Intrinsically disordered sequences can tune fungal growth and the cell cycle for specific temperatures.

Temperature can impact every reaction essential to a cell. For organisms that cannot regulate their own temperature, adapting to temperatures that fluctuate unpredictably and on variable timescales is a major challenge. Extremes in the magnitude and frequency of temperature changes are increasing across the planet, raising questions as to how the biosphere will respond. To examine mechanisms of adaptation to temperature, we collected wild isolates from different climates of the fungus Ashbya gossypii, which has a compact genome of only ∼4,600 genes. We found control of the nuclear division cycle and polarized morphogenesis, both critical processes for fungal growth, were temperature sensitive and varied among the isolates. The phenotypes were associated with naturally varying sequences within the glutamine-rich region (QRR) IDR of an RNA-binding protein called Whi3. This protein regulates both nuclear division and polarized growth via its ability to form biomolecular condensates. In cells and in cell-free reconstitution assays, we found that temperature tunes the properties of Whi3-based condensates. Exchanging Whi3 sequences between isolates was sufficient to rescue temperature-sensitive phenotypes, and specifically, a heptad repeat sequence within the QRR confers temperature-sensitive behavior. Together, these data demonstrate that sequence variation in the size and composition of an IDR can promote cell adaptation to growth at specific temperature ranges. These data demonstrate the power of IDRs as tuning knobs for rapid adaptation to environmental fluctuations.

Translational Diffusion and Self-Association of an Intrinsically Disordered Protein κ-Casein Using NMR with Ultra-High Pulsed-Field Gradient and Time-Resolved FRET.

Much attention has been given to studying the translational diffusion of globular proteins, whereas the translational diffusion of intrinsically disordered proteins (IDPs) is less studied. In this study, we investigate the translational diffusion and how it is affected by the self-association of an IDP, κ-casein, using pulsed-field gradient nuclear magnetic resonance and time-resolved Förster resonance energy transfer. Using the analysis of the shape of diffusion attenuation and the concentration dependence of κ-casein diffusion coefficients and intermolecular interactions, we demonstrate that κ-casein exhibits continuous self-association. When the volume fraction of κ-casein is below 0.08, we observe that κ-casein self-association results in a macroscopic phase separation upon storage at 4 °C. At κ-casein volume fractions above 0.08, self-association leads to the formation of labile gel-like networks without subsequent macroscopic phase separation. Unlike α-casein, which shows a strong concentration dependence and extensive gel-like network formation, only one-third of κ-casein molecules participate in the gel network at a time, resulting in a more dynamic and less extensive structure. These findings highlight the unique association properties of κ-casein, contributing to a better understanding of its behavior under various conditions and its potential role in casein micelle formation.

Differential Effects of Sequence-Local versus Nonlocal Charge Patterns on Phase Separation and Conformational Dimensions of Polyampholytes as Model Intrinsically Disordered Proteins.

Conformational properties of intrinsically disordered proteins (IDPs) are governed by a sequence-ensemble relationship. To differentiate the impact of sequence-local versus sequence-nonlocal features of an IDP's charge pattern on its conformational dimensions and its phase-separation propensity, the charge "blockiness" κ and the nonlocality-weighted sequence charge decoration (SCD) parameters are compared for their correlations with isolated-chain radii of gyration (Rgs) and upper critical solution temperatures (UCSTs) of polyampholytes modeled by random phase approximation, field-theoretic simulation, and coarse-grained molecular dynamics. SCD is superior to κ in predicting Rg because SCD accounts for effects of contact order, i.e., nonlocality, on dimensions of isolated chains. In contrast, κ and SCD are comparably good, though nonideal, predictors of UCST because frequencies of interchain contacts in the multiple-chain condensed phase are less sensitive to sequence positions than frequencies of intrachain contacts of an isolated chain, as reflected by κ correlating better with condensed-phase interaction energy than SCD.

Evolution of Virus-like Features and Intrinsically Disordered Regions in Retrotransposon-derived Mammalian Genes.

