High-throughput discovery of functional disordered regions: investigation of transactivation domains

Intrinsically disordered regions as facilitators of the transcription factor target search

Transcription factors (TFs) contribute to organismal development and function by regulating gene expression. Despite decades of research, the factors determining the specificity and speed at which eukaryotic TFs detect their target binding sites remain poorly understood. Recent studies have pointed to intrinsically disordered regions (IDRs) within TFs as key regulators of the process by which TFs find their target sites on DNA (the TF target search). However, IDRs are challenging to study because they can confer specificity despite low sequence complexity and can be functionally conserved despite rapid sequence divergence. Nevertheless, emerging computational and experimental approaches are beginning to elucidate the sequence-function relationship within the IDRs of TFs. Additional insights are informing potential mechanisms underlying the IDR-directed search for the DNA targets of TFs, including incorporation into biomolecular condensates, facilitating TF co-localization, and the hypothesis that IDRs recognize and directly interact with specific genomic regions.

Hierarchy in regulator interactions with distant transcriptional activation domains empowers rheostatic regulation

Transcription factors carry long intrinsically disordered regions often containing multiple activation domains. Despite numerous recent high-throughput identifications and characterizations of activation domains, the interplay between sequence motifs, activation domains, and regulator binding in intrinsically disordered transcription factor regions remains unresolved. Here, we map sequence motifs and activation domains in an Arabidopsis thaliana NAC transcription factor clade, revealing that although sequence motifs and activation domains often coincide, no systematic overlap exists. Biophysical analyses using NMR spectroscopy show that the long intrinsically disordered region of senescence-associated transcription factor ANAC046 is devoid of residual structure. We identify two activation domain/sequence motif regions, one at each end that both bind a panel of six positive and negative regulator domains from biologically relevant regulators promiscuously. Binding affinities measured using isothermal titration calorimetry reveal a hierarchy for regulator binding of the two ANAC046 activation domain/sequence motif regions defining these as regulatory hotspots. Despite extensive dynamic intramolecular contacts along the disordered chain revealed using paramagnetic relaxation enhancement experiments and simulations, the regions remain uncoupled in binding. Together, the results imply rheostatic regulation by ANAC046 through concentration-dependent regulator competition, a mechanism likely mirrored in other transcription factors with distantly located activation domains.

The intrinsically disordered AB region: a key modulator of the molecular properties of human RXRγ

The human retinoid X receptor γ (hRXRγ) is one of three characterized RXR subtypes, transcription factors belonging to the nuclear receptor superfamily. All RXR subtypes share nearly identical structural elements, including a conserved DNA-binding domain, a D region, a ligand-binding domain, and an F region. However, each subtype possesses a unique N-terminal AB region, which modulates the transcriptional activation of target genes in a cell- and promoter-dependent manner through its ligand-independent activation function involved in protein-protein interactions. Despite the functional significance of the AB region, its structural contributions, particularly in the context of the full-length receptor, remain largely unexplored. Here, we uncover the role of the AB region of hRXRγ in modulating the molecular properties of the receptor. A comparative analysis of the full-length receptor (hRXRγ) and a deletion mutant lacking the AB region (ΔABhRXRγ) highlights the critical role of the intrinsically disordered AB region in modulating the structural and functional properties of hRXRγ, including its ability to oligomerize, its overall stability, and conformation heterogeneity. The AB region does not act as an independent unit but amalgamates with the rest of the receptor, which fine-tunes the structural variability of hRXRγ, making it responsive to environmental conditions. These findings highlight the AB region as a critical determinant of hRXRγ's structural features and, potentially, its transcriptional potential.

Identification of microproteins with transactivation activity by polyalanine motif selection

Microproteins are an emerging class of proteins that are encoded by small open reading frames (smORFs) less than or equal to 100 amino acids. The functions of several microproteins have been illuminated through phenotypic screening or protein-protein interaction studies, but thousands of microproteins remain uncharacterized. The functional characterization of microproteins is challenging due to a lack of sequence homology. Here, we demonstrate a strategy to enrich microproteins that contain specific motifs as a means to more rapidly characterize microproteins. Specifically, we used the fact that polyalanine motifs are associated with nuclear proteins to select 58 candidate microproteins to screen for transactivation function. We identified three microproteins with transactivation activity when tested as GAL4-fusions in a cell-based luciferase assay. The results support the continued use of the motif selection strategy for the discovery of microprotein function.

Q-rich activation domains: flexible 'rulers' for transcription start site selection?

Recent findings broadened the function of RNA polymerase II (Pol II) proximal promoter motifs from quantitative regulators of transcription to important determinants of transcription start site (TSS) position. These motifs are recognized by transcription factors (TFs) that we propose to term 'ruler' TFs (rTFs), such as NRF1, NF-Y, YY1, ZNF143, BANP, and members of the SP, ETS, and CRE families, sharing as a common feature a glutamine-rich (Q-rich) effector domain also enriched in valine, isoleucine, and threonine (QVIT-rich). We propose that rTFs guide TSS location by constraining the position of the pre-initiation complex (PIC) during its promoter recognition phase through a specialized, and still enigmatic, class of activation domains.

Conservation of function without conservation of amino acid sequence in intrinsically disordered transcriptional activation domains

Protein function is canonically believed to be more conserved than amino acid sequence, but this idea is only well supported in folded domains, where highly diverged sequences can fold into equivalent 3D structures. In contrast, intrinsically disordered protein regions (IDRs) do not fold into a stable 3D structure, thus it remains unknown when and how function is conserved for IDRs that experience rapid amino acid sequence divergence. As a model system for studying the evolution of IDRs, we examined transcriptional activation domains, the regions of transcription factors that bind to coactivator complexes. We systematically identified activation domains on 502 orthologs of the transcriptional activator Gcn4 spanning 600 MY of fungal evolution. We find that the central activation domain shows strong conservation of function without conservation of sequence. This conservation of function without conservation of sequence is facilitated by evolutionary turnover (gain and loss) of key acidic and aromatic residues, the positions most important for function. This high sequence flexibility of functional orthologs mirrors the physical flexibility of the activation domain coactivator interaction interface, suggesting that physical flexibility enables evolutionary plasticity. We propose that turnover of short functional elements, sometimes individual amino acids, is a general mechanism for conservation of function without conservation of sequence during IDR evolution.

Reconciling competing models on the roles of condensates and soluble complexes in transcription factor function

Phase separation explains the exquisite spatial and temporal regulation of many biological processes, but the role of transcription factor-mediated condensates in gene regulation is contentious, requiring head-to-head comparison of competing models. Here, we focused on the prototypical yeast transcription factor Gcn4 and assessed two models for gene transcription activation, i.e., mediated via soluble complexes or transcriptional condensates. Both models rely on the ability of transcription factors and coactivators to engage in multivalent interactions. Unexpectedly, we found that propensity to form homotypic Gcn4 condensates does not correlate well with transcriptional activity. Contrary to prevailing models, binding to DNA suppresses Gcn4 phase separation. Notably, the ability of Gcn4 to form soluble complexes with coactivator subunit Med15 closely mirrored the propensity to recruit Med15 into condensates, indicating that these properties are intertwined and cautioning against interpretation of mutational data without head-to-head comparisons. However, Gcn4 variants with the highest affinity for Med15 do not function as well as expected and instead have activities that reflect their abilities to phase separate with Med15. These variants therefore indeed form cellular condensates, and those attenuate activity. Our results show that transcription factors can function as soluble complexes as well as condensates, reconciling two seemingly opposing models, and have implications for other phase-separating systems.

