bims-indpro Biomed News
on Intrinsically disordered proteins
Issue of 2022‒08‒21
eleven papers selected by
Sara Mingu
Johannes Gutenberg University


  1. Essays Biochem. 2022 Aug 17. pii: EBC20220046. [Epub ahead of print]
      The pathological assembly of intrinsically disordered proteins/peptides (IDPs) into amyloid fibrils is associated with a range of human pathologies, including neurodegeneration, metabolic diseases and systemic amyloidosis. These debilitating disorders affect hundreds of millions of people worldwide, and the number of people affected is increasing sharply. However, the discovery of therapeutic agents has been immensely challenging largely because of (i) the diverse number of aggregation pathways and the multi-conformational and transient nature of the related proteins or peptides and (ii) the under-development of experimental pipelines for the identification of disease-modifying molecules and their mode-of-action. Here, we describe current approaches used in the search for small-molecule modulators able to control or arrest amyloid formation commencing from IDPs and review recently reported accelerators and inhibitors of amyloid formation for this class of proteins. We compare their targets, mode-of-action and effects on amyloid-associated cytotoxicity. Recent successes in the control of IDP-associated amyloid formation using small molecules highlight exciting possibilities for future intervention in protein-misfolding diseases, despite the challenges of targeting these highly dynamic precursors of amyloid assembly.
    Keywords:  accelerator; amyloid; energy landscape; inhibitor; protein aggregation; small-molecule modulator
    DOI:  https://doi.org/10.1042/EBC20220046
  2. Cell Mol Life Sci. 2022 Aug 16. 79(9): 484
      Ubiquitin is a small, globular protein that is conjugated to other proteins as a posttranslational event. A palette of small, folded domains recognizes and binds ubiquitin to translate and effectuate this posttranslational signal. Recent computational studies have suggested that protein regions can recognize ubiquitin via a process of folding upon binding. Using peptide binding arrays, bioinformatics, and NMR spectroscopy, we have uncovered a disordered ubiquitin-binding motif that likely remains disordered when bound and thus expands the palette of ubiquitin-binding proteins. We term this motif Disordered Ubiquitin-Binding Motif (DisUBM) and find it to be present in many proteins with known or predicted functions in degradation and transcription. We decompose the determinants of the motif showing it to rely on features of aromatic and negatively charged residues, and less so on distinct sequence positions in line with its disordered nature. We show that the affinity of the motif is low and moldable by the surrounding disordered chain, allowing for an enhanced interaction surface with ubiquitin, whereby the affinity increases ~ tenfold. Further affinity optimization using peptide arrays pushed the affinity into the low micromolar range, but compromised context dependence. Finally, we find that DisUBMs can emerge from unbiased screening of randomized peptide libraries, featuring in de novo cyclic peptides selected to bind ubiquitin chains. We suggest that naturally occurring DisUBMs can recognize ubiquitin as a posttranslational signal to act as affinity enhancers in IDPs that bind to folded and ubiquitylated binding partners.
    Keywords:  Context; Cyclic peptide; Deep mutational scanning; IDP; NMR; SLiM; UBM; Ubiquitin
    DOI:  https://doi.org/10.1007/s00018-022-04486-w
  3. Front Plant Sci. 2022 ;13 956299
      Intrinsically disorder regions or proteins (IDRs or IDPs) constitute a large subset of the eukaryotic proteome, which challenges the protein structure-function paradigm. These IDPs lack a stable tertiary structure, yet they play a crucial role in the diverse biological process of plants. This study represents the intrinsically disordered nature of a plant-specific DNA binding with one finger transcription factor (DOF-TF). Here, we have investigated the role of OsDOF27 and characterized it as an intrinsically disordered protein. Furthermore, the molecular role of OsDOF27 in thermal stress tolerance has been elucidated. The qRT-PCR analysis revealed that OsDOF27 was significantly upregulated under different abiotic stress treatments in rice, particularly under heat stress. The stress-responsive transcript induction of OsDOF27 was further correlated with enriched abiotic stress-related cis-regulatory elements present in its promoter region. The in vivo functional analysis of the potential role of OsDOF27 in thermotolerance was further studied in yeast and in planta. Ectopic expression of OsDOF27 in yeast implicates thermotolerance response. Furthermore, the rice transgenic lines with overexpressing OsDOF27 revealed a positive role in mitigating heat stress tolerance. Collectively, our results evidently show the intrinsically disorderedness in OsDOF27 and its role in thermal stress response in rice.
