The mechanisms regulating the transcription factor ATF5 and its function in the integrated stress response

Indiana University-Purdue University Indianapolis (IUPUI)Phosphorylation of eukaryotic initiation factor 2 (eIF2) is an important mechanism regulating global and gene-specific translation during different environmental stresses. Repressed global translation by eIF2 phosphorylation allows for cells to conserve resources and elicit a program of gene expression to alleviate stress-induced injury. Central to this gene expression program is eIF2 phosphorylation induction of preferential translation of ATF4. ATF4 is a transcriptional activator of genes involved in stress remediation, a pathway referred to as the Integrated Stress Response (ISR). We investigated whether there are additional transcription factors whose translational expression is regulated by eIF2 kinases. We found that the expression of the transcriptional regulator ATF5 is enhanced in response to many different stresses, including endoplasmic reticulum stress, arsenite exposure, and proteasome inhibition, by a mechanism requiring eIF2 phosphorylation. ATF5 is regulated by translational control as illustrated by the preferential association of ATF5 mRNA with large polyribosomes in response to stress. ATF5 translational control involves two upstream open reading frames (uORFs) located in the 5′-leader of the ATF5 mRNA, a feature shared with ATF4. Mutational analyses of the 5′-leader of ATF5 mRNA fused to a luciferase reporter suggests that the 5′-proximal uORF1 is positive-acting, allowing scanning ribosomes to reinitiate translation of a downstream ORF. During non-stressed conditions, when eIF2 phosphorylation is low, ribosomes reinitiate translation at the next ORF, the inhibitory uORF2. Phosphorylation of eIF2 during stress delays translation reinitiation, allowing scanning ribosomes to bypass uORF2, and instead translate the ATF5 coding region. In addition to translational control, ATF5 mRNA and protein levels are significantly reduced in mouse embryo fibroblasts deleted for ATF4, or its target gene, the transcriptional factor CHOP. This suggests that ISR transcriptional mechanisms also contribute to ATF5 expression. To address the function of ATF5 in the ISR, we employed a shRNA knock-down strategy and our analysis suggests that ATF5 promotes apoptosis under stress conditions via caspase-dependent mechanisms. Given the well-characterized role of CHOP in the promotion of apoptosis, this study suggests that there is an ATF4-CHOP-ATF5 signaling axis in the ISR that can determine cell survival during different environmental stresses

Layer-refined Graph Convolutional Networks for Recommendation

Recommendation models utilizing Graph Convolutional Networks (GCNs) have achieved state-of-the-art performance, as they can integrate both the node information and the topological structure of the user-item interaction graph. However, these GCN-based recommendation models not only suffer from over-smoothing when stacking too many layers but also bear performance degeneration resulting from the existence of noise in user-item interactions. In this paper, we first identify a recommendation dilemma of over-smoothing and solution collapsing in current GCN-based models. Specifically, these models usually aggregate all layer embeddings for node updating and achieve their best recommendation performance within a few layers because of over-smoothing. Conversely, if we place learnable weights on layer embeddings for node updating, the weight space will always collapse to a fixed point, at which the weighting of the ego layer almost holds all. We propose a layer-refined GCN model, dubbed LayerGCN, that refines layer representations during information propagation and node updating of GCN. Moreover, previous GCN-based recommendation models aggregate all incoming information from neighbors without distinguishing the noise nodes, which deteriorates the recommendation performance. Our model further prunes the edges of the user-item interaction graph following a degree-sensitive probability instead of the uniform distribution. Experimental results show that the proposed model outperforms the state-of-the-art models significantly on four public datasets with fast training convergence. The implementation code of the proposed method is available at https://github.com/enoche/ImRec.Comment: 12 pages, 5 figure

An Improved Focused Crawler: Using Web Page Classification and Link Priority Evaluation

A focused crawler is topic-specific and aims selectively to collect web pages that are relevant to a given topic from the Internet. However, the performance of the current focused crawling can easily suffer the impact of the environments of web pages and multiple topic web pages. In the crawling process, a highly relevant region may be ignored owing to the low overall relevance of that page, and anchor text or link-context may misguide crawlers. In order to solve these problems, this paper proposes a new focused crawler. First, we build a web page classifier based on improved term weighting approach (ITFIDF), in order to gain highly relevant web pages. In addition, this paper introduces an evaluation approach of the link, link priority evaluation (LPE), which combines web page content block partition algorithm and the strategy of joint feature evaluation (JFE), to better judge the relevance between URLs on the web page and the given topic. The experimental results demonstrate that the classifier using ITFIDF outperforms TFIDF, and our focused crawler is superior to other focused crawlers based on breadth-first, best-first, anchor text only, link-context only, and content block partition in terms of harvest rate and target recall. In conclusion, our methods are significant and effective for focused crawler