Grammar rules and exceptions for the language of transcriptional activation domains

Transcriptional activation domains (ADs) of gene activators have remained enigmatic for decades as short, extremely variable, and structurally disordered sequences. Using a rational design and high throughput in vivo experimentation, we determine the grammar rules and exceptions for the language of ADs. According to identified rules, billions of highly active ADs can be composed of balanced amounts of acidic/aromatic amino acids, with either mixed composition of aromatic residues, or using only one aromatic residue mixed with acidic residues. However, equally active sequences can be composed of only aliphatic leucine and aspartic acid residues. The much rarer LD exceptions have a higher ratio of hydrophobic/acidic balance and display a specific LDL(L/D)DLL motif. For aromatic/acidic Ads, the intermixing of proline residues in context of amphipathic α-helix structures significantly increases the AD activity. The identified grammar rules and exceptions are interpreted in application to the biochemistry of AD function and eukaryotic gene expression.

The Enigma of Transcriptional Activation Domains

Activation domains (ADs) of eukaryotic gene activators remain enigmatic for decades as short, extremely variable sequences which often are intrinsically disordered in structure and interact with an uncertain number of targets. The general absence of specificity increasingly complicates the utilization of the widely accepted mechanism of AD function by recruitment of coactivators. The long-standing enigma at the heart of molecular biology demands a fundamental rethinking of established concepts. Here, we review the experimental evidence supporting a novel mechanistic model of gene activation, based on ADs functioning via surfactant-like near-stochastic interactions with gene promoter nucleosomes. This new model is consistent with recent information-rich experimental data obtained using high-throughput synthetic biology and bioinformatics analysis methods, including machine learning. We clarify why the conventional biochemical principle of specificity for sequence, structures, and interactions fails to explain activation domain function. This perspective provides connections to the liquid-liquid phase separation model, signifies near-stochastic interactions as fundamental for the biochemical function, and can be generalized to other cellular functions.

Revisiting the model for coactivator recruitment: Med15 can select its target sites independent of promoter-bound transcription factors

Activation domains (ADs) within transcription factors (TFs) induce gene expression by recruiting coactivators such as the Mediator complex. Coactivators lack DNA binding domains (DBDs) and are assumed to passively follow their recruiting TFs. This is supported by direct AD-coactivator interactions seen in vitro but has not yet been tested in living cells. To examine that, we targeted two Med15-recruiting ADs to a range of budding yeast promoters through fusion with different DBDs. The DBD-AD fusions localized to hundreds of genomic sites but recruited Med15 and induced transcription in only a subset of bound promoters, characterized by a fuzzy-nucleosome architecture. Direct DBD-Med15 fusions shifted DBD localization towards fuzzy-nucleosome promoters, including promoters devoid of the endogenous Mediator. We propose that Med15, and perhaps other coactivators, possess inherent promoter preference and thus actively contribute to the selection of TF-induced genes.

Nuclear and cytosolic fractions of SOX2 synergize as transcriptional and translational co-regulators of cell fate

Stemness and pluripotency are mediated by transcriptional master regulators that promote self-renewal and repress cell differentiation, among which is the high-mobility group (HMG) box transcription factor SOX2. Dysregulated SOX2 expression, by contrast, leads to transcriptional aberrations relevant to oncogenic transformation, cancer progression, metastasis, therapy resistance, and relapse. Here, we report a post-transcriptional mechanism by which the cytosolic pool of SOX2 contributes to these events in an unsuspected manner. Specifically, a low-complexity region within SOX2's C-terminal segment connects to the ribosome to modulate the expression of cognate downstream factors. Independent of nuclear structures or DNA, this C-terminal functionality alone changes metabolic properties and induces non-adhesive growth when expressed in the cytosol of SOX2 knockout cells. We thus propose a revised model of SOX2 action where nuclear and cytosolic fractions cooperate to impose cell fate decisions via both transcriptional and translational mechanisms.

EDA Fibronectin Microarchitecture and YAP Translocation During Wound Closure

Fibronectin (Fn) is an extracellular matrix glycoprotein with mechanosensitive structure-function. EDA Fn, a Fn isoform, is not present in adult tissue but is required for tissue repair. Curiously, EDA Fn is linked to both regenerative and fibrotic tissue repair. Given that Fn mechanoregulates cell behavior, Fn EDA organization during wound closure might play a role in mediating these differing responses. One mechanism by which cells sense and respond to their microenvironment is by activating a transcriptional co-activator, Yes-associated protein (YAP). Interestingly, YAP activity is not only required for wound closure, but similarly linked to both regenerative and fibrotic repair. Therefore, this study aims to evaluate how, during normal and fibrotic wound closure, EDA Fn organization might modulate YAP translocation by culturing human dermal fibroblasts on polydimethylsiloxane (PDMS) substrates mimicking normal (soft: 18 kPa) and fibrotic (stiff: 146 kPa) wounded skin. On stiffer substrates mimicking fibrotic wounds, fibroblasts assembled an aligned EDA Fn matrix comprising thinner fibers, suggesting increased microenvironmental tension. To evaluate if cell binding to the EDA domain of Fn was essential to overall matrix organization, fibroblasts were treated with Irigenin, which inhibits binding to the EDA domain within Fn. Blocking adhesion to EDA led to randomly organized EDA Fn matrices with thicker fibers, suggesting reduced microenvironmental tension even during fibrotic wound closure. To evaluate if YAP signaling plays a role in EDA Fn organization, fibroblasts were treated with CA3, which suppresses YAP activity in a dose-dependent manner. Treatment with CA3 also led to randomly organized EDA Fn matrices with thicker fibers, suggesting a potential connected mechanism of reducing tension during fibrotic wound closure. Next, YAP activity was assessed to evaluate the impact of EDA Fn organization. Interestingly, fibroblasts migrating on softer substrates mimicking normal wounds increased YAP activity but on stiffer substrates, decreased YAP activity. When fibroblasts on stiffer substrates were treated with Irigenin or CA3, fibroblasts increased YAP activity. These results suggest there may be disrupted signaling between EDA Fn organization and YAP translocation during fibrotic wound closure that could be restored when reestablishing normal EDA Fn matrix organization to instead drive regenerative wound repair.

