Abstract Changes in cellular pH act as potent upstream signals that rewire phosphorylation networks controlling cellular function and disease. In yeast, this response is thought to arise mainly from pH-dependent perturbations to membrane integrity and cell wall stress, which are relayed through TORC2- and PKC-dependent signaling pathways. Yet several proteins exhibit acid-dependent phosphorylation independently of TORC2 and PKC, pointing to additional, uncharacterized acid stress signaling mechanisms. To investigate this possibility, we performed SILAC-based deep phosphoproteomics to distinguish phosphoproteome changes that are dependent on plasma membrane and cell wall stress from those that are independent. Across more than 19,000 unique phosphosites, we identified over 1,000 sites whose acid stress–dependent regulation occurs outside the canonical acid stress pathways. These noncanonical targets were significantly enriched in proteins associated with the plasma membrane, GTPase-mediated signaling, and endocytosis. Motif analysis revealed enrichment of acidophilic substrates implicating the membrane-tethered casein kinase Yck1 as a major mediator of this response. In contrast, canonical acid stress signaling preferentially involved basophilic kinase substrates, while acid-repressed responses were enriched for proline-containing phosphosites involved in cell cycle progression. Collectively, these results uncover a distinct acid-responsive phosphorylation network that operates independently of plasma membrane and cell wall integrity signaling.

The extracellular matrix (ECM) is a protein polymer network that physically supports cells within a tissue. It acts as an important physical and biochemical stimulus directing cell behaviors. For fibronectin (Fn), a predominant component of the ECM, these physical and biochemical activities are inextricably linked as physical forces trigger conformational changes that impact its biochemical activity. Here, we analyze whether oxidative post-translational modifications, specifically glutathionylation, alter Fn’s mechano-chemical characteristics through stretch-dependent protein modification. ECM post-translational modifications represent a potential for time- or stimulus-dependent changes in ECM structure-function relationships that could persist over time with potentially significant impacts on cell and tissue behaviors. In this study, we show evidence that glutathionylation of Fn ECM fibers is stretch-dependent and alters Fn fiber mechanical properties with implications on the selectivity of engaging integrin receptors. These data demonstrate the existence of multimodal post-translational modification mechanisms within the ECM with high relevance to the microenvironmental regulation of downstream cell behaviors. Post-translational modifications potentially alter the biochemical and biophysical properties of the extracellular matrix in significant ways. Here, the authors discover that glutathionylation alters the properties of the matrix protein fibronectin.

In patients with von-Hippel Lindau (VHL) disease, hypoxia-independent accumulation of HIF-2α leads to increased transcriptional activity of HIF-2α:ARNT that drives cancers such as renal cell carcinoma. Belzutifan, a recently FDA-approved drug, is designed to prevent the transcriptional activity of HIF-2α:ARNT, thereby overcoming the consequences of its unnatural accumulation in VHL-dependent cancers. Emerging evidence suggests that the naturally occurring variant G323E located in the HIF-2α drug binding pocket prevents inhibitory activity of belzutifan analogs, though the mechanism of inhibition remains unclear. Interestingly, proximal phosphorylation at neighboring T324, previously shown to regulate HIF-2 protein interactions, has also been proposed to affect HIF-2 drug binding. Here, we used molecular dynamics (MD) simulations to understand and compare the molecular-level effects of G323E and phospho-T324 (pT324) on the belzutifan bound-HIF-2α:ARNT complex. We find that both G323E and pT324 increase structural flexibility within the drug binding site and reduce the apparent binding affinity for belzutifan. Whereas the effects of G323E are concentrated in the binding pocket Fα helix within the HIF-2α PAS-B domain, pT324 decreased the belzutifan binding affinity and stabilized the HIF-2 heterodimer through an alternate mechanism involving polar interactions between the HIF-2α PAS-B and PAS-A domains. Further analysis via ensemble machine learning uncovered important and distinct interchain residue interactions modified by G323E and pT324. These findings reveal a molecular mechanism of G323E-induced drug resistance and suggest that pT324 may also affect the efficacy of HIF-2 drug binding interactions via allosteric effects.

