acids within the sequence (Uversky, 2002c). It is hence not surprising that many IDPs with compact disorder actually occur as molten globules (classical MGs are close to WMGs) and even in the case of engineered molten globule of dihydrofolate reductase, transition to the native ordered structure upon binding to the substrate has been reported (Gupta & Uversky, 2023b). The similarity between molten globules of structured proteins and IDPs with compact disorder indicates that the binary of structured proteins and disordered proteins is based upon an artificial boundary and unification by removing the wall maybe desirable.
Overall, typical IDPs/IDRs have fewer amino acids in their makeup than ordered proteins, with the side chains of the amino acids that are enriched in IDPs/IDRs promoting disorder. A ranking of disorder‐promoting ability has been reported as follows (Radivojac et al., 2007; Theillet et al., 2013; Uversky, 2013a, 2015b; Vacic, Uversky, et al., 2007; Williams et al., 2001):
Pro > Glu > Ser > Gln > Lys > Arg.
Let us look at how these amino acids promote disorder and are part of the disorder‐function paradigm. We will find that in reality, it is not very different from structure–function paradigm. The idea of devoting attention to individual disorder‐promoting amino acids is to underline that it is merely a case of different kinds of primary sequences containing different information content lending more versatility to the proteins as molecular machines.
8.1. Glutamic acid
Glutamate (Glu) is reported to rank second among the disorder‐promoting amino acids (Uversky, 2013a). Curiously, although Glu is one of the most enriched amino acids in IDPs/IDRs, the chemically similar amino acid aspartate (Asp) is enriched noticeably less (Roesgaard et al., 2022).
Tompa (2002) suggested that IDPs/IDRs can be organized into five functional classes: entropic chains (which include bristles, linkers, and springs), effectors, scavengers, assemblers, and display sites. It is known that Glu contributes importantly to the formation of entropic bristle domains (EBDs; Uversky, 2013a). Jan H. Hoh, far back in 1998, had proposed the concept of EBD, according to which even in structured proteins thermal factor leads some peptide segments to form a “time‐averaged three‐dimensional domains”, which can be either in an enthalpy‐driven structured conformation or entropically driven disordered form (Hoh, 1998). In their extended form, EBDs occupy a relatively large space, which may be used to regulate protein–protein interactions and confer mechanical properties to proteins (Hoh, 1998). Overall, EBDs beautifully illustrate the classical notion of enthalpy–entropy compensation (Li et al., 2021). EBDs are thus an extension of conformational selection model, suggesting another possible conformation in equilibria for proteins with such domains. More relevant to the theme of our article, a continuum model unifies all such concepts in which an amino acid sequence (along with the environments and conditions) decides the extent of compactness, flexibility, or disorder.
EBDs embody the usual advantage of disorder by regulating the formation of interfaces and thereby the binding of the ligands on EBDs (Uversky, 2013a). As it was already mentioned, a powerful application of EBDs is that their use as fusion tags prevents protein aggregation (Santner et al., 2012). These fusion tags include Glu along with Pro, Gln, and Ser (Santner et al., 2012). Recently, it has been shown that entropic bristles flanking the aggregation prone core increase the infectivity of prions (Michiels et al., 2020). This is interesting in a view of IDPs being associated with pathological aggregation and especially amyloid formation. Again, it is noteworthy that all kinds of disorder in proteins should be viewed as just a translated information from the amino acid composition, just like one would in the case of structural motifs associated with structured proteins. A continuum model underlines this very well.
8.2. Proline
As a known structure‐breaker in structured proteins, Pro is expected to be an important disorder‐promoting amino acid. Theillet et al. (2013) provided a fairly comprehensive review of its importance in both structures and disorders in proteins. So, we will here mostly restrict ourselves to more recent insights on its role in disorder. Ahuja et al. (2016) have questioned the concept of Cistausis suggesting that the cis conformation of Pro is a key for tau protein aggregation causing pathological consequences such as Alzheimer's and traumatic brain injury. After looking at many sequences of functional tau fragments, they did not find high number of cis conformation in Thr231–Pro232 segment (Ahuja et al., 2016). Recently, an NMR study showed that at least in some IDPs, ratio of cis/trans conformations of Pro depends upon occurrence of aromatic and charged side chains in the neighboring sequences (Sebak et al., 2023). Also, Mateos et al. (2020) studied an IDP osteopontin by NMR and found Pro having a role in nucleation of its central compact region. This is unlike the frequent role of proline‐rich motifs in extended conformation. Therefore, Pro can both compact and extend protein chains (Mateos et al., 2020).
8.3. Serine
Serine ranks third in many estimates of ranking of disorder‐promoting amino acid (Uversky, 2015b). In structured proteins, Ser is mostly found on the surface, but is also known to be buried in a few cases with 0.2 kcal/mol as the estimated value as a cost for that (Bordo & Argos, 1991; Karplus, 1997). Ser is a hot spot for mutation except at the sites where it undergoes PTM, especially phosphorylation. It prefers β‐turns and destabilizes α‐helices, except when it is at the end, with Ser‐X‐X‐Glu being an N‐capping motifs for many alpha α‐helices (Aurora & Rose, 1998; Lu et al., 1999; Zhou et al., 1994). It is often found at turns and loops and even when present as the key active site residue, it is located at a sharp turn at the tip of the strand‐turn‐helix motif, called the “nucleophile elbow” or “serine elbow” (Nardini & Dijkstra, 1999; Uversky, 2015b).
Coming to its important roles in protein disorder, many proteins of the signaling pathways connected with cell growth, differentiation, and stress response have PEST sequence, which constitutes a degradation signal (Rechsteiner & Rogers, 1996). Ser is a part of PEST (Pro, Glu, Ser, Thr) motif, which controls protein degradation via ubiquitin degradation pathway or calpain cleavage (Belizario et al., 2008; Rechsteiner & Rogers, 1996; Rogers et al., 1986; Singh et al., 2006). PEST sequences are part of IDRs (Singh et al., 2006).
Importance of Glu and Ser in artificial EBDs has been discussed earlier (Santner et al., 2012). Many neurofilament proteins, which contain long natural EBDs (Brown & Hoh, 1997), besides being enriched in Glu residues, also have high Ser content (Geisler et al., 1984).
Polyserine linkers (PSL) in bacterial proteins as IDRs act as flycasters for binding of the domains containing them with other proteins (Howard et al., 2004). Polyserine tracks (PSTs) containing 10 or more consecutive Ser residues were found in 59 human proteins (Huntley & Golding, 2006). Many of those are involved in signaling, transcription control, DNA binding, and other diverse protein–protein interactions (Huntley & Golding, 2006). SRm160/300 splicing coactivator, which processes pre‐mRNA, is rich in Ser (serine accounts for 16.7% and 23.3% of residues in SRm60 and SR300, respectively; Blencowe et al., 2000).
Ser undergoes numerous PTMs, such as phosphorylation, O‐glycosylation, N‐acetylation, O‐acetylation, phosphopantetheinylation, autocleavage, N‐ADP‐ribosylation, amidation, N‐decanoylation, O‐octanoylation, O‐palmitoylation, and sulfation (Uversky, 2015b).
Basile et al. (2019) estimated that an important factor contributing to more disorder among eukaryotic proteins (as compared to prokaryotic proteins) is that former contains more and larger linkers connecting Pfam domains. These authors reported that three amino acids contribute to the difference in disorder, serine (8.6 vs. 6.5%) and proline (5.4 vs. 4.0%) are more abundant in eukaryotic linkers, while isoleucine is less frequent (5.3 vs. about 7.5%; Basile et al., 2019). This observation is illustrated by Figure 2 showing some properties of protein regions from different kingdoms.
FIGURE 2.
Frequency of (a) serine, (b) proline, and (c) isoleucine in different secondary structures in proteins from eukaryotes (dark green), bacteria (red), and Archaea (blue). Error bars represent the standard error for each property (Reproduced from Basile et al. (2019), under CC 4.0 attribution license).