Prediction and design of transcriptional repressor domains with large-scale mutational scans and deep learning

Regulatory proteins have evolved diverse repressor domains (RDs) to enable precise context-specific repression of transcription. However, our understanding of how sequence variation impacts the functional activity of RDs is limited. To address this gap, we generated a high-throughput mutational scanning dataset measuring the repressor activity of 115,000 variant sequences spanning more than 50 RDs in human cells. We identified thousands of clinical variants with loss or gain of repressor function, including TWIST1 HLH variants associated with Saethre-Chotzen syndrome and MECP2 domain variants associated with Rett syndrome. We also leveraged these data to annotate short linear interacting motifs (SLiMs) that are critical for repression in disordered RDs. Then, we designed a deep learning model called TENet ( T ranscriptional E ffector Net work) that integrates sequence, structure and biochemical representations of sequence variants to accurately predict repressor activity. We systematically tested generalization within and across domains with varying homology using the mutational scanning dataset. Finally, we employed TENet within a directed evolution sequence editing framework to tune the activity of both structured and disordered RDs and experimentally test thousands of designs. Our work highlights critical considerations for future dataset design and model training strategies to improve functional variant prioritization and precision design of synthetic regulatory proteins.

High-throughput affinity measurements of direct interactions between activation domains and co-activators

Sequence-specific activation by transcription factors is essential for gene regulation1,2. Key to this are activation domains, which often fall within disordered regions of transcription factors3,4 and recruit co-activators to initiate transcription5. These interactions are difficult to characterize via most experimental techniques because they are typically weak and transient6,7. Consequently, we know very little about whether these interactions are promiscuous or specific, the mechanisms of binding, and how these interactions tune the strength of gene activation. To address these questions, we developed a microfluidic platform for expression and purification of hundreds of activation domains in parallel followed by direct measurement of co-activator binding affinities (STAMMPPING, for Simultaneous Trapping of Affinity Measurements via a Microfluidic Protein-Protein INteraction Generator). By applying STAMMPPING to quantify direct interactions between eight co-activators and 204 human activation domains (>1,500 K ds), we provide the first quantitative map of these interactions and reveal 334 novel binding pairs. We find that the metazoan-specific co-activator P300 directly binds >100 activation domains, potentially explaining its widespread recruitment across the genome to influence transcriptional activation. Despite sharing similar molecular properties (e.g. enrichment of negative and hydrophobic residues), activation domains utilize distinct biophysical properties to recruit certain co-activator domains. Co-activator domain affinity and occupancy are well-predicted by analytical models that account for multivalency, and in vitro affinities quantitatively predict activation in cells with an ultrasensitive response. Not only do our results demonstrate the ability to measure affinities between even weak protein-protein interactions in high throughput, but they also provide a necessary resource of over 1,500 activation domain/co-activator affinities which lays the foundation for understanding the molecular basis of transcriptional activation.

Systematic identification of transcriptional activation domains from non-transcription factor proteins in plants and yeast

Transcription factors can promote gene expression through activation domains. Whole-genome screens have systematically mapped activation domains in transcription factors but not in non-transcription factor proteins (e.g., chromatin regulators and coactivators). To fill this knowledge gap, we employed the activation domain predictor PADDLE to analyze the proteomes of Arabidopsis thaliana and Saccharomyces cerevisiae. We screened 18,000 predicted activation domains from >800 non-transcription factor genes in both species, confirming that 89% of candidate proteins contain active fragments. Our work enables the annotation of hundreds of nuclear proteins as putative coactivators, many of which have never been ascribed any function in plants. Analysis of peptide sequence compositions reveals how the distribution of key amino acids dictates activity. Finally, we validated short, "universal" activation domains with comparable performance to state-of-the-art activation domains used for genome engineering. Our approach enables the genome-wide discovery and annotation of activation domains that can function across diverse eukaryotes.

Drug resistant pancreatic cancer cells exhibit altered biophysical interactions with stromal fibroblasts in imaging studies of 3D co-culture models

Interactions between tumor and stromal cells are well known to play a prominent roles in progression of pancreatic ductal adenocarcinoma (PDAC). As knowledge of stromal crosstalk in PDAC has evolved, it has become clear that cancer associated fibroblasts can play both tumor promoting and tumor suppressive roles through a combination of paracrine crosstalk and juxtacrine interactions involving direct physical contact. Another major contributor to dismal survival statistics for PDAC is development of resistance to chemotherapy drugs. Though less is known about how the acquisition of chemoresistance impacts upon tumor-stromal crosstalk. Here, we use 3D co-culture geometries to recapitulate juxtacrine interactions between epithelial and stromal cells. In particular, extracellular matrix (ECM) overlay cultures in which stromal cells (pancreatic stellate cells, or normal human fibroblasts) are placed adjacent to PDAC cells (PANC1), result in direct heterotypic cell adhesions accompanied by dramatic fibroblast contractility which leads to highly condensed macroscopic multicellular aggregates as detected using particle image velocimetry (PIV) analysis to quantify cell velocities over the course of time lapse movie sequences. To investigate how drug resistance impacts these juxtacrine interactions we contrast cultures in which PANC1 are substituted with a drug resistant subline (PANC1-OR) previously established in our lab. We find that heterotypic cell-cell interactions are highly suppressed in drug-resistant cells relative to the parental PANC1 cells. To investigate further we conduct RNA-seq and bioinformatics analysis to identify differential gene expression in PANC1 and PANC1-OR, which shows that negative regulation of cell adhesion molecules, consistent with increased epithelial mesenchymal transition (EMT), is also consistent with loss of hetrotypic cell-cell contact necessary for the contractile behavior observed in drug naïve cultures. Overall these findings elucidate the role of drug-resistance in inhibiting an avenue of stromal crosstalk which is associated with tumor suppression and also help to establish cell culture conditions useful for further mechanistic investigation.

Direct prediction of intermolecular interactions driven by disordered regions

Intrinsically disordered regions (IDRs) are critical for a wide variety of cellular functions, many of which involve interactions with partner proteins. Molecular recognition is typically considered through the lens of sequence-specific binding events. However, a growing body of work has shown that IDRs often interact with partners in a manner that does not depend on the precise order of the amino acid order, instead driven by complementary chemical interactions leading to disordered bound-state complexes. Despite this emerging paradigm, we lack tools to describe, quantify, predict, and interpret these types of structurally heterogeneous interactions from the underlying amino acid sequences. Here, we repurpose the chemical physics developed originally for molecular simulations to develop an approach for predicting intermolecular interactions between IDRs and partner proteins. Our approach enables the direct prediction of phase diagrams, the identification of chemically-specific interaction hotspots on IDRs, and a route to develop and test mechanistic hypotheses regarding IDR function in the context of molecular recognition. We use our approach to examine a range of systems and questions to highlight its versatility and applicability.

A Lipopeptidomimetic of Transcriptional Activation Domains Selectively Disrupts the Coactivator Med25 Protein-Protein Interactions

Short amphipathic peptides are capable of binding to transcriptional coactivators, often targeting the same binding surfaces as native transcriptional activation domains. However, they do so with modest affinity and generally poor selectivity, limiting their utility as synthetic modulators. Here we show that incorporation of a medium-chain, branched fatty acid to the N-terminus of one such heptameric lipopeptidomimetic (LPPM-8) increases the affinity for the coactivator Med25 >20-fold (Ki >100 μM to 4 μM), rendering it an effective inhibitor of Med25 protein-protein interactions (PPIs). The lipid structure, the peptide sequence, and the C-terminal functionalization of the lipopeptidomimetic each influence the structural propensity of LPPM-8 and its effectiveness as an inhibitor. LPPM-8 engages Med25 through interaction with the H2 face of its activator interaction domain and in doing so stabilizes full-length protein in the cellular proteome. Further, genes regulated by Med25-activator PPIs are inhibited in a cell model of triple-negative breast cancer. Thus, LPPM-8 is a useful tool for studying Med25 and mediator complex biology and the results indicate that lipopeptidomimetics may be a robust source of inhibitors for activator-coactivator complexes.