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the β-hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of β hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial β-hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

Studies of folded-to-misfolded transitions using model protein systems reveal a range of unfolding needed for exposure of amyloid-prone regions for subsequent fibrillization. Here, we probe the relationship between unfolding and aggregation for glaucoma-associated myocilin. Mutations within the olfactomedin domain of myocilin (OLF) cause a gain-of-function, namely cytotoxic intracellular aggregation, which hastens disease progression. Aggregation by wild-type OLF (OLF WT ) competes with its chemical unfolding, but only below the threshold where OLF loses tertiary structure. Representative moderate (OLF D380A ) and severe (OLF I499F ) disease variants aggregate differently, with rates comparable to OLF WT in initial stages of unfolding, and variants adopt distinct partially folded structures seen along the OLF WT urea-unfolding pathway. Whether initiated with mutation or chemical perturbation, unfolding propagates outward to the propeller surface. In sum, for this large protein prone to amyloid formation, the requirement for a conformational change to promote amyloid fibrillization leads to direct competition between unfolding and aggregation.

14-3-3s are abundant proteins that regulate essentially all aspects of cell biology, including cell cycle, motility, metabolism, and cell death. 14-3-3s work by docking to phosphorylated Ser/Thr residues on a large network of client proteins and modulating client protein function in a variety of ways. In recent years, aided by improvements in proteomics, the discovery of 14-3-3 client proteins has far outpaced our ability to understand the biological impact of individual 14-3-3 interactions. The rate-limiting step in this process is often the identification of the individual phospho-serines/threonines that mediate 14-3-3 binding, which are difficult to distinguish from other phospho-sites by sequence alone. Furthermore, trial-and-error molecular approaches to identify these phosphorylations are costly and can take months or years to identify even a single 14-3-3 docking site phosphorylation. To help overcome this challenge, we used machine learning to analyze predictive features of 14-3-3 binding sites. We found that accounting for intrinsic protein disorder and the unbiased mass spectrometry identification rate of a given phosphorylation significantly improves the identification of 14-3-3 docking site phosphorylations across the proteome. We incorporated these features, coupled with consensus sequence prediction, into a publicly available web app, called "14-3-3 site-finder". We demonstrate the strength of this approach through its ability to identify 14-3-3 binding sites that do not conform to the loose consensus sequence of 14-3-3 docking phosphorylations, which we validate with 14-3-3 client proteins, including TNK1, CHEK1, MAPK7, and others. In addition, by using this approach, we identify a phosphorylation on A-kinase anchor protein-13 (AKAP13) at Ser2467 that dominantly controls its interaction with 14-3-3.

Heme b (iron protoporphyrin IX) plays important roles in biology as a metallocofactor and signaling molecule. However, the targets of heme signaling and the network of proteins that mediate the exchange of heme from sites of synthesis or uptake to heme dependent or regulated proteins are poorly understood. Herein, we describe a quantitative mass spectrometry (MS)-based chemoproteomics strategy to identify exchange labile hemoproteins in human embryonic kidney HEK293 cells that may be relevant to heme signaling and trafficking. The strategy involves depleting endogenous heme with the heme biosynthetic inhibitor succinylacetone (SA), leaving putative heme-binding proteins in their apo-state, followed by the capture of those proteins using hemin-agarose resin, and finally elution and identification by MS. By identifying only those proteins that interact with high specificity to hemin-agarose relative to control beaded agarose in an SA-dependent manner, we have expanded the number of proteins and ontologies that may be involved in binding and buffering labile heme or are targets of heme signaling. Notably, these include proteins involved in chromatin remodeling, DNA damage response, RNA splicing, cytoskeletal organization, and vesicular trafficking, many of which have been associated with heme through complementary studies published recently. Taken together, these results provide support for the emerging role of heme in an expanded set of cellular processes from genome integrity to protein trafficking and beyond.