8.4. Arginine
Among the key functional involvements of IDPs/IDRs are their established roles in protein–protein interactions. On the surfaces interacting with IDPs, Trp occurs most frequently and is followed by Arg (Jones et al., 2019; Jones & Thornton, 1997). The adequate hydrophobicity and flexibility enable Arg for this stellar role (Bhowmick et al., 2023). Recently, the π‐bonds of its guanidino group, already well known for its role in cation–π interactions, have also been reported to be responsible for fibril formation by stacking (Ferrari et al., 2020; Gallivan & Dougherty, 1999).
While considering the importance of cation–π interactions, it is important to consider the roles of Tyr and Trp in these interactions with Arg during protein–protein interactions. Jubb et al. (2015) have discussed that Tyr and Trp are among the most conserved amino acids in short foldable sequences of low complexity, thereby providing further support to the earlier observations that α‐MoRFs are effectively depleted in aromatic residues, whereas β‐MoRFs and ι‐MoRF partners are enriched in these residues, and that there is a notable asymmetry in the aromatic content in all MoRF‐partner pairs, where one member of the complex has a larger composition of aromatic residues than the other (Vacic, Oldfield, et al., 2007). The hot spots constituted by these sequences have been targeted for drug design (Blundell et al., 2020). Recently, a comprehensive review on different roles of Arg in biology has been published (Gupta & Uversky, 2024).
8.5. Glutamine
The roles of sequences rich in glutamine and polyglutamine in so‐called polyglutamine diseases have been extensively investigated, with the most studied glutamine‐related disease/protein dyads being Huntington's disease—huntingtin, Kennedy's disease—androgen receptor; spinocerebellar ataxia—ataxin‐1, and dentatorubral‐pallidoluysian atrophy—atrophin‐1 (Lieberman et al., 2019). In these inherited polyglutamine diseases originating from CAG/polyQ repeat expansions, the neurotoxicity (and often the age of the disease onset) correlates with the length of consecutive glutamine tracts in the corresponding proteins (Lieberman et al., 2019). Some finer details of its role in aggregation associated with these diseases have begun to emerge (Barrera et al., 2021). Initially, it starts seeding the aggregate by association of monomeric peptides. As nucleation proceeds further to form larger aggregates, buried Gln residues optimize the H‐bond network inside these aggregates (Barrera et al., 2021). Furthermore, exceptional H‐bonding abilities of both Gln and Asn have been implicated in protein folding diseases, bacterial biofilm formation, and prion‐forming domains (Halfmann et al., 2011). Asn has greater propensity to be at turns of protein chains as compared to Gln. It has been suggested that this is responsible for Asn forming benign self‐templating amyloids and Gln forming toxic nonamyloid oligomeric species (Halfmann et al., 2011).
9. GLYCINE
Gly along with Pro are frequently found in loops and turns in proteins and contribute to the disorder content (Krieger et al., 2005). Morris et al. (2021) have pointed out that Gly with minimum steric hindrances offered by its side chain contributes to high conformational freedom and hence is often found in IDPs/IDRs. Elastomeric proteins have high content of both glycine and proline (Theillet et al., 2013). Furthermore, high Gly content in a protein favors LLPS and promotes protein aggregation/fibrillation. This is illustrated by the protein fused in sarcoma (FUS), which is unique in having poly‐Gly tracts, which are implicated in initiating the self‐assembly of the protein to form fibrils (Kar et al., 2021).
9.1. Cysteine
We are concluding this section with a brief consideration of cysteine, which forms inter‐ and intramolecular disulfide bridges, or is involved in the coordination of different prosthetic groups (e.g., Zn2+ ions in zinc‐fingers), or is subjected to numerous PTMs, and is therefore generally associated with lending structural stability, thus being considered as the most order‐promoting residue (Dunker et al., 2001; Radivojac et al., 2007; Romero et al., 2001; Vacic, Uversky, et al., 2007; Williams et al., 2001). Contrarily to this generally accepted classification, cysteine was shown to be located in the middle of the TOP‐IDP amino acid scale that was designed to efficiently discriminate between order and disorder (Campen et al., 2008). Furthermore, Bhopatkar et al. (2020) indicated that many IDPs and IDRs are interspersed with cysteins and that cysteine‐rich sequences might display significant disorder in the reduced but not the oxidized form, suggesting that such conditional IDRs can function in a redox‐sensitive manner, undergoing both disorder‐to‐order and order‐to‐disorder transitions in response to changes in the cellular redox status. In line with these considerations, ~5% and 30% of the yeast and human proteomes correspond to the proteins with redox‐sensitive, cysteine‐rich sequences (Erdos et al., 2019). A comprehensive review by Bhopatkar et al. (2020) contains numerous examples, where Cys in reduced form is present in variety of disordered parts of many motifs and domains. In fact, Cys is also an important part of several redox‐regulated conditionally disordered proteins, such as Hsp33 (Reichmann et al., 2012), Cox17 (Fraga et al., 2017), and CP12 (Gontero & Maberly, 2012; see below for a discussion of the conditionally disordered proteins).
As is well‐known in structural biology, it is not the amino acid composition but the primary sequence, which dictates the structure and hence function of the ordered proteins. Let us now discuss this in the context of proteins with intrinsic disorders.
10. HIERARCHY OF DISORDER
Kaj Ulrik Linderstrøm‐Lang (1896–1959) introduced the terms primary structure, secondary structure, and tertiary structure (Edsall, 1959; Linderstrøm‐Lang, 1952; Scheraga, 1992). Much of the structural biology, driven by the results from x‐ray diffraction studies has been devoted to description of protein folding in terms of various types of secondary structure and tertiary structure of individual proteins T, The unsructure instead of secondary structure and tertiary structure is discussed in terms of disorder, which has its own descriptive terms: semi‐foldons, non‐foldons, inducible foldons, and unfoldons (Uversky, 2013b, 2015c, 2016a). Foldons are independently foldable units; inducible foldons are intrinsically disordered regions, which get either partially or completely folded during the interaction with binding partner. There are also morphing inducible foldons, which fold differently while interacting promiscuously with different binding partners. Non‐foldons, on the other hand remain disordered even after a binding. Similarly, semi‐foldons remain partially disordered. Unfoldons undergo order → disorder transition to become functional. The concept of foldons expands the conformational dynamics narrative and includes both structural and disordered regions being in equilibrium (Uversky, 2013b, 2015c, 2016a).
Structural classification of proteins (SCOP) has four levels of hierarchy: family, superfamily, fold, and class (Andreeva et al., 2020; Murzin et al., 1995). Perhaps, time has come to bring in semi‐foldons, non‐foldons, inducible foldons, and unfoldons and integrate these into it along with fold to create a common narrative for structure and disorder. The seminal review of van der Lee et al. (2014) is helpful in this context of understanding disorder as an “extension of structure–function paradigm”.
van der Lee et al. (2014) visualize proteins are modules of structured and disordered regions. At this point, it is prudent to mention that the term “module” has been used rather loosely in the context of protein structure. Sometimes, the word module has been used interchangeably with domains (Lesk, 2010). On the other hand, Petsko and Ringe (2004) while discussing the modular nature of proteins stated “…insertion of a new exon into an existing domain…”. Actually, the concept of module was suggested by Traut (1986) who thought of “exon‐coded modules” as having “a unique function, such as the ability to bind a specific ligand” (Traut, 1988). Altogether different connotation is “Three general classes of modular biocatalysis can be identified: enzymes in which catalysis and substrate specificity are separable, multisubstrate enzymes in which binding sites for individual substrates are modular, and multienzyme systems that can catalyze programmable metabolic pathways” (Khosla & Harbury, 2001). Therefore, the point is that even for structured proteins, meaning of some terms goes on evolving and sometimes is a matter of context. So, as time goes by, we should see a similar discourse happening to the terms associated with hierarchy of intrinsic disorder.