Predicting transcriptional activation domain function using Graph Neural Networks

Analysis of factors that lead to the functionality of transcriptional activation domains remains a crucial and yet challenging task owing to the significant diversity in their sequences and their intrinsically disordered nature. Almost all existing methods that have aimed to predict activation domains have involved traditional machine learning approaches, such as logistic regression, that are unable to capture complex patterns in data or plain convolutional neural networks and have been limited in exploration of structural features. However, there is a tremendous potential in the inspection of the structural properties of activation domains, and an opportunity to investigate complex relationships between features of residues in the sequence. To address these, we have utilized the power of graph neural networks which can represent structural data in the form of nodes and edges, allowing nodes to exchange information among themselves. We have experimented with two kinds of graph formulations, one involving residues as nodes and the other assigning atoms to be the nodes. A logistic regression model was also developed to analyze feature importance. For all the models, several feature combinations were experimented with. The residue-level GNN model with amino acid type, residue position, acidic/basic/aromatic property and secondary structure feature combination gave the best performing model with accuracy, F1 score and AUROC of 97.9%, 71% and 97.1% respectively which outperformed other existing methods in the literature when applied on the dataset we used. Among the other structure-based features that were analyzed, the amphipathic property of helices also proved to be an important feature for classification. Logistic regression results showed that the most dominant feature that makes a sequence functional is the frequency of different types of amino acids in the sequence. Our results consistent have shown that functional sequences have more acidic and aromatic residues whereas basic residues are seen more in non-functional sequences.

Fuzzy recognition by the prokaryotic transcription factor HigA2 from Vibrio cholerae

Disordered protein sequences can exhibit different binding modes, ranging from well-ordered folding-upon-binding to highly dynamic fuzzy binding. The primary function of the intrinsically disordered region of the antitoxin HigA2 from Vibrio cholerae is to neutralize HigB2 toxin through ultra-high-affinity folding-upon-binding interaction. Here, we show that the same intrinsically disordered region can also mediate fuzzy interactions with its operator DNA and, through interplay with the folded helix-turn-helix domain, regulates transcription from the higBA2 operon. NMR, SAXS, ITC and in vivo experiments converge towards a consistent picture where a specific set of residues in the intrinsically disordered region mediate electrostatic and hydrophobic interactions while "hovering" over the DNA operator. Sensitivity of the intrinsically disordered region to scrambling the sequence, position-specific contacts and absence of redundant, multivalent interactions, point towards a more specific type of fuzzy binding. Our work demonstrates how a bacterial regulator achieves dual functionality by utilizing two distinct interaction modes within the same disordered sequence.

Evolutionary analyses of intrinsically disordered regions reveal widespread signals of conservation

Intrinsically disordered regions (IDRs) are segments of proteins without stable three-dimensional structures. As this flexibility allows them to interact with diverse binding partners, IDRs play key roles in cell signaling and gene expression. Despite the prevalence and importance of IDRs in eukaryotic proteomes and various biological processes, associating them with specific molecular functions remains a significant challenge due to their high rates of sequence evolution. However, by comparing the observed values of various IDR-associated properties against those generated under a simulated model of evolution, a recent study found most IDRs across the entire yeast proteome contain conserved features. Furthermore, it showed clusters of IDRs with common "evolutionary signatures," i.e. patterns of conserved features, were associated with specific biological functions. To determine if similar patterns of conservation are found in the IDRs of other systems, in this work we applied a series of phylogenetic models to over 7,500 orthologous IDRs identified in the Drosophila genome to dissect the forces driving their evolution. By comparing models of constrained and unconstrained continuous trait evolution using the Brownian motion and Ornstein-Uhlenbeck models, respectively, we identified signals of widespread constraint, indicating conservation of distributed features is mechanism of IDR evolution common to multiple biological systems. In contrast to the previous study in yeast, however, we observed limited evidence of IDR clusters with specific biological functions, which suggests a more complex relationship between evolutionary constraints and function in the IDRs of multicellular organisms.

Intrinsically disordered regions of the Msn2 transcription factor encode multiple functions using interwoven sequence grammars

Intrinsically disordered regions (IDRs) are abundant in eukaryotic proteins, but their sequence-function relationship remains poorly understood. IDRs of transcription factors (TFs) can direct promoter selection and recruit coactivators, as shown for the budding yeast TF Msn2. To examine how IDRs encode both these functions, we compared genomic binding specificity, coactivator recruitment, and gene induction amongst a large set of designed Msn2-IDR mutants. We find that both functions depend on multiple regions across the > 600AA IDR. Yet, transcription activity was readily disrupted by mutations that showed no effect on the Msn2 binding specificity. Our data attribute this differential sensitivity to the integration of a relaxed, composition-based code directing binding specificity with a more stringent, motif-based code controlling the recruitment of coactivators and transcription activity. Therefore, Msn2 utilizes interwoven sequence grammars for encoding multiple functions, suggesting a new IDR design paradigm of potentially general use.

Targeting the heat shock response induced by modulated electro-hyperthermia (mEHT) in cancer

The Heat Shock Response (HSR) is a cellular stress reaction crucial for cell survival against stressors, including heat, in both healthy and cancer cells. Modulated electro-hyperthermia (mEHT) is an emerging non-invasive cancer therapy utilizing electromagnetic fields to selectively target cancer cells via temperature-dependent and independent mechanisms. However, mEHT triggers HSR in treated cells. Despite demonstrated efficacy in cancer treatment, understanding the underlying molecular mechanisms for improved therapeutic outcomes remains a focus. This review examines the HSR induced by mEHT in cancer cells, discussing potential strategies to modulate it for enhanced tumor-killing effects. Approaches such as HSF1 gene-knockdown and small molecule inhibitors like KRIBB11 are explored to downregulate the HSR and augment tumor destruction. We emphasize the impact of HSR inhibition on cancer cell viability, mEHT sensitivity, and potential synergistic effects, addressing challenges and future directions. This understanding offers opportunities for optimizing treatment strategies and advancing precision medicine in cancer therapy.

Defining the mechanisms and properties of post-transcriptional regulatory disordered regions by high-throughput functional profiling

Disordered regions within RNA binding proteins are required to control mRNA decay and protein synthesis. To understand how these disordered regions modulate gene expression, we surveyed regulatory activity across the entire disordered proteome using a high-throughput functional assay. We identified hundreds of regulatory sequences within intrinsically disordered regions and demonstrate how these elements cooperate with core mRNA decay machinery to promote transcript turnover. Coupling high-throughput functional profiling with mutational scanning revealed diverse molecular features, ranging from defined motifs to overall sequence composition, underlying the regulatory effects of disordered peptides. Machine learning analysis implicated aromatic residues in particular contexts as critical determinants of repressor activity, consistent with their roles in forming protein-protein interactions with downstream effectors. Our results define the molecular principles and biochemical mechanisms that govern post-transcriptional gene regulation by disordered regions and exemplify the encoding of diverse yet specific functions in the absence of well-defined structure.