Activated G protein-coupled receptors promote the dissociation of heterotrimeric G proteins into Gα and Gβγ subunits that bind to effector proteins to drive intracellular signaling responses. In yeast, Gβγ subunits coordinate the simultaneous activation of multiple signaling axes in response to mating pheromones, including MAP kinase (MAPK)-dependent transcription, cell polarization, and cell cycle arrest responses. The Gγ subunit in this complex contains an N-terminal intrinsically disordered region that governs Gβγ-dependent signal transduction in yeast and mammals. Here, we demonstrate that N-terminal intrinsic disorder is likely an ancestral feature that has been conserved across different Gγ subtypes and organisms. To understand the functional contribution of structural disorder in this region, we introduced precise point mutations that produce a stepwise disorder-to-order transition in the N-terminal tail of the canonical yeast Gγ subunit, Ste18. Mutant tail structures were confirmed using circular dichroism and molecular dynamics and then substituted for the wildtype gene in yeast. We find that increasing the number of helix-stabilizing mutations, but not isometric mutation controls, has a negative and proteasome-independent effect on Ste18 protein levels as well as a differential effect on pheromone-induced levels of active MAPK/Fus3, but not MAPK/Kss1. When expressed at wildtype levels, we further show that mutants with an alpha-helical N terminus exhibit a counterintuitive shift in Gβγ signaling that reduces active MAPK/Fus3 levels whilst increasing cell polarization and cell cycle arrest. These data reveal a role for Gγ subunit intrinsically disordered regions in governing the balance between multiple Gβγ signaling axes.

Granulomatous inflammation around parasite eggs is the prominent lesion in human schistosomiasis. Studies have suggested the involvement of a series of suppressive mechanisms in the control of this reaction, such as macrophages, cytokines, idiotipic interactions and immune complexes (IC). The studies examine the role of IC obtained from chronic intestinal schistosomiasis patients (ISP) in the reactivity of peripheral blood mononuclear cells (PBMC). The results have shown that these immune complexes are able to suppress cell reactivity by inducing an increase in the production of soluble mediators such as prostaglandins and IL-10. To gain a better understanding of how this suppression occurs the present study examines the phenotypic pattern of PBMC after immune complex treatment in cell proliferation assays. These data show that cultures including immune complex present a higher percentage of B lymphocytes in which a lower expression of a MHC-class II gene product, HLA-DR was detected. This altered expression of the HLA-DR molecule on B lymphocytes after IC treatment suggests a novel mechanism for the suppression observed, that is, IC might decrease the antigen-presenting function of B lymphocytes.

Protein posttranslational modifications (PTMs) are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof, the number of functionals PTMs in the eukaryotic proteome is currently underestimated. Furthermore, not all PTMs are functionally equivalent. Computational approaches that can confidently recommend PTMs of probable function can improve the heuristics of PTM investigation and alleviate these problems. To address this need, we developed SAPH-ire: a multifeature heuristic neural network model that takes community wisdom into account by recommending experimental PTMs similar to those which have previously been established as having regulatory impact. Here, we describe the principle behind the SAPH-ire model, how it is developed, how we evaluate its performance, and important caveats to consider when building and interpreting such models. Finally, we discus current limitations of functional PTM prediction models and highlight potential mechanisms for their improvement.