Approaches like the one used by Bajaj et al. (2022), which can distinguish functional determinants irrespective of their solvent accessibility, should help in integrating the concept of functional units across the spectrum of structure/flexibility/disorder. In fact, going a step further than van der Lee et al. (2014) and the general impression that there are structured proteins (with no disorder) and IDPs (with no structure), we should recognize that such examples are not common. Enzymes, which are considered to rely upon structure, actually include ones, that have IDRs (loops and linkers) that play a number of important roles in the catalytic process (Babu, 2016; Feller & Lewitzky, 2012). In fact, despite the fact that for a long time, enzymes have been considered an exception to the rule of protein intrinsic disorder due to the structural requirements for catalysis, a comprehensive bioinformatics analysis revealed that IDRs in enzymes “occur at similar lengths as in non‐enzymes, and are correlated with unique functions that parallel IDRs in non‐enzymes” (DeForte & Uversky, 2017). Hence, it is more logical to talk of “structured proteins with varying degree of disorder and IDPs with extreme level of disorder” rather than “structured proteins and IDPs”!
It turns out that from the functional point of view, IDRs are more versatile and more amenable to evolutionary forces and hence confer an advantage of better and faster adaptability to changing environments of the niche, in which the organisms have to survive (Ahrens et al., 2017; Brown et al., 2002, 2011; Fahmi & Ito, 2019; Xue et al., 2013).
One should also keep in mind that the information content of the protein sequence is not limited to coding for folding patterns/capability as discovered by Anfinsen. In fact, it is further extended via the precise orchestration by PTMs (frequently in a reversible way at sites where and when it is tremendously important for regulation). IDRs, with greater accessibility to the modifying enzymes (and the necessary chemical entities), frequently are the sites of PTMs (Darling & Uversky, 2018; Iakoucheva et al., 2004; Pejaver et al., 2014; Uversky, 2013c; Xie, Vucetic, Iakoucheva, Oldfield, Dunker, Uversky, & Obradovic, 2007). In fact, because PTMs can affect protein activity, folding, interactions, localization, stability, and turnover, they are crucial for the protein structure–function continuum, where generation of the multiple proteoforms of a given protein by various mechanisms (including PTMs) defines the ability of a protein to have a multitude of structurally and functionally different states, proteoforms (Uversky, 1874, 2015c, 2016a, 2016b). Furthermore, PTMs themselves can have rather diverse structural consequences. Phosphorylation, for example, can affect the disorder differently depending upon the original charge on IDRs (Figure 3; Jin & Grater, 2021). In fact, depending on the charge state of an unmodified IDR/IDP, either compaction/shrinkage or expansion/swelling can be induced by phosphorylation (Jin & Grater, 2021). With real proteins, the effects may be somewhat more complex but the drastic results of PTMs can be anticipated from this simple illustration. In line with an expected complexity of the response of a disordered polypeptide chain to multiple phosphorylation events, the all‐atom molecular dynamics simulations of phosphorylated and non‐phosphorylated forms of five disordered peptides originated from tau, statherin, and β‐casein revealed that “the net charge is not enough to predict the impact of phosphorylation on the global dimensions. Instead, the distribution of phosphorylated and positively charged residues throughout the sequence has great impact due to the formation of salt bridges” (Rieloff & Skepo, 2021). From a more general perspective, it is clear that phosphorylation represents an important means for tightly controlled remodeling of the conformational landscape explored by IDPs (Kumar & Thompson, 2019). A recent comprehensive review by Newcombe et al. (2022) provides a detailed view of how phosphorylation impacts intrinsically disordered proteins and their function.
FIGURE 3.
Scheme of the potential effect of phosphorylation on the global conformation of IDPs. Assuming electrostatics to be the major determinant, an overall neutral or negatively charged IDP swells upon phosphorylation, while a positively changed IDP shrinks accordingly. Reproduced from Jin and Grater (2021) under CC 4.0 attribution license.
In IDPs, short (3–10 amino acids long) linear peptide motifs (SLiMs, which have been already mentioned in the section “Interactions of IDPs/IDRs with other proteins and surfaces in vitro and in vivo”) often have autonomous functional capabilities (van der Lee et al., 2014). This is more a virtue enabled by disorder rather than a very new concept, short sequences of active centers of enzymes carry out the function, and many biologically important peptides have been known for a long time. The concept of a conformation as a function of time is already recognized. We might as well extend the meaning of conformation to include disordered segments, which can interconvert faster because of the low activation barrier among various proteoforms. These SLiMs as functional units offer several advantages (Diella et al., 2008; Tompa et al., 2014; Van Roey et al., 2012, 2014; Via et al., 2011). Given their limited number of interacting surfaces, PTMs of their residues have more drastic consequences (Babu, 2016). Therefore, these features are very well suited to functioning as molecular switches for reaction pathways/cascades. SLiMs occur repeatedly, turning low affinity into avidity, the importance and theoretical framework of which in the context of biological systems was reviewed by Whitesides' group quite some time back (Mammen et al., 1998).
IDPs/IDRs have another type of interactive segments, which are longer, (10–70 amino acids long) molecular recognition features (MoRFs) that are disordered regions capable of binding‐induced folding (Cheng et al., 2007; Oldfield et al., 2005) and Pre‐Structured Motifs (PreSMos), which are preformed structural elements in the sense that they represent the transient local structural elements that presage target‐bound conformations and act as specificity determinants for IDP/IDR recognition by target proteins (Kim & Han, 2018, 2021; Lee et al., 2012, 2014; Szollosi et al., 2014). Therefore, MoRFs and PreSMos occur in those IDPs/IDRs that undergo folding upon binding their interacting partner. As it was already pointed out, this disorder → order transition may lead to the formation of α‐heilces, β‐strands, or irregular secondary structures in the bound state (Vacic, Oldfield, et al., 2007). Importantly, a disordered protein, such as p53 (with hundreds of known different binding partners) may form different kinds of secondary structures at different interacting sites, and even one disordered segment of such a protein can fold differently at binding to different partners (i.e., represent an illustrative example of morphing MoRFs; Oldfield et al., 2008).
One should also keep in mind many protein domains have varying extents of disordered regions. In fact, some long, interaction‐prone, disordered protein segments conform to the definition of domains rather than motifs, as they represent functional, evolutionary, and structural units (Tompa et al., 2009). Functions of such intrinsically disordered domains (IDDs), being based on a new kind of interaction principle, are different from the functionality of short motifs and ordered domains (Tompa et al., 2009). Finally, disorder can also occur just before or after ordered protein domains and has functional significance. van der Lee et al. (2014) speculated that these disordered regions evolved by portions of introns becoming exons during evolution.
It was rightly pointed out that the distinctions between SLiMs, MoRFs/PreSMos, and IDDs are not a clear cut. MoRFs/PreSMos, by definition fold upon binding, but about 70% of SLiMs do that as well. IDDs binding to each other involve mutually induced folding. With time, there will be more clarity about the terminology, but the point to note is that these all represent “same continuum of binding mechanisms” by disordered protein segments of varying length (van der Lee et al., 2014).
van der Lee et al. (2014) elaborates upon the continuum model (Dunker, Brown, Lawson, Iakoucheva‐Sebat, et al., 2002; Dyson & Wright, 2005; Fonin et al., 2019; Gupta & Uversky, 2023a; Uversky, 2002a, 2002b, 2013b, 2016a, 2019) to state (van der Lee et al., 2014): “Proteins have been proposed to function within a conformational continuum, ranging from fully structured to completely disordered… spectrum covers tightly folded domains that display either no disorder or only local disorder in loops or tails, multidomain proteins linked by disordered regions, compact molten globules containing extensive secondary structure, collapsed globules formed by polar sequence tracts, unfolded states that transiently populate local elements of secondary structure, and highly extended states that resemble statistical coils … In this model, there are no boundaries between the described states and native proteins could appear anywhere within the continuous landscape” (van der Lee et al., 2014). Hsu et al. (2020) indicated that the order–disorder continuum represents an important means for linking prediction of protein structure with prediction of intrinsic disorder.
