Impact of Asp/Glu-ADP-ribosylation on protein-protein interaction and protein function.

PARylation plays critical role in regulating multiple cellular processes such as DNA damage response and repair, transcription, RNA processing, and stress response. More than 300 human proteins have been found to be modified by PARylation on acidic residues, that is, Asp (D) and Glu (E). We used the deep-learning tool AlphaFold to predict protein-protein interactions (PPIs) and their interfaces for these proteins based on coevolution signals from joint multiple sequence alignments (MSAs). AlphaFold predicted 260 confident PPIs involving PARylated proteins, and about one quarter of these PPIs have D/E-PARylation sites in their predicted PPI interfaces. AlphaFold predictions offer novel insights into the mechanisms of PARylation regulations by providing structural details of the PPI interfaces. D/E-PARylation sites have a preference to occur in coil regions and disordered regions, and PPI interfaces containing D/E-PARylation sites tend to occur between short linear sequence motifs in disordered regions and globular domains. The hub protein PCNA is predicted to interact with more than 20 proteins via the common PIP box motif and the structurally variable flanking regions. D/E-PARylation sites were found in the interfaces of key components of the RNA transcription and export complex, the SF3a spliceosome complex, and H/ACA and C/D small nucleolar ribonucleoprotein complexes, suggesting that systematic PARylation have a profound effect in regulating multiple RNA-related processes such as RNA nuclear export, splicing, and modification. Finally, PARylation of SUMO2 could modulate its interaction with CHAF1A, thereby representing a potential mechanism for the cross-talk between PARylation and SUMOylation in regulation of chromatin remodeling.

PARP1 inhibitors induce pyroptosis via caspase 3-mediated gasdermin E cleavage.

The identification of PARP1 as a therapeutic target for BRCA1/2-deficient cells has led to a paradigm shift for the treatment of human malignancies with BRCA1/2 mutations. However, our understanding of the mechanism of action of PARP1 inhibitors (PARPi) is still evolving. It is being increasingly appreciated that the immunomodulatory function of PARPi is a critical contributor of the anti-tumor effects of these compounds. Here, we identify a novel cell death effector pathway for PARPi where PARPi induces inflammatory pyroptosis that is mediated by caspase 3-dependent cleavage of GSDME. Caspase 3 is activated upon PARPi treatment which directly cleaves GSDME and, subsequently induces pyroptosis. Genetic and pharmacological experiments show that the presence of the PARP1 protein with uncompromised DNA binding capability is required for PARPi-induced pyroptosis, suggesting that PARP1 trapping is a key driver of this phenomenon. Importantly, we show that PARPi-induced GSDME cleavage and pyroptosis occurred only in the BRCA1-deficient cells, but not in those reconstituted with BRCA1 wild-type (WT). These findings suggest that pyroptosis could be a novel aspect of the immunomodulatory function of PARPi. Our studies could also offer new insights to the potential biomarkers and therapeutic strategies to achieve better anti-tumor effects of PARPi for BRCA-deficient tumors with low GSDME expression.

Cholesterol Regulates the Tumor Adaptive Resistance to MAPK Pathway Inhibition.

Although targeted MAPK pathway inhibition has achieved remarkable patient responses in many cancers, the development of resistance has remained a critical challenge. Adaptive tumor response underlies the drug resistance. Furthermore, such bypass mechanisms often lead to the activation of many pro-survival kinases, which complicates the rational design of combination therapies. Here, we performed global tyrosine phosphoproteomic (pTyr) analyses and demonstrated that targeted MAPK signaling inhibition in melanoma leads to a profound remodeling of the pTyr proteome. Intriguingly, altered cholesterol metabolism might drive, in a coordinated fashion, the activation of these kinases. Indeed, we found an accumulation of intracellular cholesterol in melanoma cells (with BRAFV600E mutations) and non-small cell lung cancer cells (with KRASG12C mutations) treated with MAPK and KRASG12C inhibitors, respectively. Importantly, depletion of cholesterol not only prevents the feedback activation of pTyr signaling but also enhances the cytotoxic effects of MAPK pathway inhibitors, both in vitro and in vivo. Together, our findings suggest that cholesterol contributes to the tumor adaptive response upon targeted MAPK pathway inhibitors. These results also suggest that MAPK pathway inhibitors could be combined with cholesterol-lowering agents to achieve a more complete and durable response in tumors with hyperactive MAPK signaling.