A new class of orthosteric uPAR·uPA small-molecule antagonists are allosteric inhibitors of the uPAR·vitronectin interaction

The urokinase receptor (uPAR) is a GPI-anchored cell surface receptor that is at the center of an intricate network of protein-protein interactions. Its immediate binding partners are the serine proteinase urokinase (uPA), and vitronectin (VTN), a component of the extracellular matrix. uPA and VTN bind at distinct sites on uPAR to promote extracellular matrix degradation and integrin signaling, respectively. Here, we report the discovery of a new class of pyrrolone small-molecule inhibitors of the tight ∼1 nM uPAR·uPA protein-protein interaction. These compounds were designed to bind to the uPA pocket on uPAR. The highest affinity compound, namely 7, displaced a fluorescently labeled α-helical peptide (AE147-FAM) with an inhibition constant Ki of 0.7 μM and inhibited the tight uPAR·uPAATF interaction with an IC50 of 18 μM. Biophysical studies with surface plasmon resonance showed that VTN binding is highly dependent on uPA. This cooperative binding was confirmed as 7, which binds at the uPAR·uPA interface, also inhibited the distal VTN·uPAR interaction. In cell culture, 7 blocked the uPAR·uPA interaction in uPAR-expressing human embryonic kidney (HEK-293) cells and impaired cell adhesion to VTN, a process that is mediated by integrins. As a result, 7 inhibited integrin signaling in MDA-MB-231 cancer cells as evidenced by a decrease in focal adhesion kinase (FAK) phosphorylation and Rac1 GTPase activation. Consistent with these results, 7 blocked breast MDA-MB-231 cancer cell invasion with IC50 values similar to those observed in ELISA and surface plasmon resonance competition studies. Explicit-solvent molecular dynamics simulations show that the cooperativity between uPA and VTN is attributed to stabilization of uPAR motion by uPA. In addition, free energy calculations revealed that uPA stabilizes the VTNSMB·uPAR interaction through more favorable electrostatics and entropy. Disruption of the uPAR·VTNSMB interaction by 7 is consistent with the cooperative binding to uPAR by uPA and VTN. Interestingly, the VTNSMB·uPAR interaction was less favorable in the VTNSMB·uPAR·7 complex suggesting potential cooperativity between 7 and VTN. Compound 7 provides an excellent starting point for the development of more potent derivatives to explore uPAR biology

Mimicking Intermolecular Interactions of Tight Protein–Protein Complexes for Small-Molecule Antagonists

Tight protein–protein interactions (Kd1000 Å2) are highly challenging to disrupt with small molecules. Historically, the design of small molecules to inhibit protein–protein interactions has focused on mimicking the position of interface protein ligand side chains. Here, we explore mimicry of the pairwise intermolecular interactions of the native protein ligand with residues of the protein receptor to enrich commercial libraries for small-molecule inhibitors of tight protein–protein interactions. We use the high-affinity interaction (Kd=1 nm) between the urokinase receptor (uPAR) and its ligand urokinase (uPA) to test our methods. We introduce three methods for rank-ordering small molecules docked to uPAR: 1) a new fingerprint approach that represents uPA′s pairwise interaction energies with uPAR residues; 2) a pharmacophore approach to identify small molecules that mimic the position of uPA interface residues; and 3) a combined fingerprint and pharmacophore approach. Our work led to small molecules with novel chemotypes that inhibited a tight uPAR⋅uPA protein–protein interaction with single-digit micromolar IC50 values. We also report the extensive work that identified several of the hits as either lacking stability, thiol reactive, or redox active. This work suggests that mimicking the binding profile of the native ligand and the position of interface residues can be an effective strategy to enrich commercial libraries for small-molecule inhibitors of tight protein–protein interactions

Structure-Based Target-Specific Screening Leads to Small-Molecule CaMKII Inhibitors