In line with all these considerations, Figure 4 represents a generalized (and clearly oversimplified) structure–function continuum model that includes “lock‐and‐key”, induced fit, and folding at binding models. This simple model is not meant to restrict the interaction to induced fit, the “conformation” shown in the illustration can very well be the one selected as per conformation selection hypothesis.
FIGURE 4.
Structure–function continuum model includes lock and key and induced fit model along with the disorder → order transition in protein structure. Although the figure portrays enzyme (E) and substrate (S), by no means this model is limited to the catalytic activity and instead is applicable to any type of functional protein interactions. The flexibility may be limited to obey lock and key hypothesis, whereas extreme disorder may lead to the folding upon binding at MoRF sites. Clearly, both interaction partners should be considered from the perspective of varying flexibility at their binding sites. Furthermore, varying flexibility phenomenon is not only limited to binding sites, as the entire protein can be flexible/disordered to different degree. We would like to thank Ms. R. Sahadevan and Dr. S. Sadhukhan, IIT, Palakkad, India for their help in drawing this figure.
Moosa et al. (2020) discussed marginally stable disordered proteins as a part of the continuum from structured proteins to the unstructured/disordered proteins. The marginally stable disordered proteins, from their description, are what others have referred to as highly flexible (with extreme case being molten globules). The point to be noted here is that there is no binary but a continuum (Moosa et al., 2020). It starts with highly stable compact proteins with their denaturation fitting in well with a two‐step model. At the other end are unstructured proteins but wherein the information for folding in the presence of multiple partners/ligands is very much there. So, in one sense, we can say that the folding code is followed but we have to enlarge it to make it more inclusive of the folding of these conformations (whether those of marginally stable or regular disordered proteins). In short, the information is still there in the primary sequence except it is not restricted to dictate folding (Moosa et al., 2020). A good analogy may be that the words convey the information, not just for prose but for a poetry (with fewer constraints of grammar) as well!
These authors have argued that the presence of trimethylamine N‐oxide (TMAO, which is a metabolite produced by gut bacteria) compacts α‐synuclein differently from other ligands, which means that the folding code for IDPs is partly dictated by the ligand (Moosa et al., 2020). Perhaps, one should distinguish between physiologically relevant ligands and other additives like TMAO. Therefore, it is likely that the “folding code” has evolved for dealing with the physiologically relevant processes. Also, though in a less dramatic fashion, the conformations induced by different ligands in case of the structured proteins are not identical (Moosa et al., 2020). As a continuum model from the perspective of energetics, Moosa et al. (2020) arrange proteins in terms of ΔΔG for the N → D transition: hyperstable folded proteins > stable folded proteins > marginally stable disordered proteins > natively unfolded disordered proteins > hyperdestabilized/functionally disordered proteins. As examples of the last kind, authors have mentioned RPA70 and MAP2‐PD. This classification is noteworthy as it reflects the continuum of stability, where in addition to stable folded proteins like RNase A, we consider the three classes with increasing disorder where natively unfolded proteins (exemplified by tau and α‐synuclein) follow proteins having least thermodynamic stabilities such as RCAM and RPA70.
A key element of the structure (conformation)–function is the small region, where the actual binding of the ligand to the protein occurs to initiate the biological process. It is here that we find that the IDPs/IDRs differ drastically from the structured proteins which bind ligands via a preformed binding site. The next section describes how binding takes place with a disordered region in a protein.
11. PREFORMED BINDING SITE AND INDUCIBLE FORMATION OF BINDING SITES
One key distinction that is often made between the structured proteins and IDPs/IDRs is that the former (especially the enzymes with their active sites endowed with the twin magic of high catalytic rates and specificity) have preformed binding sites for their biologically relevant ligands. While in the induced fit model, the ligands reorganize conformation of the binding site, the conformation selection goes a step even further in the sense that the ligand only selects a pre‐existing conformer, which provides the best fit/optimal binding to the ligand via its pre‐existing binding site. Below we built a case for the gray zone between pre‐formed and not pre‐formed binding site binary being closer to the reality.
An interesting article published by Dagmar Ringe quite some time back suggested that “….proteins are flexible molecules and many regions on their surfaces can adapt their shapes to those of incoming ligands” (Ringe, 1995). That, though written in the context of structured proteins, appears to be a good description of IDPs. The author had pointed out that thrombin can bind to hirudin at two regions although only one of these was binding site, which was part of the active site (Ringe, 1995). Also, the key may be to create optimum local environment in which the substrate can compete with the water molecules bound to the active site.
The second important feature of proteins to be factored in is their nonspecificity. Catalytic promiscuity shown by lipases in catalyzing formation of numerous C—C bonds indicates that the preformed (even if inducible) active sites can not only bind to the non‐native molecules but can also catalyze very different reactions (Kapoor & Gupta, 2012). What is more, catalytic efficiency of these promiscuous reactions can be improved upon by protein engineering and directed evolution. So, the promiscuity shown by IDPs/IDRs in protein–protein interactions is not such a radical departure from the behavior of structured proteins. It is to be noted that catalytic promiscuity is not limited to lipases, and the active site region involved in their hydrolase activity and promiscuous activity is same, and only relative roles of different side chains in the active site are different (Khersonsky & Tawfik, 2010; O'Brien & Herschlag, 1999).
The moonlighting activities are even better example, where more often flexibility or disorder leads to non‐specificity. Moonlighting refers to an enzyme/protein displaying a biological activity different from its usual one. The moonlighting activity can be expressed at a different cellular localization or may be seen in different cell types or even when cellular flux of a ligand changes. The well‐known examples of moonlighting proteins include crystallins, ceruloplasmin, and glycolytic enzymes (Gupta & Uversky, 2023d, 2023e, 2023f). Here, the binding site/active site can be same or even different, proving that the contention by Ringe (1995) was correct. Moonlighting is closer to the catalytic promiscuity in the sense that very different kinds of biological activities are exhibited by very similar kinds of protein molecules (Gupta & Uversky, 2023d, 2023e, 2023f).
Both catalytic promiscuity and moonlighting indicate that the pre‐formed binding sites are quite capable of nonspecificity revealed by IDPs/IDRs [with their MoRFs] during protein–protein interaction. The inherent information to bind is there in both structured proteins and disordered proteins, the kind of amino acids involved are different. Structured proteins are little ahead in the trajectory of crafting binding site. On the other hand, IDPs and IDRs may lag in this respect but gain in having many other functional advantages as mentioned earlier in this review. Structure or disorder is just two different designs with their respective functional attributes. We should also add here that in both designs, behaviors fitting in well with induced fit or conformational selection are known. In some cases, both models are required to describe the trajectory of catalytic/biological activity, the choice sometimes depending upon the ligand (Berger et al., 1999; Cai & Zhou, 2011; Daniels et al., 2014; Greives & Zhou, 2014; Hammes et al., 2009; Mori et al., 2023; Wang et al., 2013).
Therefore, now that the early skepticism and novelty of the occurrence and functions of intrinsic disorder have worn out; as the above discussion shows, they may look very different but both structure and disorder complement each other and often exist together in the same protein.
Not just that, there are structured proteins, which become disordered to become functional! The next section is devoted to this interesting class of proteins, which further shows that both structure and disorder are critically involved in enabling protein function.