Several mammalian genes have originated from the domestication of retrotransposons, selfish mobile elements related to retroviruses. Some of the proteins encoded by these genes have maintained virus-like features; including self-processing, capsid structure formation, and the generation of different isoforms through -1 programmed ribosomal frameshifting. Using quantitative approaches in molecular evolution and biophysical analyses, we studied 28 retrotransposon-derived genes, with a focus on the evolution of virus-like features. By analyzing the rate of synonymous substitutions, we show that the -1 programmed ribosomal frameshifting mechanism in three of these genes (PEG10, PNMA3, and PNMA5) is conserved across mammals and originates alternative proteins. These genes were targets of positive selection in primates, and one of the positively selected sites affects a B-cell epitope on the spike domain of the PNMA5 capsid, a finding reminiscent of observations in infectious viruses. More generally, we found that retrotransposon-derived proteins vary in their intrinsically disordered region content and this is directly associated with their evolutionary rates. Most positively selected sites in these proteins are located in intrinsically disordered regions and some of them impact protein posttranslational modifications, such as autocleavage and phosphorylation. Detailed analyses of the biophysical properties of intrinsically disordered regions showed that positive selection preferentially targeted regions with lower conformational entropy. Furthermore, positive selection introduces variation in binary sequence patterns across orthologues, as well as in chain compaction. Our results shed light on the evolutionary trajectories of a unique class of mammalian genes and suggest a novel approach to study how intrinsically disordered region biophysical characteristics are affected by evolution.

Predicting Conformational Ensembles of Intrinsically Disordered Proteins: From Molecular Dynamics to Machine Learning.

Intrinsically disordered proteins and regions (IDP/IDRs) are ubiquitous across all domains of life. Characterized by a lack of a stable tertiary structure, IDP/IDRs populate a diverse set of transiently formed structural states that can promiscuously adapt upon binding with specific interaction partners and/or certain alterations in environmental conditions. This malleability is foundational for their role as tunable interaction hubs in core cellular processes such as signaling, transcription, and translation. Tracing the conformational ensemble of an IDP/IDR and its perturbation in response to regulatory cues is thus paramount for illuminating its function. However, the conformational heterogeneity of IDP/IDRs poses several challenges. Here, we review experimental and computational methods devised to disentangle the conformational landscape of IDP/IDRs, highlighting recent computational advances that permit proteome-wide scans of IDP/IDRs conformations. We briefly evaluate selected computational methods using the disordered N-terminal of the human copper transporter 1 as a test case and outline further challenges in IDP/IDRs ensemble prediction.

Exploring Intrinsic Disorder in Human Synucleins and Associated Proteins.

In this work, we explored the intrinsic disorder status of the three members of the synuclein family of proteins-α-, ß-, and γ-synucleins-and showed that although all three human synucleins are highly disordered, the highest levels of disorder are observed in γ-synuclein. Our analysis of the peculiarities of the amino acid sequences and modeled 3D structures of the human synuclein family members revealed that the pathological mutations A30P, E46K, H50Q, A53T, and A53E associated with the early onset of Parkinson's disease caused some increase in the local disorder propensity of human α-synuclein. A comparative sequence-based analysis of the synuclein proteins from various evolutionary distant species and evaluation of their levels of intrinsic disorder using a set of commonly used bioinformatics tools revealed that, irrespective of their origin, all members of the synuclein family analyzed in this study were predicted to be highly disordered proteins, indicating that their intrinsically disordered nature represents an evolutionary conserved and therefore functionally important feature. A detailed functional disorder analysis of the proteins in the interactomes of the human synuclein family members utilizing a set of commonly used disorder analysis tools showed that the human α-synuclein interactome has relatively higher levels of intrinsic disorder as compared with the interactomes of human ß- and γ- synucleins and revealed that, relative to the ß- and γ-synuclein interactomes, α-synuclein interactors are involved in a much broader spectrum of highly diversified functional pathways. Although proteins interacting with three human synucleins were characterized by highly diversified functionalities, this analysis also revealed that the interactors of three human synucleins were involved in three common functional pathways, such as the synaptic vesicle cycle, serotonergic synapse, and retrograde endocannabinoid signaling. Taken together, these observations highlight the critical importance of the intrinsic disorder of human synucleins and their interactors in various neuronal processes.

Modulation of α-synuclein aggregation amid diverse environmental perturbation.