Target-specific scoring methods are more commonly used to identify small-molecule inhibitors among compounds docked to a target of interest. Top candidates that emerge from these methods have rarely been tested for activity and specificity across a family of proteins. In this study we docked a chemical library into CaMKIIδ, a member of the Ca2+ /calmodulin (CaM)-dependent protein kinase (CaMK) family, and re-scored the resulting protein-compound structures using Support Vector Machine SPecific (SVMSP), a target-specific method that we developed previously. Among the 35 selected candidates, three hits were identified, such as quinazoline compound 1 (KIN-1; N4-[7-chloro-2-[(E)-styryl]quinazolin-4-yl]-N1,N1-diethylpentane-1,4-diamine), which was found to inhibit CaMKIIδ kinase activity at single-digit micromolar IC50 . Activity across the kinome was assessed by profiling analogues of 1, namely 6 (KIN-236; N4-[7-chloro-2-[(E)-2-(2-chloro-4,5-dimethoxyphenyl)vinyl]quinazolin-4-yl]-N1,N1-diethylpentane-1,4-diamine), and an analogue of hit compound 2 (KIN-15; 2-[4-[(E)-[(5-bromobenzofuran-2-carbonyl)hydrazono]methyl]-2-chloro-6-methoxyphenoxy]acetic acid), namely 14 (KIN-332; N-[(E)-[4-(2-anilino-2-oxoethoxy)-3-chlorophenyl]methyleneamino]benzofuran-2-carboxamide), against 337 kinases. Interestingly, for compound 6, CaMKIIδ and homologue CaMKIIγ were among the top ten targets. Among the top 25 targets of 6, IC50 values ranged from 5 to 22 μm. Compound 14 was found to be not specific toward CaMKII kinases, but it does inhibit two kinases with sub-micromolar IC50 values among the top 25. Derivatives of 1 were tested against several kinases including several members of the CaMK family. These data afforded a limited structure-activity relationship study. Molecular dynamics simulations with explicit solvent followed by end-point MM-GBSA free-energy calculations revealed strong engagement of specific residues within the ATP binding pocket, and also changes in the dynamics as a result of binding. This work suggests that target-specific scoring approaches such as SVMSP may hold promise for the identification of small-molecule kinase inhibitors that exhibit some level of specificity toward the target of interest across a large number of proteins

Numerical Study of the Movement of Fine Particle in Sound Wave Field

AbstractInhalable particulate matter, especially PM2.5 is one of the main pollutants in China and it's harmful to both human health and atmosphere. Since the removal efficiency of traditional dust removal devices such as ESP for PM2.5 is very low, pretreatment becomes necessary before the dust gets into the dust remover. Acoustic agglomeration is one of the pretreatment technologies which uses sound wave with high intensity to make fine particles get agglomerate and grow up, and improves the efficiency of traditional dust removal devices for PM2.5. In sound wave field, fine particles are carried by the medium which in this paper is air, and vibrate with different amplitude because of different particle sizes, thus relative movement appears and then particles have more chances to collide and get agglomerate. In this paper, the movement of particles with different sizes in travelling wave sound field and standing wave sound field were calculated, including the velocity, displacement, amplitude and so on. The situation that Re<1 was considered and Viscous force in Stokes region was chose as the main forces here. Studying the movement of fine particle in sound field with different conditions has great meaning in learning the mechanisms of acoustic agglomeration

Small-molecule CaVα1⋅CaVβ antagonist suppresses neuronal voltage-gated calcium-channel trafficking

Extracellular calcium flow through neuronal voltage-gated CaV2.2 calcium channels converts action potential-encoded information to the release of pronociceptive neurotransmitters in the dorsal horn of the spinal cord, culminating in excitation of the postsynaptic central nociceptive neurons. The CaV2.2 channel is composed of a pore-forming α1 subunit (CaVα1) that is engaged in protein-protein interactions with auxiliary α2/δ and β subunits. The high-affinity CaV2.2α1⋅CaVβ3 protein-protein interaction is essential for proper trafficking of CaV2.2 channels to the plasma membrane. Here, structure-based computational screening led to small molecules that disrupt the CaV2.2α1⋅CaVβ3 protein-protein interaction. The binding mode of these compounds reveals that three substituents closely mimic the side chains of hot-spot residues located on the α-helix of CaV2.2α1 Site-directed mutagenesis confirmed the critical nature of a salt-bridge interaction between the compounds and CaVβ3 Arg-307. In cells, compounds decreased trafficking of CaV2.2 channels to the plasma membrane and modulated the functions of the channel. In a rodent neuropathic pain model, the compounds suppressed pain responses. Small-molecule α-helical mimetics targeting ion channel protein-protein interactions may represent a strategy for developing nonopioid analgesia and for treatment of other neurological disorders associated with calcium-channel trafficking