12. CRYPTIC DISORDER/CONDITIONALLY DISORDERED PROTEINS
In some cases, proteins show reversible increase in the disorder during their functional phase. This may even include order → disorder transition of a structured protein. The trigger for this may be solution pH, temperature, interaction with membranes, redox status, interaction with proteins and nucleic acids, and PTMs (Jakob et al., 2014). In their comprehensive review of this interesting phenomenon, Jakob et al. claimed: “The function‐related changes range from local partial folding to complete unfolding, and from allosteric transitions to induced fit adjustments in IDPs and ordered proteins” (Jakob et al., 2014). These proteins are called conditionally disordered proteins. The usefulness of this cryptic disorder in metabolic regulation has been discussed recently (Gerard et al., 2022).
Hausrath and Kingston (2017) suggest that the proteins, which display cryptic disorder are marginally stable in their folded state. This fits in well with the “unfoldon hypothesis” discussed by Jakob et al. (2014). According to this hypothesis, structured proteins can be considered to have modules called foldons, which are in equilibrium with their less folded conformations. IDPs, in addition to foldons also have inducible foldons, morphing foldons, semifoldons, and nonfoldons. Incidentally, this accords well with the continuum model, where the entire range of proteins is built of these different modules of varying compactness and stability (Uversky, 2016a, 2013b, 2015c).
The periplasmic chaperone Hde A occurs as an inactive dimer, which dissociates and locally unfolds into active chaperone monomers at pH < 3 (Jakob et al., 2014). This behavior illustrates two recurring features of similar chaperones, which are conditionally disordered proteins. First, these are active under stressed conditions, under which their client proteins need help with refolding. Second, dissociation into monomers/dimers liberates the hydrphobic surface (of the inter‐subunits) for binding to the client proteins. The disorder, of course, helps in its having broad specificity towards a wider range of client proteins. As yet another example of this, Hsp27 is a human small heat shock protein (sHsp) with a structured core of α‐crystallin domain (ACD, in fact, the presence of ACD is a common feature for all sHsps, which are a special class of molecular chaperones that lack an ATPase domain), which dissociates into a monomer, which is partially unfolded under stressed conditions. NMR and bioinformatics suggest that this conditional disorder accounts for the chaperon activity of Hsp27 (Alderson et al., 2020). In fact, a systematic analysis of the intrinsic disorder predispositions of the members of human sHsp family revealed that all of them contain disordered N‐ and C‐termini flanking the ACD, suggesting that the structural flexibility of these tails supports dynamic interactions with clients and other sHsp subunits (Webster et al., 2019). In line with these notions, Xinmiao Fu indicated that in sHsps, functionally important dynamics occur at five levels, such as (1) flexible domains flanking the ACD, (2) polydisperse self‐multimerization, (3) multimerization with other sHsps, (4) subunit exchange, and (5) regulation by the cellular environment including PTMs (Fu, 2015).
Wrighton (2015) cited the example of protein 4E‐BP2, which folds (and becomes functional) upon phosphorylation. The protein 4E‐BP2 controls translation by binding to the eukaryotic initiation factor slF4E. Recently, Smyth et al. (2022) have described that to abolish binding affinity for the initiation factor (and allow translation to proceed), this protein undergoes phosphorylation in a specific sequence at five sites. The last few are at the C‐terminal region which remains disordered and stabilizes the folded structure elsewhere in the protein. This is an interesting example where folding abolishes binding to the partner protein. The authors used fluorescence anisotropy decay and fluorescence correlation spectroscopy to gain insight into the flexibility/disorder in the various regions of this multistate conditional IDP at various stages of phosphorylation (Smyth et al., 2022).
Gondelaud et al. (2023) cautioned that if the protein has two or more cysteins, it is prudent to estimate disorder content under both oxidizing and reducing conditions, as the protein may be a case of redox‐dependent conditional disorder. The caution can indeed be generalized to restate that one should check if a structured protein is in fact a conditionally disordered protein. This also implies that even if the protein occurs in PDB, especially without being complexed with a biologically relevant ligand, we cannot rule out cryptic disorder being in play during its function!
Some members of the superfamily of nuclear receptors have a short sequence of variable length, which is partly disordered (Wiech et al., 2021). The nuclear receptor of malaria‐causing mosquito A. aegypte has one of the longest sequences reported for this region. In a recent report on the metal ion‐induced LLPS and a biomolecular condensate formation, Wiech et al. (2021) mentioned that the cupric ion (and Zn2+ to a lesser extent) induced LLPS. While the physiological implications of this phenomenon are unknown, LLPS are known to be induced under stressed conditions.
The nuclear envelope has nuclear pore complexes (NPCs), which regulate the entry or exit of molecules through it. NPCs consist of nucleoporins (Nups). The Nups lining the central channel of the pore have multiple phenylalanine‐glycine (FG) repeats and are characterized by noticeable levels of intrinsic disorder (Denning et al., 2003; Lyngdoh et al., 2021; Wubben et al., 2020). In fact, biophysical characterization of the structural properties of the purified S. cerevisiae FG Nups in vitro revealed that these proteins are typical IDPs, and are also disordered in situ within the NPCs of purified yeast nuclei (Denning et al., 2003). Importantly, despite being disordered, FG‐Nups clearly show structural heterogeneity, being grouped in molten globule‐like species with low charge and highly charged coil‐like polypeptides (Yamada et al., 2010). The FG repeats enable interaction with hydrophobic patches on the surface of nuclear transport receptors (NTRs), which results in the complex to pass through nuclear pores. The usual advantages of involvement of intrinsic disorder allow interactions with multiple partners and a rapid process time. The signal sequences on NTRs are also disordered with adequate solvent accessibility to facilitate translocation (Wubben et al., 2020). The importance of intrinsic disorder in nuclear proteins is further reflected in the fact that almost all human FG‐Nups contains >50% disordered residues, with Nup98, Nup153, and POM121 being extremely disordered with ~80% disordered residues (Lyngdoh et al., 2021). As always, the disorder also facilitates PTMs, which further regulates the translocation (Wubben et al., 2020). Furthermore, all human FG‐Nups have the potential to undergo LLPS and form liquid droplets that mimic the permeability barrier observed in the interior of NPCs (Lyngdoh et al., 2021; Nag et al., 2022).
So far, we have mostly focused on the roles of intrinsic disorder under the physiological conditions of normal cells/organisms. We briefly discuss below how disorder is very much involved in various diseases and pathologies.
13. DISORDER IN DISORDERS AND (INFECTIOUS) DISEASES
Protein promiscuity powered by flexibility/disorder, especially in protein–protein interactions has also put “one gene–one drug–one disease” concept into question (Blundell et al., 2020; Dunker & Uversky, 2010; Gupta & Roy, 2021; Metallo, 2010; Ruan et al., 2019; Uversky et al., 2008). The roles of intrinsic disorder in protein misfolding and formation of amyloids and prions, which lead to numerous kinds of diseases, continue to be reviewed continuously (Coskuner‐Weber et al., 2022; Kulkarni & Uversky, 2019).
It is known that viruses can subvert transport across the nuclear envelope to hijack the cellular processes of the host. It turns out that quite a few viruses (e.g., adenoviruses types 2 and 5, Dengue and Zika viruses, poliovirus, etc.) exploit the disorder of Nups and affect the functioning of NPCs (Wubben et al., 2020). In fact, intrinsic disorder in viral proteins plays a far wider and extensive role in their infective process and ensuing pathogenesis (Mishra et al., 2020). Recently, liquid–liquid phase separation of viral proteins has been shown to be involved in the viral life cycle within the host cells (Brocca et al., 2020; Saito et al., 2021). The intrinsic disorder is also exploited by SARS‐CoV‐2 to evade immune systems by mutating preferentially at disordered sites of spike and nuclear proteins (Quaglia et al., 2022), as well as to hijack cellular machinery utilizing a multitude of SLiMs in SARS‐CoV‐2 nucleocapsid protein (Schuck & Zhao, 2023).
It is not just diseases and infections, disorder is also an enabler for cells/organisms to survive under other stress conditions, when the environment can be extreme.