Commonly asked questions about transcriptional activation domains

Eukaryotic transcription factors activate gene expression with their DNA-binding domains and activation domains. DNA-binding domains bind the genome by recognizing structurally related DNA sequences; they are structured, conserved, and predictable from protein sequences. Activation domains recruit chromatin modifiers, coactivator complexes, or basal transcriptional machinery via structurally diverse protein-protein interactions. Activation domains and DNA-binding domains have been called independent, modular units, but there are many departures from modularity, including interactions between these regions and overlap in function. Compared to DNA-binding domains, activation domains are poorly understood because they are poorly conserved, intrinsically disordered, and difficult to predict from protein sequences. This review, organized around commonly asked questions, describes recent progress that the field has made in understanding the sequence features that control activation domains and predicting them from sequence.

Haploinsufficient Transcription Factors in Myeloid Neoplasms

Many transcription factors (TFs) function as tumor suppressor genes with heterozygous phenotypes, yet haploinsufficiency generally has an underappreciated role in neoplasia. This is no less true in myeloid cells, which are normally regulated by a delicately balanced and interconnected transcriptional network. Detailed understanding of TF dose in this circuitry sheds light on the leukemic transcriptome. In this review, we discuss the emerging features of haploinsufficient transcription factors (HITFs). We posit that: (a) monoallelic and biallelic losses can have distinct cellular outcomes; (b) the activity of a TF exists in a greater range than the traditional Mendelian genetic doses; and (c) how a TF is deleted or mutated impacts the cellular phenotype. The net effect of a HITF is a myeloid differentiation block and increased intercellular heterogeneity in the course of myeloid neoplasia.

Molecular switching in transcription through splicing and proline-isomerization regulates stress responses in plants

The Arabidopsis thaliana DREB2A transcription factor interacts with the negative regulator RCD1 and the ACID domain of subunit 25 of the transcriptional co-regulator mediator (Med25) to integrate stress signals for gene expression, with elusive molecular interplay. Using biophysical and structural analyses together with high-throughput screening, we reveal a bivalent binding switch in DREB2A containing an ACID-binding motif (ABS) and the known RCD1-binding motif (RIM). The RIM is lacking in a stress-induced DREB2A splice variant with retained transcriptional activity. ABS and RIM bind to separate sites on Med25-ACID, and NMR analyses show a structurally heterogeneous complex deriving from a DREB2A-ABS proline residue populating cis- and trans-isomers with remote impact on the RIM. The cis-isomer stabilizes an α-helix, while the trans-isomer may introduce energetic frustration facilitating rapid exchange between activators and repressors. Thus, DREB2A uses a post-transcriptionally and post-translationally modulated switch for transcriptional regulation.

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination

Proteins play a crucial role in many biological processes, where their interaction with other proteins are integral. Abnormal protein-protein interactions (PPIs) have been linked to various diseases including cancer, and thus targeting PPIs holds promise for drug development. However, experimental confirmation of the peculiarities of PPIs is challenging due to their dynamic and transient nature. As a complement to experimental technologies, multiple computational molecular docking (MD) methods have been developed to predict the structures of protein-protein complexes and their dynamics, still requiring further improvements in several issues. Here, we report an improved MD method, namely three-software docking (3SD), by employing three popular protein-peptide docking software (CABS-dock, HPEPDOCK, and HADDOCK) in combination to ensure constant quality for most targets. We validated our 3SD performance in known protein-peptide interactions (PpIs). We also enhanced MD performance in proteins having intrinsically disordered regions (IDRs) by applying the modified 3SD strategy, the three-software docking after removing random coiled IDR (3SD-RR), to the comparable crystal PpI structures. At the end, we applied 3SD-RR to the AlphaFold2-predicted receptors, yielding an efficient prediction of PpI pose with high relevance to the experimental data regardless of the presence of IDRs or the availability of receptor structures. Our study provides an improved solution to the challenges in studying PPIs through computational docking and has the potential to contribute to PPIs-targeted drug discovery. SIGNIFICANCE STATEMENT: Protein-protein interactions (PPIs) are integral to life, and abnormal PPIs are associated with diseases such as cancer. Studying protein-peptide interactions (PpIs) is challenging due to their dynamic and transient nature. Here we developed improved docking methods (3SD and 3SD-RR) to predict the PpI poses, ensuring constant quality in most targets and also addressing issues like intrinsically disordered regions (IDRs) and artificial intelligence-predicted structures. Our study provides an improved solution to the challenges in studying PpIs through computational docking and has the potential to contribute to PPIs-targeted drug discovery.

Transcriptional co-activators: emerging roles in signaling pathways and potential therapeutic targets for diseases

Specific cell states in metazoans are established by the symphony of gene expression programs that necessitate intricate synergic interactions between transcription factors and the co-activators. Deregulation of these regulatory molecules is associated with cell state transitions, which in turn is accountable for diverse maladies, including developmental disorders, metabolic disorders, and most significantly, cancer. A decade back most transcription factors, the key enablers of disease development, were historically viewed as 'undruggable'; however, in the intervening years, a wealth of literature validated that they can be targeted indirectly through transcriptional co-activators, their confederates in various physiological and molecular processes. These co-activators, along with transcription factors, have the ability to initiate and modulate transcription of diverse genes necessary for normal physiological functions, whereby, deregulation of such interactions may foster tissue-specific disease phenotype. Hence, it is essential to analyze how these co-activators modulate specific multilateral processes in coordination with other factors. The proposed review attempts to elaborate an in-depth account of the transcription co-activators, their involvement in transcription regulation, and context-specific contributions to pathophysiological conditions. This review also addresses an issue that has not been dealt with in a comprehensive manner and hopes to direct attention towards future research that will encompass patient-friendly therapeutic strategies, where drugs targeting co-activators will have enhanced benefits and reduced side effects. Additional insights into currently available therapeutic interventions and the associated constraints will eventually reveal multitudes of advanced therapeutic targets aiming for disease amelioration and good patient prognosis.

Sequence-ensemble-function relationships for disordered proteins in live cells

Intrinsically disordered protein regions (IDRs) are ubiquitous across all kingdoms of life and play a variety of essential cellular roles. IDRs exist in a collection of structurally distinct conformers known as an ensemble. An IDR's amino acid sequence determines its ensemble, which in turn can play an important role in dictating molecular function. Yet a clear link connecting IDR sequence, its ensemble properties, and its molecular function in living cells has not been directly established. Here, we set out to test this sequence-ensemble-function paradigm using a novel computational method (GOOSE) that enables the rational design of libraries of IDRs by systematically varying specific sequence properties. Using ensemble FRET, we measured the ensemble dimensions of a library of rationally designed IDRs in human-derived cell lines, revealing how IDR sequence influences ensemble dimensions in situ. Furthermore, we show that the interplay between sequence and ensemble can tune an IDR's ability to sense changes in cell volume - a de novo molecular function for these synthetic sequences. Our results establish biophysical rules for intracellular sequence-ensemble relationships, enable a new route for understanding how IDR sequences map to function in live cells, and set the ground for the design of synthetic IDRs with de novo function.