Novel high voltage polymer insulators using computational and data-driven techniques.

One of the key bottlenecks in the development of high voltage electrical systems is the identification of suitable insulating materials capable of supporting high voltages. Under high voltage scenarios, conventional polymer based insulators, which are one of the popular choices of insulators, suffer from the drawback of space charge accumulation, which leads to degradation in desirable electronic properties and facilitates dielectric breakdown. In this work, we aid the development of novel polymers for high voltage insulation applications by enabling the rapid prediction of properties that are correlated with dielectric breakdown, i.e.,the bandgap (Egap) of the polymer and electron injection barrier (Φe) at the electrode-insulator interface. To accomplish this, density functional theory based methods are used to develop large, chemically diverse datasets of Φe and Egap. The deviation of the computed properties from experimental observations is addressed using a statistical technique called Bayesian calibration. Furthermore, to enable rapid estimation of these properties for a large set of polymers, machine learning models are developed using the created dataset. These models are further used to predict Egap and Φe for a set of 13k previously known polymers. Polymers with high values of these properties are selected as potential high voltage insulators and are recommended for synthesis. Finally, the models developed here are deployed at www.polymergenome.org to enable the community use.

Critical Assessment of the Hildebrand and Hansen Solubility Parameters for Polymers.

Solubility parameter models are widely used to select suitable solvents/nonsolvents for polymers in a variety of processing and engineering applications. In this study, we focus on two well-established models, namely, the Hildebrand and Hansen solubility parameter models. Both models are built on the basis of the notion of "like dissolves like" and identify a liquid as a good solvent for a polymer if the solubility parameters of the liquid and the polymer are close to each other. Here we make a critical and quantitative assessment of the accuracy/utility of these two models by comparing their predictions against actual experimental data. Using a data set of 75 polymers, we find that the Hildebrand model displays a predictive accuracy of 60% for solvents and 76% for nonsolvents. The Hansen model leads to a similar performance; on the basis of a data set of 25 polymers for which Hansen parameters are available, we find that it has an accuracy of 67% for solvents and 76% for nonsolvents. The availability of the Hildebrand parameters for a large polymer data set makes it a widely applicable capability, as the Hildebrand parameter for a new polymer may be determined using this data set and machine learning methods as we have done before; the predicted Hildebrand parameter for a new polymer may then be used to determine suitable solvents and nonsolvents. Such predictions are difficult to make with the Hansen model, as the data set of Hansen parameters for polymers is rather small. Nevertheless, the Hildebrand approach must be used with caution. Our analysis shows that while the Hildebrand model has a predictive accuracy of 70-75% for nonpolar polymers, it performs rather poorly for polar polymers (with an accuracy of 57%). Going forward, determination of solvents and nonsolvents for polymers may benefit by developing classification models built directly on the basis of available experimental data sets rather than utilizing the solubility parameter approach, which is limited in versatility and accuracy.

Ullmann Reaction Catalyzed by Heterogeneous Mesoporous Copper/Manganese Oxide: A Kinetic and Mechanistic Analysis.