14. HOW DISORDER HELPS PROTEINS UNDER EXTREME CONDITIONS?
Many cells and organisms show anhydrobiosis, being able to survive under low water conditions, such as desiccation and freeze‐drying. One well‐known mechanism is their accumulation of osmolytes. The involvement of IDPs/IDRs in anhydrobiosis has been discussed by Chakrabortee et al. (2012) who examined the role of late embryogenesis abundant (LEA) proteins in preventing protein aggregation, which is one outcome of desiccation. These authors showed that these disordered proteins function differently from molecular chaperones and hence they prefer the term “molecular shields” for describing this role of IDPs like LEA proteins. They invoke the “entropy transfer” mechanism, which has been also advanced to explain the chaperone action of IDPs (Chakrabortee et al., 2012). In their recent comprehensive review, Smith and Graether (2022) discussed the crucial roles of intrinsically disordered dehydrins in improving desiccation tolerance in plants.
Another system where IDPs were reported to help in surviving desiccation is the case of tardigrades (microscopic animals also known as water bears). Tardidigrade‐specific IDPs were part of cytosolic abundant heat soluble proteins (CAHS). It was shown that CAHS works in synergy with trehalose to constitute this survival mechanism under water stress (Nguyen et al., 2022). Overall, it was concluded that IDPs, such as LEA proteins, dehydrins, and tardigrade‐specific IDPs play a central role in desiccation tolerance in all species investigated and therefore constitute an important functional group of anhydrobiosis‐related intrinsically disordered (ARID) proteins (Janis et al., 2018). Taking into account this prevalence of IDPs in desiccation combined with the well‐established propensity of many IDPs to undergo LLPS, it was not too surprising to find that LEA‐driven LLPS was shown to promotes animal desiccation tolerance (Belott et al., 2020).
One crucial process in production of many pharmaceutically important protein formulations is freeze‐drying, which subject proteins to the desiccating conditions. It may be interesting to investigate (a) if IDPs survive freeze‐drying better than structured proteins and (b) if inexpensive IDPs can be used as cryoprotectants and/or lyoprotectant during freeze‐drying and concentration of protein pharmaceuticals (Izutsu, 2014; Roy & Gupta, 2004).
Pancsa et al. (2019) have remarked about the “sparseness of data on disordered proteins from extremophiles” but do point out that significant differences in the disorder contents of proteins from thermophiles or radiotolerant organisms and mesophiles do exist. They also observe that disorder content of proteins from halophiles tends to be overestimated because ordered halophilic proteins maintain a highly acidic and hydrophilic surface to avoid aggregation in high salt conditions (Pancsa et al., 2019). Nevertheless, there is some indication that disorder does play a role in the functional capacity of the proteins from halophiles, which again constitute a special realm of survivors of the low water activity conditions (Gloss et al., 2008; Paul et al., 2008; Uversky, 2013d). The need to look more closely at the IDPs in archaea, which survive under many harsh conditions, has been highlighted by Xue et al. (2010).
As we have gained insight into the layered complexities in behavior of disordered proteins/regions, enzymologists have also been investigating how intrinsic disorder affects the fundamental phenomena of biological specificity (and multi‐specificity) of proteins.
15. PROTEIN SPECIFICITY BEYOND LOCK AND KEY HYPOTHESIS
Schreiber and Keating (2011) wrote that in vivo “…proteins can participate in specific interactions with just one or a few partners, in promiscuous yet functional interactions with many partners, and/or in nonspecific interactions with some of the numerous functionally non‐cognate partners”. Specificity is as much about not binding to the other available ligands around it as about binding to a specific ligand. Biologically relevant bindings occur with affinities in the rather wide range of low millimolar to femtomolar. As Schreiber and Keating (2011) point out, in some cases, specificity is achieved by ensuring structural features that suppress nonspecific binding (Schreiber & Keating, 2011). This is particularly true of coiled–coil interactions. Multi‐specificity is possible for even relatively rigid proteins, which leads to the structurally similar complexes but as low water enzymology teaches us, some minimum flexibility is essential for binding (Gupta, 1992; Mukherjee & Gupta, 2015a). However, more structural flexibility allows different residues in and around the binding region to form dissimilar complexes (such as in catalytic or substrate promiscuity). Disorder and PTMs enable collaborating via different protein regions (even simultaneously) to form very different complexes. A good example is that of tumor suppressor protein p53 which interacts with >80 protein partners using its disordered C‐terminal region. In some cases, phosphorylation, methylation, and acetylation mediate or rather facilitate the binding specificity (Schreiber & Keating, 2011).
Two important points made by Schreiber and Keating (2011) are that an interacting surface tends to be conserved but may use different residues for binding and interacting sites co‐evolve. An interesting example cited by these authors is that of a Fab binding to VEGF, HER2, IGF‐1, and protein A. Among the residues of the antibody fragment, Tyr contributed to both affinity and specificity, Gly and Ser to flexibility, and Trp and Arg to the affinity in these complexes (Schreiber & Keating, 2011). Therefore, the residues at the interface contributing to affinity and specificity are different (more on this shortly). It is noteworthy that all these amino acids often are part of IDRs. The authors also discuss the example of calmodulin, where any mutation, which increases its affinity toward one partner leads to simultaneous drop in affinity towards others (Schreiber & Keating, 2011).
Szwajkajzer and Carey (1997) pointed out that affinity correlates well with specificity in rigid systems, such as host–guest complexes (or Fischer's “lock‐and‐key” system) as the rigid host/receptor is pre‐organized to optimize both affinity and selectivity (specificity). When the receptor/protein is not rigid, these authors cite examples for high affinity/high specificity, high affinity/low specificity, low affinity/high specificity, and low affinity/low specificity scenarios (Szwajkajzer & Carey, 1997). Greenspan (2010) focused on lack of the correlation between affinity and specificity in the context of antigen–antibody interactions. A monoclonal antibody may have low affinity (towards the antigen) but still may discriminate very well between that and other antigens. The author breaks down specificity into geometrical fit (which obviously does not exist in the absence of a preformed binding site in the case of IDRs/IDPs) and chemical complementarity arising out of the multiple weak interactions with the binding site (Greenspan, 2010).
Some of the challenges in experimentally determining the range of multi‐specificity of proteins have been discussed by Ketudat Cairns et al. (2015). One can, of course, use computational approaches (including machine learning) to predict possible substrates/ligands for a protein (Pertusi et al., 2017). Importantly, Ketudat Cairns et al. also described examples, where the use of the synthetic substrates or relying upon recombinant proteins to assess specificity has given misleading results (Ketudat Cairns et al., 2015).
Peracchi (2018) presented another review with valuable insights, which discusses the usefulness of imperfect enzymes (as opposed to perfect enzyme, for which every encounter with the cognate ligand is productive) in metabolism and how positive selection, neural drift, and negative selection are involved in evolving enzyme specificity. All in all, enzymes may not be designed to be absolutely specific. The imperfect specificity leaves scope for evolution of new activity or broader specificity if desired at different time scales (Peracchi, 2018).
Gianni and Jemth (2019) argued against the common view that protein–protein interactions involving IDPs/IDRs are of high specificity and low affinity. Former may be an inaccurate description as these interactions tend to be promiscuous. Regarding affinity, the authors pointed out that binding affinities are in the range of few nanomolar to high micromolar. They also pointed out the uncertainty about “binding before the folding” or “folding before the binding” (Gianni & Jemth, 2019). Curiously, they did not mention induced fit or conformation selection in this context. As is being increasingly realized, in real systems both induced fit and conformation selection are involved at different steps of protein interactions. This commentary article is thought provoking and highlights the need to unravel finer details of interactions involving IDPs/IDRs in larger number of cases (Gianni & Jemth, 2019).