    Keywords:  DOF-transcription factor; crop improvement; heat stress response; intrinsically disorder proteins; transcriptional regulation
    DOI:  https://doi.org/10.3389/fpls.2022.956299
  4. J Phys Chem Lett. 2022 Aug 17. 7804-7808
      The phenomenon of liquid-liquid phase separation is found in numerous biological processes. The biomolecules enveloped in the phase-separated droplets experience an obviously different environment from those in cellular or aqueous solution. Herein, we quantitatively characterized the thermodynamics and exchange kinetics of a model protein SH3 domain in the condensed phase of an intrinsically disordered region of a germ cell-specific protein DDX4N1 by using 19F-NMR spectroscopy. The stability and exchange rate of the SH3 domain are different from those in buffer and macromolecular crowding conditions. Our finding indicates that the local transient ordered microstructure and heterogeneity in the condensates play significant roles in modulating the biophysical properties of the enveloped proteins, and this finding may be essential to further our understanding how phase separation regulates the function of proteins in cells.
    DOI:  https://doi.org/10.1021/acs.jpclett.2c01920
  5. J Phys Chem B. 2022 Aug 15.
      Most biological events occur on time scales that are difficult to access using conventional all-atom molecular dynamics simulations in explicit solvent. Implicit solvent techniques offer a promising solution to this problem, alleviating the computational cost associated with the simulation of large systems and accelerating the sampling compared to explicit solvent models. The substitution of water molecules by a mean field, however, introduces simplifications that may penalize accuracy and impede the prediction of certain physical properties. We demonstrate that existing implicit solvent models developed using a transfer free energy approach, while satisfactory at reproducing the folding behavior of globular proteins, fare less well in characterizing the conformational properties of intrinsically disordered proteins. We develop a new implicit solvent model that maximizes the degree of accuracy for both disordered and folded proteins. We show, by comparing the simulation outputs to experimental data, that in combination with the a99SB-disp force field, the implicit solvent model can describe both disordered (aβ40, PaaA2, and drkN SH3) and folded ((AAQAA)3, CLN025, Trp-cage, and GTT) peptides. Our implicit solvent model permits a computationally efficient investigation of proteins containing both ordered and disordered regions, as well as the study of the transition between ordered and disordered protein states.
    DOI:  https://doi.org/10.1021/acs.jpcb.2c03980
  6. J Phys Chem B. 2022 Aug 17.
      AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota-human protein-protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.
    DOI:  https://doi.org/10.1021/acs.jpcb.2c04346
  7. J Phys Chem B. 2022 Aug 15.
      The intrinsically disordered DNA-binding domain of cytidine repressor (CytR-DBD) folds in the presence of target DNA and regulates the expression of multiple genes in E. coli. To explore the conformational rearrangements in the unbound state and the target recognition mechanisms of CytR-DBD, we carried out single-molecule Förster resonance energy transfer (smFRET) measurements. The smFRET data of CytR-DBD in the absence of DNA show one major and one minor population assignable to an expanded unfolded state and a compact folded state, respectively. The population of the folded state increases and decreases upon titration with salt and denaturant, respectively, in an apparent two-state manner. The peak FRET efficiencies of both the unfolded and folded states change continuously with denaturant concentration, demonstrating the intrinsic flexibility of the DNA-binding domain and the deviation from a strict two-state transition. Remarkably, the CytR-DBD exhibits a compact structure when bound to both the specific and nonspecific DNA; however, the peak FRET efficiencies of the two structures are slightly but consistently different. The observed conformational heterogeneity highlights the potential structural changes required for CytR to bind variably spaced operator sequences.