A heterogeneous copper oxide supported on mesoporous manganese oxide (meso Cu/MnOx) was explored for Ullmann-type cross-coupling reactions. An inverse micelle-templated evaporation-induced self-assembly method with in situ addition of copper was adopted to synthesize the mesoporous catalyst. Broad substrate scope and excellent functional group tolerability in C-O, C-N, and C-S bond formation reactions were observed using the optimized reaction conditions. The catalytic protocol was ligand free, and the catalyst was reusable without any significant loss of activity. The kinetic and Hammett analyses provided evidence for oxidative addition to a Cu(I) reaction center followed by nucleophilic addition and reductive elimination at the active copper oxide surface. Rate acceleration was observed for aryl halides with electron-withdrawing groups. The Hammett analysis determined ρ = +1.0, indicative of an oxidative addition, whereas the electronic effect in the phenol ring (ρ = -2.9) was indicative of coordination to a metal ion. Theoretically, the oxidative addition of the aryl halides is assisted by the ligand environment of the copper center. Relevant mechanistic implications are discussed on the basis of the experimental and computational results.

Anamorsin, a novel caspase-3 substrate in neurodegeneration.

Activated caspases play a central role in the execution of apoptosis by cleaving endogenous substrates. Here, we developed a high throughput screening method to identify novel substrates for caspase-3 in a neuronal cell line. Critical steps in our strategy consist of two-dimensional electrophoresis-based protein separation and in vitro caspase-3 incubation of immobilized proteins to sort out direct substrates. Among 46 putative substrates identified in MN9D neuronal cells, we further evaluated whether caspase-3-mediated cleavage of anamorsin, a recently recognized cell death-defying factor in hematopoiesis, is a general feature of apoptosis. In vitro and cell-based cleavage assays indicated that anamorsin was specifically cleaved by caspase-3 but not by other caspases, generating 25- and 10-kDa fragments. Thus, in apoptosis of neuronal and non-neuronal cells induced by various stimuli including staurosporine, etoposide, or 6-hydroxydopamine, the cleavage of anamorsin was found to be blocked in the presence of caspase inhibitor. Among four tetrapeptide consensus DXXD motifs existing in anamorsin, we mapped a specific cleavage site for caspase-3 at DSVD(209)↓L. Intriguingly, the 25-kDa cleaved fragment of anamorsin was also detected in post-mortem brains of Alzheimer and Parkinson disease patients. Although the RNA interference-mediated knockdown of anamorsin rendered neuronal cells more vulnerable to staurosporine treatment, reintroduction of full-length anamorsin into an anamorsin knock-out stromal cell line made cells resistant to staurosporine-induced caspase activation, indicating the antiapoptotic function of anamorsin. Taken together, our approach seems to be effective to identify novel substrates for caspases and has the potential to provide meaningful insights into newly identified substrates involved in neurodegenerative processes.

Gel-based protease proteomics for identifying the novel calpain substrates in dopaminergic neuronal cell.

Calpains are a family of calcium-dependent cysteine proteases that are ubiquitously expressed in mammals and play critical roles in neuronal death by catalyzing substrate proteolysis. Here, we developed two-dimensional gel electrophoresis-based protease proteomics to identify putative calpain substrates. To accomplish this, cellular lysates from neuronal cells were first separated by pI, and the immobilized sample on a gel strip was incubated with a recombinant calpain and separated by molecular weight. Among 25 altered protein spots that were differentially expressed by at least 2-fold, we confirmed that arsenical pump-driving ATPase, optineurin, and peripherin were cleaved by calpain using in vitro and in vivo cleavage assays. Furthermore, we found that all of these substrates were cleaved in MN9D cells treated with either ionomycin or 1-methyl-4-phenylpyridinium, both of which cause a calcium-mediated calpain activation. Their cleavage was blocked by calcium chelator or calpain inhibitors. In addition, calpain-mediated cleavage of these substrates and its inhibition by calpeptin were confirmed in a middle cerebral artery occlusion model of cerebral ischemia, as well as a stereotaxic brain injection model of Parkinson disease. Transient overexpression of each protein was shown to attenuate 1-methyl-4-phenylpyridinium-induced cell death, indicating that these substrates may confer protection of varying magnitudes against dopaminergic injury. Taken together, the data indicate that our protease proteomic method has the potential to be applicable for identifying proteolytic substrates affected by diverse proteases. Moreover, the results described here will help us decipher the molecular mechanisms underlying the progression of neurodegenerative disorders where protease activation is critically involved.