Intrinsically disordered protein α-synuclein (αS) is implicated in Parkinson's disease due to its aberrant aggregation propensity. In a bid to identify the traits of its aggregation, here we computationally simulate the multi-chain association process of αS in aqueous as well as under diverse environmental perturbations. In particular, the aggregation of αS in aqueous and varied environmental condition led to marked concentration differences within protein aggregates, resembling liquid-liquid phase separation (LLPS). Both saline and crowded settings enhanced the LLPS propensity. However, the surface tension of αS droplet responds differently to crowders (entropy-driven) and salt (enthalpy-driven). Conformational analysis reveals that the IDP chains would adopt extended conformations within aggregates and would maintain mutually perpendicular orientations to minimize inter-chain electrostatic repulsions. The droplet stability is found to stem from a diminished intra-chain interactions in the C-terminal regions of αS, fostering inter-chain residue-residue interactions. Intriguingly, a graph theory analysis identifies small-world-like networks within droplets across environmental conditions, suggesting the prevalence of a consensus interaction patterns among the chains. Together these findings suggest a delicate balance between molecular grammar and environment-dependent nuanced aggregation behavior of αS.

Disengagement of somatostatin neurons from lateral septum circuitry by oxytocin and vasopressin restores social-fear extinction and suppresses aggression outbursts in Prader-Willi syndrome model.

Background: Responding to social signals by expressing the correct behavior is not only challenged in autism, but also in diseases with high prevalence of autism, like Prader-Willi Syndrome (PWS). Clinical evidence suggests aberrant pro-social behavior in patients can be regulated by intranasal oxytocin (OXT) or vasopressin (AVP). However, what neuronal mechanisms underlie impaired behavioral responses in a socially-aversive context, and how can they be corrected, remains largely unknown. Methods: Using the Magel2 knocked-out (KO) mouse model of PWS (crossed with CRE-dependent transgenic lines), we devised optogenetic, physiological and pharmacological strategies in a social-fear-conditioning paradigm. Pathway specific roles of OXT and AVP signaling were investigated converging on the lateral septum (LS), a region which receives dense hypothalamic inputs. Results: OXT and AVP signaling promoted inhibitory synaptic transmission in the LS, which failure in Magel2KO mice disinhibited somatostatin (SST) neurons and disrupted social-fear extinction. The source of OXT and AVP deficits mapped specifically in the supraoptic nucleus→LS pathway of Magel2KO mice disrupting social-fear extinction, which could be corrected by optogenetic or pharmacological inhibition of SST-neurons in the LS. Interestingly, LS SST-neurons also gated the expression of aggressive behavior, possibly as part of functional units operating beyond local septal circuits. Conclusions: SST cells in the LS play a crucial role in integration and expression of disrupted neuropeptide signals in autism, thereby altering the balance in expression of safety versus fear. Our results uncover novel mechanisms underlying dysfunction in a socially-aversive context, and provides a new framework for future treatments in autism-spectrum disorders.

A suicidal and extensively disordered luciferase with a bright luminescence.

Gaussia luciferase (GLuc) is one of the most luminescent luciferases known and is widely used as a reporter in biochemistry and cell biology. During catalysis, GLuc undergoes inactivation by irreversible covalent modification. The mechanism by which GLuc generates luminescence and how it becomes inactivated are however not known. Here, we show that GLuc unlike other enzymes has an extensively disordered structure with a minimal hydrophobic core and no apparent binding pocket for the main substrate, coelenterazine. From an alanine scan, we identified two Arg residues required for light production. These residues separated with an average of about 22 Å and a major structural rearrangement is required if they are to interact with the substrate simultaneously. We furthermore show that in addition to coelenterazine, GLuc also can oxidize furimazine, however, in this case without production of light. Both substrates result in the formation of adducts with the enzyme, which eventually leads to enzyme inactivation. Our results demonstrate that a rigid protein structure and substrate-binding site are no prerequisites for high enzymatic activity and specificity. In addition to the increased understanding of enzymes in general, the findings will facilitate future improvement of GLuc as a reporter luciferase.

Refined Bonded Terms in Coarse-Grained Models for Intrinsically Disordered Proteins Improve Backbone Conformations.

Coarse-grained models designed for intrinsically disordered proteins and regions (IDP/Rs) usually omit some bonded potentials (e.g., angular and dihedral potentials) as a conventional strategy to enhance backbone flexibility. However, a notable drawback of this approach is the generation of inaccurate backbone conformations. Here, we addressed this problem by introducing residue-specific angular, refined dihedral, and correction map (CMAP) potentials, derived based on the statistics from a customized coil database. These bonded potentials were integrated into the existing Mpipi model, resulting in a new model, denoted as the "Mpipi+" model. Results show that the Mpipi+ model can improve backbone conformations. More importantly, it can markedly improve the secondary structure propensity (SSP) based on the experimental chemical shift and, consequently, succeed in capturing transient secondary structures. Moreover, the Mpipi+ model preserves the liquid-liquid phase separation (LLPS) propensities of IDPs.