Emerging evidence suggests that heterotrimeric G protein gamma subunits (Gγ) are important governors of G protein signaling, a function that is mediated through GPCR- and pH-dependent combinatorial phosphorylation of their intrinsically disordered N-terminal tails (Gγ-Nt) that controls Gβγ/effector interactions and signaling. Intrinsic disorder is a universally conserved structural feature of all Gγ subunit N-termini, which prompted us to hypothesize that, beyond phosphorylation, intrinsic disorder itself is inherently important to the signal-governing roles of Gγ subunits. To test this hypothesis we devised a strategy in which single amino acid substitutions are sequentially introduced into the Gγ tail, producing a series of isoforms that proceed step-wise from a fully-disordered to fully-ordered (α-helical) Nt tail structure. As a control for the increasing mutation load, we compare these mutants to those in which the same number of amino acid substitutions are incorporated that do not alter the inherent structural disorder of the tail. These mutant isoforms were then structurally analyzed by circular dichroism (CD) in vitro, by molecular dynamics (MD) simulation in silico, and by functional analysis of Gβγ-dependent molecular signaling in vivo. Here, we apply this approach to the yeast Gγ subunit, Ste18. CD and MD analyses of Ste18-Nt tail isoforms indicate that a successful transition from a fully-disordered to fully-ordered state is achievable through precise point mutation. Replacing the wild type Gγ subunit with each of the mutant isoforms in yeast, we further show that intrinsic disorder of Gγ-Nt controls the stability of the Gγ subunit in a manner that is proportional to the loss of intrinsic disorder in vivo. pH-dependent phosphorylation at Ser3 in the tail is largely unaffected by these changes. However, unexpectedly, we found that the GPCR-dependent phosphorylation site, Ser7, becomes pH-sensitive in response to changes in tail structure. Ongoing experiments reveal the effects of Ste18-Nt tail structure on the interaction of yeast Gbg with its primary effector Ste5, and subsequent effects on activation of MAPKs, which have been shown to be highly sensitive to Gγ-Nt tail phosphorylation previously. Taken together, these data provide evidence that intrinsic structural disorder plays a direct role in functionality of Gγ subunits as governors of G proteins signaling and substantiates the rationale for exploring similar roles for these tails in mammalian Gβγ-dependent signaling pathways.

The extracellular matrix (ECM) is a protein polymer network that physically supports cells within a tissue and also acts as an important biochemical stimulus directing cell behaviors. For fibronectin, a predominant component of the ECM, these physical and biochemical activities are inextricably linked as physical forces trigger conformational changes that impact its biochemical activity. We analyzed whether oxidative post-translational modifications, specifically glutathionylation, enable fibronectin to ‘record’ physical information through stretch-dependent protein modification. Posttranslational modifications of the ECM are understudied, but represent opportunities for time- or stimuli-dependent changes in structure-function relationships that both persist over time and could have dominant impacts on cell-ECM homeostasis. We provide direct evidence that stretch-dependent glutathionylation of fibronectin irreversibly and significantly alters its mechanical properties with concomitant changes in the binding of integrin receptors and downstream cell signaling events. Stretch-dependent glutathionylation of fibronectin could have significant impact on the balance between tissue homeostasis and pathological progression, particularly in tissues and organs that are exposed to high oxidative stress, such as the lung.

Protein intrinsically disordered regions (IDRs) are often targets of combinatorial post-translational modifications (PTMs) that serve to regulate protein structure and/or function. Emerging evidence suggests that the N-terminal tails of G protein γ subunits – essential components of heterotrimeric G protein complexes – are intrinsically disordered, highly phosphorylated governors of G protein signaling. Here, we demonstrate that the yeast Gγ Ste18 undergoes combinatorial, multi-site phosphorylation within its N-terminal IDR. Phosphorylation at S7 is responsive to GPCR activation and osmotic stress while phosphorylation at S3 is responsive to glucose stress and is a quantitative indicator of intracellular pH. Each site is phosphorylated by a distinct set of kinases and both are also interactive, such that phosphomimicry at one site affects phosphorylation on the other. Lastly, we show that phosphorylation produces subtle yet clear changes in IDR structure and that different combinations of phosphorylation modulate the activation rate and amplitude of the scaffolded MAPK Fus3. These data place Gγ subunits among the growing list of intrinsically disordered proteins that exploit combinatorial post-translational modification to govern signaling pathway output.