Acetylation of cyclin-dependent kinase 5 is mediated by GCN5.

Cyclin-dependent kinase 5 (CDK5), a member of atypical serine/threonine cyclin-dependent kinase family, plays a crucial role in pathophysiology of neurodegenerative disorders. Its kinase activity and substrate specificity are regulated by several independent pathways including binding with its activator, phosphorylation and S-nitrosylation. In the present study, we report that acetylation of CDK5 comprises an additional posttranslational modification within the cells. Among many candidates, we confirmed that its acetylation is enhanced by GCN5, a member of the GCN5-related N-acetyl-transferase family of histone acetyltransferase. Co-immunoprecipitation assay and fluorescent localization study indicated that GCN5 physically interacts with CDK5 and they are co-localized at the specific nuclear foci. Furthermore, liquid chromatography in conjunction with a mass spectrometry indicated that CDK5 is acetylated at Lys33 residue of ATP binding domain. Considering this lysine site is conserved among a wide range of species and other related cyclin-dependent kinases, therefore, we speculate that acetylation may alter the kinase activity of CDK5 via affecting efficacy of ATP coordination.

Synthesis of nimbolide and its analogues and their application as poly(ADP-ribose) polymerase-1 trapping inducers.

Nimbolide, a ring seco-C limonoid natural product, was recently found to inhibit the poly(ADP)-ribosylation (PARylation)-dependent ubiquitin E3 ligase RNF114. In doing so, it induces the 'supertrapping' of both PARylated PARP1 and PAR-dependent DNA-repair factors. PARP1 inhibitors have reshaped the treatment of cancer patients with germline BRCA1/2 mutations partly through the PARP1 trapping mechanism. To this end, modular access to nimbolide analogues represents an opportunity to develop cancer therapeutics with enhanced PARP1 trapping capability. Here we report a convergent synthesis of nimbolide through a late-stage coupling strategy. Through a sulfonyl hydrazone-mediated etherification and a radical cyclization, this strategy uses a pharmacophore-containing building block and diversifiable hydrazone units to enable the modular synthesis of nimbolide and its analogues. The broad generality of our synthetic strategy allowed access to a variety of analogues with their preliminary cellular cytotoxicity and PARP1 trapping activity reported.

Synergistic Effects in LaNiO3 Perovskites between Nickel and Iron Heterostructures for Improving Durability in Oxygen Evolution Reaction for AEMWE.

Perovskite materials that aren't stable during the oxygen evolution reaction (OER) are unsuitable for anion-exchange membrane water electrolyzers (AEMWE). But through manipulating their electronic structures, their performance can further increase. Among the first-row transition metals, nickel and iron are widely recognized as prominent electrocatalysts; thus, the researchers are looking into how combining them can improve the OER. Recent research has actively explored the design and study of heterostructures in this field, showcasing the dynamic exploration of innovative catalyst configurations. In this study, a heterostructure is used to manipulate the electronic structure of LaNiO3 (LNO) to improve both OER properties and durability. Through adsorbing iron onto the LNO (LNO@Fe) as γ iron oxyhydroxide (γ-FeOOH), the binding energy of nickel in the LNO exhibited negative shifts, inferring nickel movement toward the metallic state. Consequently, the electrochemical properties of LNO@Fe are further improved. LNO@Fe showed excellent performance (1.98 A cm-2, 1 m KOH, 50 °C at 1.85 V) with 84.1% cell efficiency in AEMWE single cells, demonstrating great improvement relative to LNO. The degradation for the 850 h durability analysis of LNO@Fe is ≈68 mV kh-1, which is ≈58 times less than that of LNO.

Induced degradation of lineage-specific oncoproteins drives the therapeutic vulnerability of small cell lung cancer to PARP inhibitors.