Deeper Insight of the Conformational Ensemble of Intrinsically Disordered Proteins.

It is generally known that, unlike structured proteins, intrinsically disordered proteins, IDPs, exhibit various structures and conformers, the so-called conformational ensemble, CoE. This study aims to better understand the conformers that make up the IDP ensemble by decomposing the CoE into groups separated by their radius of gyration, Rg. A common approach to studying CoE for IDPs is to use low-resolution techniques, such as small-angle scattering, and combine those with computer simulations on different length scales. Herein, the well-studied antimicrobial saliva protein histatin 5 was utilized as a model peptide for an IDP; the average intensity curves were obtained from small-angle X-ray scattering; and compared with fully atomistic, explicit water, molecular dynamics simulations; then, the intensity curve was decomposed with respect to the different Rg values; and their secondary structure propensities were investigated. We foresee that this approach can provide important information on the CoE and the individual conformers within; in that case, it will serve as an additional tool for understanding the IDP structure-function relationship on a more detailed level.

Structures prediction and replica exchange molecular dynamics simulations of α-synuclein: A case study for intrinsically disordered proteins.

In recent years, a variety of three-dimensional structure prediction tools, including AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold, have been employed in the investigation of intrinsically disordered proteins. However, a comprehensive validation of these tools specifically for intrinsically disordered proteins has yet to be conducted. In this study, we utilize AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold to predict the structure of a model intrinsically disordered α-synuclein protein. Additionally, extensive replica exchange molecular dynamics simulations of the intrinsically disordered protein are conducted. The resulting structures from both structure prediction tools and replica exchange molecular dynamics simulations are analyzed for radius of gyration, secondary and tertiary structure properties, as well as Cα and Hα chemical shift values. A comparison of the obtained results with experimental data reveals that replica exchange molecular dynamics simulations provide results in excellent agreement with experimental observations. However, none of the structure prediction tools utilized in this study can fully capture the structural characteristics of the model intrinsically disordered protein. This study shows that a cluster of ensembles are required for intrinsically disordered proteins. Artificial-intelligence based structure prediction tools such as AlphaFold3 and C-I-TASSER could benefit from stochastic sampling or Monte Carlo simulations for generating an ensemble of structures for intrinsically disordered proteins.

An IDR-dependent mechanism for nuclear receptor control of Mediator interaction with RNA polymerase II.

The essential Mediator (MED) coactivator complex plays a well-understood role in regulation of basal transcription in all eukaryotes, but the mechanism underlying its role in activator-dependent transcription remains unknown. We investigated modulation of metazoan MED interaction with RNA polymerase II (RNA Pol II) by antagonistic effects of the MED26 subunit and the CDK8 kinase module (CKM). Biochemical analysis of CKM-MED showed that the CKM blocks binding of the RNA Pol II carboxy-terminal domain (CTD), preventing RNA Pol II interaction. This restriction is eliminated by nuclear receptor (NR) binding to CKM-MED, which enables CTD binding in a MED26-dependent manner. Cryoelectron microscopy (cryo-EM) and crosslinking-mass spectrometry (XL-MS) revealed that the structural basis for modulation of CTD interaction with MED relates to a large intrinsically disordered region (IDR) in CKM subunit MED13 that blocks MED26 and CTD interaction with MED but is repositioned upon NR binding. Hence, NRs can control transcription initiation by priming CKM-MED for MED26-dependent RNA Pol II interaction.

How to Survive without Water: A Short Lesson on the Desiccation Tolerance of Budding Yeast.

Water is essential to all life on earth. It is a major component that makes up living organisms and plays a vital role in multiple biological processes. It provides a medium for chemical and enzymatic reactions in the cell and is a major player in osmoregulation and the maintenance of cell turgidity. Despite this, many organisms, called anhydrobiotes, are capable of surviving under extremely dehydrated conditions. Less is known about how anhydrobiotes adapt and survive under desiccation stress. Studies have shown that morphological and physiological changes occur in anhydrobiotes in response to desiccation stress. Certain disaccharides and proteins, including heat shock proteins, intrinsically disordered proteins, and hydrophilins, play important roles in the desiccation tolerance of anhydrobiotes. In this review, we summarize the recent findings of desiccation tolerance in the budding yeast Saccharomyces cerevisiae. We also propose that the yeast under desiccation could be used as a model to study neurodegenerative disorders.