Sequence-ensemble-function relationships for disordered proteins in live cells

Intrinsically disordered protein regions (IDRs) are ubiquitous across all kingdoms of life and play a variety of essential cellular roles. IDRs exist in a collection of structurally distinct conformers known as an ensemble. IDR amino acid sequence determines its ensemble, which in turn can play an important role in dictating molecular function. Yet a clear link connecting IDR sequence, its ensemble properties, and its molecular function in living cells has not been systematically established. Here, we set out to test this sequence-ensemble-function paradigm using a novel computational method (GOOSE) that enables the rational design of libraries of IDRs by systematically varying specific sequence properties. Using ensemble FRET, we measured the ensemble dimensions of a library of rationally designed IDRs in human-derived cell lines, revealing how IDR sequence influences ensemble dimensions in situ. Furthermore, we show that the interplay between sequence and ensemble can tune an IDR's ability to sense changes in cell volume - a de novomolecular function for these synthetic sequences. Our results establish biophysical rules for intracellular sequence-ensemble relationships, enable a new route for understanding how IDR sequences map to function in live cells, and set the ground for the design of synthetic IDRs with de novo function.

Heat Shock Factor 1 Inhibition: A Novel Anti-Cancer Strategy with Promise for Precision Oncology

Heat shock factor 1 (HSF1) is a transcription factor crucial for regulating heat shock response (HSR), one of the significant cellular protective mechanisms. When cells are exposed to proteotoxic stress, HSF1 induces the expression of heat shock proteins (HSPs) to act as chaperones, correcting the protein-folding process and maintaining proteostasis. In addition to its role in HSR, HSF1 is overexpressed in multiple cancer cells, where its activation promotes malignancy and leads to poor prognosis. The mechanisms of HSF1-induced tumorigenesis are complex and involve diverse signaling pathways, dependent on cancer type. With its important roles in tumorigenesis and tumor progression, targeting HSF1 offers a novel cancer treatment strategy. In this article, we examine the basic function of HSF1 and its regulatory mechanisms, focus on the mechanisms involved in HSF1's roles in different cancer types, and examine current HSF1 inhibitors as novel therapeutics to treat cancers.

ECM-Focused Proteomic Analysis of Ear Punch Regeneration in Acomys Cahirinus

In mammals, significant injury is generally followed by the formation of a fibrotic scar which provides structural integrity but fails to functionally restore damaged tissue. Spiny mice of the genus Acomys represent the first example of full skin autotomy in mammals. Acomys cahirinus has evolved extremely weak skin as a strategy to avoid predation and is able to repeatedly regenerate healthy tissue without scar after severe skin injury or full-thickness ear punches. Extracellular matrix (ECM) composition is a critical regulator of wound repair and scar formation and previous studies have suggested that alterations in its expression may be responsible for the differences in regenerative capacity observed between Mus musculus and A. cahirinus , yet analysis of this critical tissue component has been limited in previous studies by its insolubility and resistance to extraction. Here, we utilize a 2-step ECM-optimized extraction to perform proteomic analysis of tissue composition during wound repair after full-thickness ear punches in A. cahirinus and M. musculus from weeks 1 to 4 post-injury. We observe changes in a wide range of ECM proteins which have been previously implicated in wound regeneration and scar formation, including collagens, coagulation and provisional matrix proteins, and matricryptic signaling peptides. We additionally report differences in crosslinking enzyme activity and ECM protein solubility between Mus and Acomys. Furthermore, we observed rapid and sustained increases in CD206, a marker of pro-regenerative M2 macrophages, in Acomys, whereas little or no increase in CD206 was detected in Mus. Together, these findings contribute to a comprehensive understanding of tissue cues which drive the regenerative capacity of Acomys and identify a number of potential targets for future pro-regenerative therapies.

Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence

Transcription factors activate gene expression in development, homeostasis, and stress with DNA binding domains and activation domains. Although there exist excellent computational models for predicting DNA binding domains from protein sequence, models for predicting activation domains from protein sequence have lagged, particularly in metazoans. We recently developed a simple and accurate predictor of acidic activation domains on human transcription factors. Here, we show how the accuracy of this human predictor arises from the clustering of aromatic, leucine, and acidic residues, which together are necessary for acidic activation domain function. When we combine our predictor with the predictions of convolutional neural network (CNN) models trained in yeast, the intersection is more accurate than individual models, emphasizing that each approach carries orthogonal information. We synthesize these findings into a new set of activation domain predictions on human transcription factors.

High-throughput functional characterization of combinations of transcriptional activators and repressors

Despite growing knowledge of the functions of individual human transcriptional effector domains, much less is understood about how multiple effector domains within the same protein combine to regulate gene expression. Here, we measure transcriptional activity for 8,400 effector domain combinations by recruiting them to reporter genes in human cells. In our assay, weak and moderate activation domains synergize to drive strong gene expression, whereas combining strong activators often results in weaker activation. In contrast, repressors combine linearly and produce full gene silencing, and repressor domains often overpower activation domains. We use this information to build a synthetic transcription factor whose function can be tuned between repression and activation independent of recruitment to target genes by using a small-molecule drug. Altogether, we outline the basic principles of how effector domains combine to regulate gene expression and demonstrate their value in building precise and flexible synthetic biology tools. A record of this paper's transparent peer review process is included in the supplemental information.

Systematic identification of transcriptional activator domains from non-transcription factor proteins in plants and yeast

Transcription factors promote gene expression via trans-regulatory activation domains. Although whole genome scale screens in model organisms (e.g. human, yeast, fly) have helped identify activation domains from transcription factors, such screens have been less extensively used to explore the occurrence of activation domains in non-transcription factor proteins, such as transcriptional coactivators, chromatin regulators and some cytosolic proteins, leaving a blind spot on what role activation domains in these proteins could play in regulating transcription. We utilized the activation domain predictor PADDLE to mine the entire proteomes of two model eukaryotes, Arabidopsis thaliana and Saccharomyces cerevisiae ( 1 ). We characterized 18,000 fragments covering predicted activation domains from >800 non-transcription factor genes in both species, and experimentally validated that 89% of proteins contained fragments capable of activating transcription in yeast. Peptides with similar sequence composition show a broad range of activities, which is explained by the arrangement of key amino acids. We also annotated hundreds of nuclear proteins with activation domains as putative coactivators; many of which have never been ascribed any function in plants. Furthermore, our library contains >250 non-nuclear proteins containing peptides with activation domain function across both eukaryotic lineages, suggesting that there are unknown biological roles of these peptides beyond transcription. Finally, we identify and validate short, 'universal' eukaryotic activation domains that activate transcription in both yeast and plants with comparable or stronger performance to state-of-the-art activation domains. Overall, our dual host screen provides a blueprint on how to systematically discover novel genetic parts for synthetic biology that function across a wide diversity of eukaryotes.