Although BRCA1/2 mutations are not commonly found in small cell lung cancer (SCLC), a substantial fraction of SCLC shows clinically relevant response to PARP inhibitors (PARPis). However, the underlying mechanism(s) of PARPi sensitivity in SCLC is poorly understood. We performed quantitative proteomic analyses and identified proteomic changes that signify PARPi responses in SCLC cells. We found that the vulnerability of SCLC to PARPi could be explained by the degradation of lineage-specific oncoproteins (e.g., ASCL1). PARPi-induced activation of the E3 ligase HUWE1 mediated the ubiquitin-proteasome system (UPS)-dependent ASCL1 degradation. Although PARPi induced a general DNA damage response in SCLC cells, this signal generated a cell-specific response in ASCL1 degradation, leading to the identification of HUWE1 expression as a predictive biomarker for PARPi. Combining PARPi with agents targeting these pathways markedly improved therapeutic response in SCLC. The degradation of lineage-specific oncoproteins therefore represents a previously unidentified mechanism for PARPi efficacy in SCLC.

Solar-Powered AEM Electrolyzer via PGM-Free (Oxy)hydroxide Anode with Solar to Hydrogen Conversion Efficiency of 12.44.

Water electrolyzers powered by renewable energy are emerging as clean and sustainable technology for producing hydrogen without carbon emissions. Specifically, anion exchange membrane (AEM) electrolyzers utilizing non-platinum group metal (non-PGM) catalysts have garnered attention as a cost-effective method for hydrogen production, especially when integrated with solar cells. Nonetheless, the progress of such integrated systems is hindered by inadequate water electrolysis efficiency, primarily caused by poor oxygen evolution reaction (OER) electrodes. To address this issue, a NiFeCo─OOH has developed as an OER electrocatalyst and successfully demonstrated its efficacy in an AEM electrolyzer, which is powered by renewable electricity and integrated with a silicon solar cell.

Caspase-3-mediated cleavage of PICOT in apoptosis.

Mammalian protein kinase C-interacting cousin of thioredoxin (PICOT) is a multi-domain mono-thiol glutaredoxin that is involved in several signal transduction pathways and is necessary for cell growth and metastasis. Here, we demonstrate that PICOT is a cleavage substrate of the apoptosis-related protein caspase-3. In vitro cleavage assays indicated that PICOT was specifically cleaved by caspase-3. Similarly, endogenous PICOT was cleaved in cell death responses induced by staurosporine and etoposide. These phenomena were blocked in the presence of a pan-caspase inhibitor. Using site-directed mutagenesis, we identified two putative caspase-3 cleavage sequences in PICOT, DRLD(101)/G and EELD(226)/T. Interestingly, overexpression of either PICOT wild type or the D101A/D226A double point mutant accelerated etoposide-induced activation of caspase-3 whereas siRNA-mediated knockdown of PICOT blocked this phenomenon. Our data raise the possibility that the pro-apoptotic role of PICOT is actively regulated via caspase-3-mediated cleavage.

Nimbolide targets RNF114 to induce the trapping of PARP1 and synthetic lethality in BRCA-mutated cancer.

Recent studies have pointed to PARP1 trapping as a key determinant of the anticancer effects of PARP1 inhibitors (PARPi). We identified RNF114, as a PARylation-dependent, E3 ubiquitin ligase involved in DNA damage response. Upon sensing genotoxicity, RNF114 was recruited, in a PAR-dependent manner, to DNA lesions, where it targeted PARP1 for degradation. The blockade of this pathway interfered with the removal of PARP1 from DNA lesions, leading to profound PARP1 trapping. We showed that a natural product, nimbolide, inhibited the E3 ligase activity of RNF114 and thus caused PARP1 trapping. However, unlike conventional PARPi, nimbolide treatment induced the trapping of both PARP1 and PARylation-dependent DNA repair factors. Nimbolide showed synthetic lethality with BRCA mutations, and it overcame intrinsic and acquired resistance to PARPi, both in vitro and in vivo. These results point to the exciting possibility of targeting the RNF114-PARP1 pathway for the treatment of homologous recombination-deficient cancers.