Teilum et al. (2015) have also questioned the high specificity‐low affinity as a feature more prevalent in protein–protein interactions involving an IDP. An interesting observation in their work is that complexes formed by globular proteins also frequently involve small surface lengths. Therefore, involvement of SLiMs and MoRFs in PPI involving IDPs/IDRs is not something very different. Another remarkable finding is that the distribution of the nature of interactions is same in PPI involving structure or disorder. This is unlike in obligate oligomers, where PPI are driven largely by hydrophobic interactions. These authors pointed out that some researchers view specificity as “embedded interactions between charged and polar side chains in the interface”. In that respect, PPIs involving IDPs do not have higher specificity. The proteins in their study, unfortunately, were mostly recombinant proteins expressed in E. coli and lacked PTMs. As PTMs regulate PPI interactions and affect the involvement of charged side chains and so forth, we need to view these conclusions keeping that in mind (and authors do acknowledge that; Teilum et al., 2015).
Teilum et al. (2015) also reported a similar level of enthalpy–entropy compensation in PPI between ordered proteins and between IDPs and ordered protein but higher free energy of interaction for the former. Again, these values may be impacted by PTMs (Teilum et al., 2015). The issue of enthalpy–entropy compensation is relevant to both protein structure and binding of ligands to them. This has been more critically discussed at few places. Severe entropy–enthalpy compensation is quite uncommon. Accurate measurements of enthalpy and entropy is not always easy, free energy measurements are more reliable. A tight binding does not always lead to higher loss in entropy (Chodera & Mobley, 2013). In fact, an intriguing case was recently reported, where two highly disordered human proteins (histone H1 and its nuclear chaperone prothymosin‐α) formed a complex with picomolar affinity, but fully retained their structural disorder, long‐range flexibility, and highly dynamic character in this ultrahigh‐affinity protein complex (Borgia et al., 2018). The rules of thumb related to thermodynamic analysis of binding are not always valid, a binding dominated by hydrophobic interactions is not always entropy driven (Setny et al., 2010).
In another important review, Teilium et al. have further developed their earlier arguments about interactions with IDPs being characterized by high specificity and low affinity (Teilum et al., 2021). They also pointed out that the range of affinities observed with IDPs/IDRs is not very different from those involving structured proteins only. Furthermore, they gave arguments in favor of even specificity mediated by disorder not being very different from that in the case of globular proteins (Teilum et al., 2021). Before we delve briefly into their arguments, these yet again forcefully support the continuum model, in which the differences in the functional behaviors as a result of disorder and structure are more of a quantitative rather than being qualitative in nature.
It is worthwhile to summarize the views of Teilium et al. on specificity and multispecificity (Teilum et al., 2021). A low specificity means that a hub protein will bind to many ligands with similar affinities when they all are present together in similar molar concentrations. Therefore, affinities alone are not sufficient to reflect protein specificity. The authors cite the example of the transactivation domain 2 (TAD‐2) of p53, where the relative concentrations of the ligands become important for what would bind. The large number of possible partners and highly dynamic structures result in what is perceived as multi‐specificity of IDPs (Teilum et al., 2021). The importance of flux concentration of various ligands is not limited to the issue of specificity and affinity alone. It has been pointed out that while deciding between induced fit and conformational selection mechanism, it is critical to consider flux concentration of the binding partners along with the rate constants (Hammes et al., 2009).
The next question is how intrinsic disorder shapes the evolution of proteins with new biological activities. The following section provides an update on what we know about this interesting issue.
16. INTRINSIC DISORDER, PROTEIN EVOLUTION, AND SPECIFICITY
Ahrens et al. (2017) recollect the old belief that “If a protein structure does not fold properly, its functional properties are negatively affected” originated from restricting oneself to PDB entries. It is obviously not a general truth anymore, as unfolded/unstructured proteins/regions, as we know now, actually not just facilitate but are often critical for some biological functions. These authors have pointed out that protein features, such as the presence of introns in their gene and sophisticated protein–protein interaction networks, which distinguish eukaryotic proteins from prokaryotic proteins are enabled by disorder in a major way (Ahrens et al., 2017). The alternate splicing as introns are removed frequently involves regions corresponding to IDRs (Romero et al., 2006).
It is now well accepted that higher disorder content of eukaryotic proteome (20.5% as compared to 7.4 and 8.5 for archaea and bacteria) is not found to correlate with the number of cell types in the organism, which is regarded as a measure of the complexity of the organism. However many features typical of eukaryotic proteins depend upon the intrinsic disorder to a significant extent. In yeasts, proteins, which are post‐translationally modified, are reported to be conserved. These sites for PTMs are in turn often associated with intrinsic disorder (Ahrens et al., 2017). Disorder‐based interactomes also have a faster adaptation to the changing conditions by reconfiguring the networks. Whether evolution leads to the emergence or sometimes loss of new domains by noncoding part of the genome becoming coding or when indels (insertions and deletions) occur, it frequently involves gain (or loss) of disorder (Ahrens et al., 2017). Therefore, protein evolution tinkers not just with the structured regions but with IDRs as well. Ahrens et al. also highlight that we still have no clarity about the sequence divergence and its correlation with disorder, it is possible that the role of disorder matters (Ahrens et al., 2017).
Newton et al. (2018) recalled Ycas–Jenson model, which led James and Tawfik (2003) to propose that “we present an evolutionary model… conformational diversity and functional promiscuity … evolvability traits that enable existing enzymes to rapidly evolve new activities”. As Newton et al. (2018) pithily wrote “Most‐and probably all‐extant enzymes are, in fact, promiscuous” and “today's enzymes are tomorrow's ancestors”. They also pointed out that catalytic chemistries are not tightly coupled to protein/domain folds (and hence structures), since every possible change between EC classes (except between ligases and isomerases) has been reported (Newton et al., 2018).
These authors have cited examples where enzymes are known to evolve from non‐catalytic ancestors which should not be surprising as moonlighting has shown that the classical binary of enzymes and noncatalytic proteins was not the correct picture (Newton et al., 2018). They also give instances where instead of gene duplication or de novo genes, gene loss has been known to lead to a bifunctional enzymes becoming two monofunctional enzymes, as well as an example, where a monofunctional enzyme became multifunctional via gene loss (Newton et al., 2018).
Perhaps the most important message of the article by Newton et al. (2018) is that by emphasizing the “fast catalytic rates and biological specificity”, we have erred in implying that these virtues are the assets because of which enzymes are so valuable to the organisms. Most enzymes do not have catalytic rates of a “perfect enzyme” nor is enzyme evolution about chasing this perfection. This issue and that of relating enzyme evolution to organismal fitness raised by them (Newton et al., 2018) have been discussed by Tawfik's group in greater length and in both in vivo and in vitro contexts (Bar‐Even et al., 2015; Goldsmith & Tawfik, 2017; James & Tawfik, 2003; Soskine & Tawfik, 2010; Tawfik, 2014).
An interesting observation concerns yeast proteome, where about 50 proteins, many of which are nucleic acid binding ones with large IDDs, showed patterns of protein‐based inheritance like prions but did not form amyloids (Chakrabortee et al., 2016). Ahrens et al. (2017) have also provided a crisp discussion on how whole gene duplication (WGD) leads to new protein activities through neofunctionalization, where the original gene copy retains the function and the duplicate may follow the trajectory of evolving into a new protein, or subfunctionalization, where the two copies share the ancestral function. An earlier article from this group has discussed how disorder facilitates neofunctionalization (Siltberg‐Liberles, 2011). In neofunctionalization, there are intermediate on the evolutionary pathway, where a promiscuous activity starts appearing. This promiscuity can be manifested in terms of novel interacting abilities or of catalytic nature including both catalytic and substrate promiscuity (Gupta et al., 2020). It is time not to treat promiscuity in protein–protein interactions as something very different from the promiscuities related to molecular recognition of small molecules such as substrates/ligands.