Significance Statement

Activation domains promote transcription and play a critical role in regulating gene expression. Although the mapping of activation domains from transcription factors has been carried out in previous genome-wide screens, their occurrence in non-transcription factors has been less explored. We utilize an activation domain predictor to mine the entire proteomes of Arabidopsis thaliana and Saccharomyces cerevisiae for new activation domains on non-transcription factor proteins. We validate peptides derived from >750 non-transcription factor proteins capable of activating transcription, discovering many potentially new coactivators in plants. Importantly, we identify novel genetic parts that can function across both species, representing unique synthetic biology tools.

The molecular grammar of protein disorder guiding genome-binding locations

Intrinsically disordered regions (IDRs) direct transcription factors (TFs) towards selected genomic occurrences of their binding motif, as exemplified by budding yeast's Msn2. However, the sequence basis of IDR-directed TF binding selectivity remains unknown. To reveal this sequence grammar, we analyze the genomic localizations of >100 designed IDR mutants, each carrying up to 122 mutations within this 567-AA region. Our data points at multivalent interactions, carried by hydrophobic-mostly aliphatic-residues dispersed within a disordered environment and independent of linear sequence motifs, as the key determinants of Msn2 genomic localization. The implications of our results for the mechanistic basis of IDR-based TF binding preferences are discussed.

The next wave of interactomics: Mapping the SLiM-based interactions of the intrinsically disordered proteome

Short linear motifs (SLiMs) are a unique and ubiquitous class of protein interaction modules that perform key regulatory functions and drive dynamic complex formation. For decades, interactions mediated by SLiMs have accumulated through detailed low-throughput experiments. Recent methodological advances have opened this previously underexplored area of the human interactome to high-throughput protein-protein interaction discovery. In this article, we discuss that SLiM-based interactions represent a significant blind spot in the current interactomics data, introduce the key methods that are illuminating the elusive SLiM-mediated interactome of the human cell on a large scale, and discuss the implications for the field.

Surveying the global landscape of post-transcriptional regulators

Numerous proteins regulate gene expression by modulating mRNA translation and decay. To uncover the full scope of these post-transcriptional regulators, we conducted an unbiased survey that quantifies regulatory activity across the budding yeast proteome and delineates the protein domains responsible for these effects. Our approach couples a tethered function assay with quantitative single-cell fluorescence measurements to analyze ~50,000 protein fragments and determine their effects on a tethered mRNA. We characterize hundreds of strong regulators, which are enriched for canonical and unconventional mRNA-binding proteins. Regulatory activity typically maps outside the RNA-binding domains themselves, highlighting a modular architecture that separates mRNA targeting from post-transcriptional regulation. Activity often aligns with intrinsically disordered regions that can interact with other proteins, even in core mRNA translation and degradation factors. Our results thus reveal networks of interacting proteins that control mRNA fate and illuminate the molecular basis for post-transcriptional gene regulation.

Interaction modules that impart specificity to disordered protein

Intrinsically disordered regions (IDRs) are especially enriched among proteins that regulate chromatin and transcription. As a result, mechanisms that influence specificity of IDR-driven interactions have emerged as exciting unresolved issues for understanding gene regulation. We review the molecular elements frequently found within IDRs that confer regulatory specificity. In particular, we summarize the differing roles of disordered low-complexity regions (LCRs) and short linear motifs (SLiMs) towards selective nuclear regulation. Examination of IDR-driven interactions highlights SLiMs as organizers of selectivity, with widespread roles in gene regulation and integration of cellular signals. Analysis of recurrent interactions between SLiMs and folded domains suggests diverse avenues for SLiMs to influence phase-separated condensates and highlights opportunities to manipulate these interactions for control of biological activity.

Targeting HSF1 for cancer treatment: mechanisms and inhibitor development

Heat Shock Factor 1 (HSF1) is a master regulator of heat shock responsive signaling. In addition to playing critical roles in cellular heat shock response, emerging evidence suggests that HSF1 also regulates a non-heat shock responsive transcriptional network to handle metabolic, chemical, and genetic stress. The function of HSF1 in cellular transformation and cancer development has been extensively studied in recent years. Due to important roles for HSF1 for coping with various stressful cellular states, research on HSF1 has been very active. New functions and molecular mechanisms underlying these functions have been continuously discovered, providing new targets for novel cancer treatment strategies. In this article, we review the essential roles and mechanisms of HSF1 action in cancer cells, focusing more on recently discovered functions and their underlying mechanisms to reflect the new advances in cancer biology. In addition, we emphasize new advances with regard to HSF1 inhibitors for cancer drug development.

A lipopeptidomimetic of transcriptional activation domains selectively disrupts Med25 PPIs

Short amphipathic peptides are capable of binding to transcriptional coactivators, often targeting the same binding surfaces as native transcriptional activation domains. However, they do so with modest affinity and generally poor selectivity, limiting their utility as synthetic modulators. Here we show that incorporation of a medium-chain, branched fatty acid to the N-terminus of one such heptameric lipopeptidomimetic (34913-8) increases the affinity for the coactivator Med25 >10-fold ( Ki >>100 μM to 10 μM). Importantly, the selectivity of 34913-8 for Med25 compared to other coactivators is excellent. 34913-8 engages Med25 through interaction with the H2 face of its Ac tivator I nteraction D omain and in doing so stabilizes full-length protein in the cellular proteome. Further, genes regulated by Med25-activator PPIs are inhibited in a cell model of triple-negative breast cancer. Thus, 34913-8 is a useful tool for studying Med25 and the Mediator complex biology and the results indicate that lipopeptidomimetics may be a robust source of inhibitors for activator-coactivator complexes.

Systematic identification and characterization of repressive domains in Drosophila transcription factors

All multicellular life relies on differential gene expression, determined by regulatory DNA elements and DNA-binding transcription factors that mediate activation and repression via cofactor recruitment. While activators have been extensively characterized, repressors are less well studied: the identities and properties of their repressive domains (RDs) are typically unknown and the specific co-repressors (CoRs) they recruit have not been determined. Here, we develop a high-throughput, next-generation sequencing-based screening method, repressive-domain (RD)-seq, to systematically identify RDs in complex DNA-fragment libraries. Screening more than 200,000 fragments covering the coding sequences of all transcription-related proteins in Drosophila melanogaster, we identify 195 RDs in known repressors and in proteins not previously associated with repression. Many RDs contain recurrent short peptide motifs, which are conserved between fly and human and are required for RD function, as demonstrated by motif mutagenesis. Moreover, we show that RDs that contain one of five distinct repressive motifs interact with and depend on different CoRs, such as Groucho, CtBP, Sin3A, or Smrter. These findings advance our understanding of repressors, their sequences, and the functional impact of sequence-altering mutations and should provide a valuable resource for further studies.