Quantitative phosphoproteomic analyses identify STK11IP as a lysosome-specific substrate of mTORC1 that regulates lysosomal acidification.

The evolutionarily conserved serine/threonine kinase mTORC1 is a central regulator of cell growth and proliferation. mTORC1 is activated on the lysosome surface. However, once mTORC1 is activated, it is unclear whether mTORC1 phosphorylates local lysosomal proteins to regulate specific aspects of lysosomal biology. Through cross-reference analyses of the lysosome proteome with the mTORC1-regulated phosphoproteome, we identify STK11IP as a lysosome-specific substrate of mTORC1. mTORC1 phosphorylates STK11IP at Ser404. Knockout of STK11IP leads to a robust increase of autophagy flux. Dephosphorylation of STK11IP at Ser404 represses the role of STK11IP as an autophagy inhibitor. Mechanistically, STK11IP binds to V-ATPase, and regulates the activity of V-ATPase. Knockout of STK11IP protects mice from fasting or Methionine/Choline-Deficient Diet (MCD)-induced fatty liver. Thus, our study demonstrates that STK11IP phosphorylation represents a mechanism for mTORC1 to regulate lysosomal acidification and autophagy, and points to STK11IP as a promising therapeutic target for the amelioration of diseases with aberrant autophagy signaling.

Avoid the trap: Targeting PARP1 beyond human malignancy.

PARP1 is a poly(ADP-ribose) polymerase (PARP) enzyme that plays a critical role in regulating DNA damage response. The main enzymatic function of PARP1 is to catalyze a protein post-translational modification known as poly(ADP-ribosyl)ation (PARylation). Human cancers with homologous recombination deficiency are highly sensitive to PARP1 inhibitors. PARP1 is aberrantly activated in many non-oncological diseases, leading to the excessive NAD+ depletion and PAR formation, thus causing cell death and tissue damage. PARP1 deletion offers a profound protective effect in the relevant animal models. However, many of the current PARP1 inhibitors also induce PARP1 trapping, which drives subsequent DNA damage, innate immune response and cytotoxicity. This minireview provides an overview of the basic biology of PARP1 trapping, and its implications in disease. Furthermore, we also discuss the recent development of PARP1 PROTAC compounds, and their utility as "non-trapping" PARP1 degraders for the potential amelioration of non-oncological diseases driven by aberrant PARP1 activation.

Polymer informatics with multi-task learning.

Modern data-driven tools are transforming application-specific polymer development cycles. Surrogate models that can be trained to predict properties of polymers are becoming commonplace. Nevertheless, these models do not utilize the full breadth of the knowledge available in datasets, which are oftentimes sparse; inherent correlations between different property datasets are disregarded. Here, we demonstrate the potency of multi-task learning approaches that exploit such inherent correlations effectively. Data pertaining to 36 different properties of over 13,000 polymers are supplied to deep-learning multi-task architectures. Compared to conventional single-task learning models, the multi-task approach is accurate, efficient, scalable, and amenable to transfer learning as more data on the same or different properties become available. Moreover, these models are interpretable. Chemical rules, that explain how certain features control trends in property values, emerge from the present work, paving the way for the rational design of application specific polymers meeting desired property or performance objectives.

An Informatics Approach for Designing Conducting Polymers.

Doping conjugated polymers, which are potential candidates for the next generation of organic electronics, is an effective strategy for manipulating their electrical conductivity. However, selecting a suitable polymer-dopant combination is exceptionally challenging because of the vastness of the chemical, configurational, and morphological spaces one needs to search. In this work, high-performance surrogate models, trained on available experimentally measured data, are developed to predict the p-type electrical conductivity and are used to screen a large candidate hypothetical data set of more than 800 000 polymer-dopant combinations. Promising candidates are identified for synthesis and device fabrication. Additionally, new design guidelines are extracted that verify and extend knowledge on important molecular fragments that correlate to high conductivity. Conductivity prediction models are also deployed at www.polymergenome.org for broader open-access community use.