Intracellular heterotrimeric G proteins (consisting of Gα, Gβ, and Gγ subunits), interface with 7‐transmembrane G protein coupled receptors (GPCRs) and function as the primary transducers of extracellular signals such as hormones, neurotransmitters, as well as pharmaceutical compounds. Upon binding their cognate ligands, GPCRs promote the dissociation of Gα and Gβγ subunits, which are then free to interact with effector proteins that promote intracellular signaling responses to the stimulus. Within this context, Gγ subunits are thought of primarily as membrane anchors for Gβ subunits, which must reside at the plasma membrane to facilitate functional protein interactions. However, emerging evidence suggests that Gγ subunits serve as phosphorylation‐dependent governors of G protein signaling. We have recently demonstrated this in the budding yeast model system, in which negative feedback phosphorylation of the intrinsically disordered N‐terminal tail of Gγ/Ste18 disrupts Gβγ/effector interactions and inhibits the normal GPCR‐dependent activation of MAPKs (Choudhury S. et al, Cell Rep. 2018). More recently, we have discovered that the yeast Gγ subunit undergoes combinatorial phosphorylation in response to several different forms of extracellular stimuli, including osmotic stress, pH stress, glucose deprivation, and cell cycle progression, in addition to GPCR activation. In light of these discoveries, we have hypothesized that Gγ phosphorylation plays a similar role in mammalian GPCR pathways. Indeed, we show that, like Gγ/Ste18, all mammalian Gγ subunits have an intrinsically disordered N‐terminus and most also undergo multi‐site phosphorylation. Here we provide new evidence to evaluate the hypothesis that Gγ phosphorylation is a governor of G protein signaling in mammals by demonstrating that phosphorylation is readily detectable on many different human Gγ subunits (Gγ3, 4, 5, 7, 10, 12) and by systematically testing the requirement for phosphorylation in proper Gβγ‐specific signaling pathways including the activation of PKD1 kinase by phospholipase C β2/3.Support or Funding InformationNIH

ABSTRACTProtein post-translational modifications (PTMs) are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof, the number of functional PTMs in the eukaryotic proteome is currently underestimated. Furthermore, not all PTMs are functionally equivalent. Therefore, computational approaches that can confidently recommend the functional potential of experimental PTMs are essential. To address this challenge, we developed SAPH-ire TFx (https://saphire.biosci.gatech.edu/): a multi-feature neural network model and web resource optimized for recommending experimental PTMs with high potential for biological impact. The model is rigorously benchmarked against independent datasets and alternative models, exhibiting unmatched performance in the recall of known functional PTM sites and the recommendation of PTMs that were later confirmed experimentally. An analysis of feature contributions to model outcome provides further insight on the need for multiple rather than single features to capture the breadth of functional data in the public domain.Contactmtorres35@gatech.eduSupplementary InformationSee Tables S1-S6 & Figures S1-S4.

Post‐translational Modifications (PTMs), chemical or proteinaceous covalent alterations to the side chains of amino acid residues in proteins, are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof and the lack of effective means for experimentalists to prioritize PTMs by functional significance, currently less than ~2% of all PTMs have an assigned biological function. Here, we describe a new artificial neural network model, SAPH‐ire TFx for the functional prediction of experimentally observed eukaryotic PTMs. Unlike previous functional PTM prioritization models, SAPH‐ire TFx is trained to emphasize metrics that maximally capture the range of diverse feature sets comprising the functional modified eukaryotic proteome. The model of was generated through systematic evaluation of input features, model architectures, training procedures, and interpretation metrics using a 2018 training dataset of 430,750 PTMs containing 7,480 PTMs with literature‐supported evidence of biological function. The resulting model was used to classify an expanded 2019 dataset of 512,015 PTMs (12,867 known functional) containing 102,475 PTMs unencountered in the original dataset. Model output from the 2019 extended dataset was benchmarked against pre‐existing prediction models, revealing superior performance in classification of functional and/or disease‐linked PTM sites, including drawing attention to PTMs that were previously thought inconsequential. Finally, a dynamic web interface provides customizable graphical and tabular visualization of PTM and SAPH‐ire TFx data within the context of all modifications within a protein family, exposing several metrics by which important functional PTMs can be identified for investigation.