HSF1, Aging, and Neurodegeneration

Heat shock factor 1 (HSF1) is a master transcription regulator that mediates the induction of heat shock protein chaperones for quality control (QC) of the proteome and maintenance of proteostasis as a protective mechanism in response to stress. Research in this particular area has accelerated dramatically over the past three decades following successful isolation, cloning, and characterization of HSF1. The intricate multi-protein complexes and transcriptional activation orchestrated by HSF1 are fundamental processes within the cellular QC machinery. Our primary focus is on the regulation and function of HSF1 in aging and neurodegenerative diseases (ND) which represent physiological and pathological states of dysfunction in protein QC. This chapter presents an overview of HSF1 structural, functional, and energetic properties in healthy cells while addressing the deterioration of HSF1 function viz-à-viz age-dependent and neuron-specific vulnerability to ND. We discuss the structural domains of HSF1 with emphasis on the intrinsically disordered regions and note that disease proteins associated with ND are often structurally disordered and exquisitely sensitive to changes in cellular environment as may occur during aging. We propose a hypothesis that age-dependent changes of the intrinsically disordered proteome likely hold answers to understand many of the functional, structural, and organizational changes of proteins and signaling pathways in aging - dysfunction of HSF1 and accumulation of disease protein aggregates in ND included.Structured AbstractsIntroduction: Heat shock factor 1 (HSF1) is a master transcription regulator that mediates the induction of heat shock protein chaperones for quality control (QC) of the proteome as a cyto-protective mechanism in response to stress. There is cumulative evidence of age-related deterioration of this QC mechanism that contributes to disease vulnerability.

OBJECTIVES

Herein we discuss the regulation and function of HSF1 as they relate to the pathophysiological changes of protein quality control in aging and neurodegenerative diseases (ND).

METHODS

We present an overview of HSF1 structural, functional, and energetic properties in healthy cells while addressing the deterioration of HSF1 function vis-à-vis age-dependent and neuron-specific vulnerability to neurodegenerative diseases.

RESULTS

We examine the impact of intrinsically disordered regions on the function of HSF1 and note that proteins associated with neurodegeneration are natively unstructured and exquisitely sensitive to changes in cellular environment as may occur during aging.

CONCLUSIONS

We put forth a hypothesis that age-dependent changes of the intrinsically disordered proteome hold answers to understanding many of the functional, structural, and organizational changes of proteins - dysfunction of HSF1 in aging and appearance of disease protein aggregates in neurodegenerative diseases included.

Connecting sequence features within the disordered C-terminal linker of Bacillus subtilis FtsZ to functions and bacterial cell division

Intrinsically disordered regions (IDRs) can function as autoregulators of folded enzymes to which they are tethered. One example is the bacterial cell division protein FtsZ. This includes a folded core and a C-terminal tail (CTT) that encompasses a poorly conserved, disordered C-terminal linker (CTL) and a well-conserved 17-residue C-terminal peptide (CT17). Sites for GTPase activity of FtsZs are formed at the interface between GTP binding sites and T7 loops on cores of adjacent subunits within dimers. Here, we explore the basis of autoregulatory functions of the CTT in Bacillus subtilis FtsZ (Bs-FtsZ). Molecular simulations show that the CT17 of Bs-FtsZ makes statistically significant CTL-mediated contacts with the T7 loop. Statistical coupling analysis of more than 1,000 sequences from FtsZ orthologs reveals clear covariation of the T7 loop and the CT17 with most of the core domain, whereas the CTL is under independent selection. Despite this, we discover the conservation of nonrandom sequence patterns within CTLs across orthologs. To test how the nonrandom patterns of CTLs mediate CTT-core interactions and modulate FtsZ functionalities, we designed Bs-FtsZ variants by altering the patterning of oppositely charged residues within the CTL. Such alterations disrupt the core-CTT interactions, lead to anomalous assembly and inefficient GTP hydrolysis in vitro and protein degradation, aberrant assembly, and disruption of cell division in vivo. Our findings suggest that viable CTLs in FtsZs are likely to be IDRs that encompass nonrandom, functionally relevant sequence patterns that also preserve three-way covariation of the CT17, the T7 loop, and core domain.

Transcription factors perform a 2-step search of the nucleus

Transcription factors regulate gene expression by binding to regulatory DNA and recruiting regulatory protein complexes. The DNA-binding and protein-binding functions of transcription factors are traditionally described as independent functions performed by modular protein domains. Here, I argue that genome binding can be a 2-part process with both DNA-binding and protein-binding steps, enabling transcription factors to perform a 2-step search of the nucleus to find their appropriate binding sites in a eukaryotic genome. I support this hypothesis with new and old results in the literature, discuss how this hypothesis parsimoniously resolves outstanding problems, and present testable predictions.

An intrinsically disordered transcription activation domain increases the DNA binding affinity and reduces the specificity of NFκB p50/RelA

Many transcription factors contain intrinsically disordered transcription activation domains (TADs), which mediate interactions with coactivators to activate transcription. Historically, DNA-binding domains and TADs have been considered as modular units, but recent studies have shown that TADs can influence DNA binding. Whether these results can be generalized to more TADs is not clear. Here, we biophysically characterized the NFκB p50/RelA heterodimer including the RelA TAD and investigated the TAD's influence on NFκB-DNA interactions. In solution, we show the RelA TAD is disordered but compact, with helical tendency in two regions that interact with coactivators. We determined that the presence of the TAD increased the stoichiometry of NFκB-DNA complexes containing promoter DNA sequences with tandem κB recognition motifs by promoting the binding of NFκB dimers in excess of the number of κB sites. In addition, we measured the binding affinity of p50/RelA for DNA containing tandem κB sites and single κB sites. While the presence of the TAD enhanced the binding affinity of p50/RelA for all κB sequences tested, it also increased the affinity for nonspecific DNA sequences by over 10-fold, leading to an overall decrease in specificity for κB DNA sequences. In contrast, previous studies have generally reported that TADs decrease DNA-binding affinity and increase sequence specificity. Our results reveal a novel function of the RelA TAD in promoting binding to nonconsensus DNA, which sheds light on previous observations of extensive nonconsensus DNA binding by NFκB in vivo in response to strong inflammatory signals.

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

A major challenge to the characterization of intrinsically disordered regions (IDRs), which are widespread in the proteome, but relatively poorly understood, is the identification of molecular features that mediate functions of these regions, such as short motifs, amino acid repeats and physicochemical properties. Here, we introduce a proteome-scale feature discovery approach for IDRs. Our approach, which we call "reverse homology", exploits the principle that important functional features are conserved over evolution. We use this as a contrastive learning signal for deep learning: given a set of homologous IDRs, the neural network has to correctly choose a held-out homolog from another set of IDRs sampled randomly from the proteome. We pair reverse homology with a simple architecture and standard interpretation techniques, and show that the network learns conserved features of IDRs that can be interpreted as motifs, repeats, or bulk features like charge or amino acid propensities. We also show that our model can be used to produce visualizations of what residues and regions are most important to IDR function, generating hypotheses for uncharacterized IDRs. Our results suggest that feature discovery using unsupervised neural networks is a promising avenue to gain systematic insight into poorly understood protein sequences.