While promiscuity related to protein–protein interactions heavily relies upon disorder, conformational flexibility/dynamics has a greater role to play in promiscuity related to catalysis. An interesting example is given by β‐lactamase, which has evolved into having a more rigid active site in TEM‐1. Pathogens have evolved β‐lactamases with greater flexible active site and hence use its promiscuity to become antibiotic resistance. In promiscuity related to catalysis, we mostly have differential ligand repositioning rather than very different protein regions becoming binding sites as in protein–protein interactions via intrinsic disorder. Therefore, in protein promiscuity too, there is again a division of labor between structure and disorder while crafting it. This division is not clear‐cut as exemplified by the detoxification enzyme glutathione transferase A1‐1, which has a molten globule like active site that powers its needed promiscuous activities (Honaker et al., 2013). Also, intrinsic disorder has a functional role in several enzymes, such as hydrolases and transferases. More specifically, chorismate mutase, variants of ribonuclease T1, and phosphoinositide 3‐kinase have significant levels of disorder (Davé & Uversky, 2023; DeForte & Uversky, 2017; Qamra et al., 2006).
As disorder facilitates mutation, it is closely associated with moonlighting functions (Tompa et al., 2005). Moonlighting involves multi‐tasking by proteins wherein molecular recognition of very different ligands is involved. Intrinsic disorder is involved at two levels here. During evolution, moonlighting is enabled via enhancing or exploiting disorder. As examples of disorder enabling moonlighting, ribosomal proteins with 30 moonlighting activities and 14‐3‐3 proteins having disordered N‐terminal with >200 binding partners represent illustrations of levels of moonlighting, which can be achieved as a combination of protein dynamics and disorder (Tompa et al., 2005).
The term conditional promiscuity has been used to describe in vitro activities such as reverse synthesis by hydrolases under low water conditions (Gupta et al., 2020). It is worth considering moonlighting as a conditional promiscuity in the in vivo context in as much as new cellular or tissue level requirement leads to a moonlighting activity (Gupta & Uversky, 2023f). Neofunctionalization occurs when the original activity is a well‐established one, like a part of central metabolic pathway. Moonlighting by many enzymes of glycolytic pathways illustrates this, though in these cases conformational dynamism rather than disorder has a significant role in moonlighting. Alarmins, the first responders to infection and apoptosis include proteins, all of them have high levels of disorder and need to multi‐task during their function (Gupta & Uversky, 2023f). Once again, we see both structure and disorder seamlessly leading to multispecificity. Subfunctionalization is an evolutionary mechanism to formation of isoenzymes, which are also implicated in moonlighting in few cases (Wilson, 2003). Apart from WGD, point mutations are also obviously involved in evolution of functional diversity.
17. CONCLUSION AND FUTURE PERSPECTIVES
The recent results on disruption of the complex formation between α‐synuclein and Endosomal Sorting Complex Required for Transport (ESCORT) by a synthetic peptide show the spin‐off of not restricting ourselves to structure–function paradigm but viewing function from the window of continuum model (Nim et al., 2023). Multiple results over the years show that the focus on disorder, while designing proteins and their inhibitors pays dividends (Blundell et al., 2020; Gupta et al., 2020; Gupta & Roy, 2021; Protasova et al., 1994; Uversky et al., 1996).
An approach involving protein disorder, cell culture, and bioimprinting, a technique exploiting adaptability of polymer structure to create a tailored binding site and well known among material scientists, deserves more attention (Sarwar & Evans, 2021; Wulff, 1995). Extracellular matrix (ECM) consists of proteins with diverse range of structures and disorder, which are most frequently used in designing 3D cell culture models. Sarwar and Evans (2021) have discussed increasing usefulness of bioimprinted cell culture models in cellular biology. Lederberg (2002) has made some interesting observations about molecular imprinting/bioimprinting. Imprinting techniques fall under instructive rather than selective mechanism (Lederberg, 2002; Mukherjee & Gupta, 2015a). More importantly, Lederberg (2002) wrote “More critical is the enigma of prion…a pathogenic conformation…can re‐conform…into its own malignant image”. There are enough indications that sometimes instruction does play a role in protein function (and biology in general; Lederberg, 2002; Mukherjee & Gupta, 2015a).
A different technique, also called bioimprinting, was developed using BSA which has IDRs. In this technique, protein flexibility is exploited to create a binding site for an imprint. The protein conformation in the presence of high concentration of the imprint was frozen by freeze‐drying and the imprint was removed under low water conditions. Later, this kind of bioimprinting has been shown to have diverse functional consequences (Braco et al., 1990; Gunasekaran et al., 2003; Mukherjee & Gupta, 2015b, 2015c, 2016b; Pidenko et al., 2023). The point is that bioimprinting also works with proteins like chymotrypsin, subtilisin, and lipases with lids on their active site. There is no study that would evaluate the role, which flexibility or disorder plays in bioimprinting. Although, the water activity level at the last stage of “drying”, which removes excess water to rigidify protein conformation, seems important for the final imprinted protein or the biological activity of the protein in low water.
Considering that imprinting can alter/confer new properties on proteins (Majumder & Gupta, 2011), looking at the protein dynamics over the entire range and during the imprinting process may be worthwhile. Low water enzymology has over the years emerged as a critical technology for organic synthesis (Carrea & Riva, 2000; Roy & Gupta, 2023). The increase in disorder in proteome under water stressed conditions has already attracted attention. However, interest in their behavior at molecular level is rather at a nascent stage (Reid et al., 2022). It is likely that we will see more work on IDPs/IDRs under low water conditions; that may even result in more applications of biomprinting in biological sciences.
There are also other contexts, in which future work on behavior of IDRs/IDPs under low water conditions may be useful. Water plays an important role both in maintaining structure as well as ensuring function of proteins. Through solvation of protein molecules, maintaining its network of H‐bonds and as the basis of hydrophobic interactions, water molecules are critical to protein structure. As a reaction medium; providing critical flexibility for biological activity, opening proton conduction pathways, and being bound to most active sites of enzymes; water molecules are also vital for function (Halling, 2004). The importance of water activity under low water conditions in vitro was proposed by Halling (1994) and is now well accepted. Watson et al. (2023) in a just‐published paper have focused on its importance in vivo under the crowded intracellular conditions. Zaslavsky and Uversky (2018) had earlier pointed out how LLPS can affect the availability of water for cellular needs. Watson et al. (2023) showed that both hyposmatic or hyperthermal stress increases water activity and dissociates proteins from biomolecular condensates formed as a result of LLPS.
The lack of correlation between abundance of intrinsic disorder and organismal complexity has puzzled enzymologists. Watson et al. (2023) have pointed out that humans (and many other animals) have anatomical and temporal variations in temperature and osmatic strength. They propose that biomolecular condensates (and hence IDPs, which went changes in their abundance swiftly under thermal and osmotic stress) act as a buffer to ensure water availability under these varied conditions (Watson et al., 2023). One can speculate that IDPs have so many different roles that one needs to look at their individual abundance at different time scales to fully appreciate their overall importance in biological organisms (Chowdhury et al., 2023; Zarin et al., 2019). We are getting there! Continuum model is a better approach than the binary of structure and disorder for the way ahead.
AUTHOR CONTRIBUTIONS
Vladimir Uversky: Conceptualization; validation; investigation; formal analysis; data curation; writing – original draft; writing – review and editing. Munishwar Nath Gupta: Conceptualization; data curation; formal analysis; validation; writing – original draft; writing – review and editing; investigation.
FUNDING INFORMATION
This research received no external funding.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Gupta MN, Uversky VN. Protein structure–function continuum model: Emerging nexuses between specificity, evolution, and structure. Protein Science. 2024;33(4):e4968. 10.1002/pro.4968
Reviewing Editor: Nir Ben‐Tal
Contributor Information
Munishwar Nath Gupta, Email: mn7gupta@gmail.com.
Vladimir N. Uversky, Email: vuversky@usf.edu.
DATA AVAILABILITY STATEMENT
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
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