A Comparative Experimental and Computational Study on the Nature of the Pangolin-CoV and COVID-19 Omicron.

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have an abnormally hard outer shell (low M disorder, i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far has been found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2, especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 and later in Omicron, is associated with attenuation according to the Shell-Disorder Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

Identification of plant transcriptional activation domains.

Gene expression in Arabidopsis is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA-binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for nearly all Arabidopsis TFs, we lack knowledge about the presence, location and transcriptional strength of their ADs1. To address this gap, here we use a yeast library approach to experimentally identify Arabidopsis ADs on a proteome-wide scale, and find that more than half of the Arabidopsis TFs contain an AD. We annotate 1,553 ADs, the vast majority of which are, to our knowledge, previously unknown. Using the dataset generated, we develop a neural network to accurately predict ADs and to identify sequence features that are necessary to recruit coactivator complexes. We uncover six distinct combinations of sequence features that result in activation activity, providing a framework to interrogate the subfunctionalization of ADs. Furthermore, we identify ADs in the ancient AUXIN RESPONSE FACTOR family of TFs, revealing that AD positioning is conserved in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examining function in intrinsically disordered regions and a predictive model of ADs.

A curated rotamer library for common post-translational modifications of proteins.

MOTIVATION: Sidechain rotamer libraries of the common amino acids of a protein are useful for folded protein structure determination and for generating ensembles of intrinsically disordered proteins (IDPs). However, much of protein function is modulated beyond the translated sequence through the introduction of post-translational modifications (PTMs). RESULTS: In this work, we have provided a curated set of side chain rotamers for the most common PTMs derived from the RCSB PDB database, including phosphorylated, methylated, and acetylated sidechains. Our rotamer libraries improve upon existing methods such as SIDEpro, Rosetta, and AlphaFold3 in predicting the experimental structures for PTMs in folded proteins. In addition, we showcase our PTM libraries in full use by generating ensembles with the Monte Carlo Side Chain Entropy (MCSCE) for folded proteins, and combining MCSCE with the Local Disordered Region Sampling algorithms within IDPConformerGenerator for proteins with intrinsically disordered regions. AVAILABILITY AND IMPLEMENTATION: The codes for dihedral angle computations and library creation are available at https://github.com/THGLab/ptm_sc.git.

Hydrogen-Bonded Network of Water in Phase-Separated Biomolecular Condensates.

Biomolecular condensates formed via phase separation of intrinsically disordered proteins/regions (IDPs/IDRs) and nucleic acids are associated with cell physiology and disease. Water makes up for ∼60-70% of the condensate volume and is thought to influence the complex interplay of chain-chain and chain-solvent interactions, modulating the mesoscale properties of condensates. The behavior of water in condensates and the key roles of protein hydration water in driving the phase separation remain elusive. Here, we employ single-droplet vibrational Raman spectroscopy to illuminate the structural redistribution within protein hydration water during the phase separation of neuronal IDPs. Our Raman measurements reveal the changes in the water hydrogen bonding network during homotypic and heterotypic phase separation governed by various molecular drivers. Such single-droplet water Raman measurements offer a potent generic tool to unmask the intriguing interplay of sequence-encoded chain-chain and chain-solvent interactions governing macromolecular phase separation into membraneless organelles, synthetic condensates, and protocells.

An activity-specificity trade-off encoded in human transcription factors.

Transcription factors (TFs) control specificity and activity of gene transcription, but whether a relationship between these two features exists is unclear. Here we provide evidence for an evolutionary trade-off between the activity and specificity in human TFs encoded as submaximal dispersion of aromatic residues in their intrinsically disordered protein regions. We identified approximately 500 human TFs that encode short periodic blocks of aromatic residues in their intrinsically disordered regions, resembling imperfect prion-like sequences. Mutation of periodic aromatic residues reduced transcriptional activity, whereas increasing the aromatic dispersion of multiple human TFs enhanced transcriptional activity and reprogramming efficiency, promoted liquid-liquid phase separation in vitro and more promiscuous DNA binding in cells. Together with recent work on enhancer elements, these results suggest an important evolutionary role of suboptimal features in transcriptional control. We propose that rational engineering of amino acid features that alter phase separation may be a strategy to optimize TF-dependent processes, including cellular reprogramming.

Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies.

Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D).