    DOI:  https://doi.org/10.1021/acs.jpcb.2c02791
  8. Sci Rep. 2022 Aug 16. 12(1): 13891
      Predicting the local structural features of a protein from its amino acid sequence helps its function prediction to be revealed and assists in three-dimensional structural modeling. As the sequence-structure gap increases, prediction methods have been developed to bridge this gap. Additionally, as the size of the structural database and computing power increase, the performance of these methods have also significantly improved. Herein, we present a powerful new tool called S-Pred, which can predict eight-state secondary structures (SS8), accessible surface areas (ASAs), and intrinsically disordered regions (IDRs) from a given sequence. For feature prediction, S-Pred uses multiple sequence alignment (MSA) of a query sequence as an input. The MSA input is converted to features by the MSA Transformer, which is a protein language model that uses an attention mechanism. A long short-term memory (LSTM) was employed to produce the final prediction. The performance of S-Pred was evaluated on several test sets, and the program consistently provided accurate predictions. The accuracy of the SS8 prediction was approximately 76%, and the Pearson's correlation between the experimental and predicted ASAs was 0.84. Additionally, an IDR could be accurately predicted with an F1-score of 0.514. The program is freely available at https://github.com/arontier/S_Pred_Paper and https://ad3.io as a code and a web server.
    DOI:  https://doi.org/10.1038/s41598-022-18205-9
  9. Cell Rep. 2022 Aug 16. pii: S2211-1247(22)01029-4. [Epub ahead of print]40(7): 111212
      Evolutionary changes in host-virus interactions can alter the course of infection, but the biophysical and regulatory constraints that shape interface evolution remain largely unexplored. Here, we focus on viral mimicry of host-like motifs that allow binding to host domains and modulation of cellular pathways. We observe that motifs from unrelated viruses preferentially target conserved, widely expressed, and highly connected host proteins, enriched with regulatory and essential functions. The interface residues within these host domains are more conserved and bind a larger number of cellular proteins than similar motif-binding domains that are not known to interact with viruses. In contrast, rapidly evolving viral-binding human proteins form few interactions with other cellular proteins and display high tissue specificity, and their interfaces have few inter-residue contacts. Our results distinguish between conserved and rapidly evolving host-virus interfaces and show how various factors limit host capacity to evolve, allowing for efficient viral subversion of host machineries.
    Keywords:  CP: Microbiology; domain-motif interactions; host-virus co-evolution; host-virus interactions; intrinsically disordered regions; protein-protein interactions; short linear motifs; viral mimicry
    DOI:  https://doi.org/10.1016/j.celrep.2022.111212
  10. Trends Cell Biol. 2022 Aug 10. pii: S0962-8924(22)00176-3. [Epub ahead of print]
      The MYC protooncogene functions as a universal amplifier of transcription through interaction with numerous factors and complexes that regulate almost every cellular process. However, a comprehensive model that explains MYC's actions and the interplay governing the complicated dynamics of components of the transcription and replication machinery is still lacking. Here, we review the potency of MYC as an oncogenic driver and how it regulates the broad spectrum of complexes (effectors and regulators). We propose a 'hand-over model' for differential partitioning and trafficking of unstructured MYC via a loose interaction network between various gene-regulatory complexes and factors. Additionally, the article discusses how unstructured-MYC energetically favors efficient modulation of the energy landscape of the transcription cycle.
    Keywords:  DNA topology; MYC; MYC–topoisome complex; RNA polymerase; intrinsically disordered proteins; multistep reactions; protein complexes; topoisomerase; transcription cycle
    DOI:  https://doi.org/10.1016/j.tcb.2022.07.006
  11. J Cell Physiol. 2022 Aug 18.
      Abnormal deposition of tau in neurons is a hallmark of Alzheimer's disease and several other neurodegenerative disorders. In the past decades, extensive efforts have been made to explore the mechanistic pathways underlying the development of tauopathies. Recently, the discovery of tau droplet formation by liquid-liquid phase separation (LLPS) has received a great deal of attention. It has been reported that tau condensates have a biological role in promoting and stabilizing microtubule (MT) assembly. Furthermore, it has been hypothesized that the transition of phase-separated tau droplets to a gel-like state and then to fibrils is associated with the pathology of neurodegenerative diseases. In this review, we outline LLPS, the structural disorder that facilitates tau droplet formation, the effects of posttranslational modification of tau on condensate formation, the physiological function of tau droplets, the pathways from droplet to toxic fibrils, and the therapeutic strategies for tauopathies that might evolve from toxic droplets. We expect a deeper understanding of tau LLPS will provide additional insights into tau physiology and tauopathies.
    Keywords:  condensate; microtubule; phase separation; tau; tauopathy
    DOI:  https://doi.org/10.1002/jcp.30853