Proteomic Ligandability Maps of Spirocycle Acrylamide Stereoprobes Identify Covalent ERCC3 Degraders.

Covalent chemistry coupled with activity-based protein profiling (ABPP) offers a versatile way to discover ligands for proteins in native biological systems. Here, we describe a set of stereo- and regiochemically defined spirocycle acrylamides and the analysis of these electrophilic "stereoprobes" in human cancer cells by cysteine-directed ABPP. Despite showing attenuated reactivity compared to structurally related azetidine acrylamide stereoprobes, the spirocycle acrylamides preferentially liganded specific cysteines on diverse protein classes. One compound termed ZL-12A promoted the degradation of the TFIIH helicase ERCC3. Interestingly, ZL-12A reacts with the same cysteine (C342) in ERCC3 as the natural product triptolide, which did not lead to ERCC3 degradation but instead causes collateral loss of RNA polymerases. ZL-12A and triptolide cross-antagonized one another's protein degradation profiles. Finally, we provide evidence that the antihypertension drug spironolactone─previously found to promote ERCC3 degradation through an enigmatic mechanism─also reacts with ERCC3_C342. Our findings thus describe monofunctional degraders of ERCC3 and highlight how covalent ligands targeting the same cysteine can produce strikingly different functional outcomes.

Therapeutic vulnerabilities of cancer stem cells and effects of natural products.

Covering: 1995 to 2022Tumors possess both genetic and phenotypic heterogeneity leading to the survival of subpopulations post-treatment. The term cancer stem cells (CSCs) describes a subpopulation that is resistant to many types of chemotherapy and which also possess enhanced migratory and anchorage-independent growth capabilities. These cells are enriched in residual tumor material post-treatment and can serve as the seed for future tumor re-growth, at both primary and metastatic sites. Elimination of CSCs is a key goal in enhancing cancer treatment and may be aided by application of natural products in conjunction with conventional treatments. In this review, we highlight molecular features of CSCs and discuss synthesis, structure-activity relationships, derivatization, and effects of six natural products with anti-CSC activity.

Chemical Proteomic Discovery of Isotype-Selective Covalent Inhibitors of the RNA Methyltransferase NSUN2.

5-Methylcytosine (m5 C) is an RNA modification prevalent on tRNAs, where it can protect tRNAs from endonucleolytic cleavage to maintain protein synthesis. The NSUN family (NSUN1-7 in humans) of RNA methyltransferases are capable of installing the methyl group onto the C5 position of cytosines in RNA. NSUNs are implicated in a wide range of (patho)physiological processes, but selective and cell-active inhibitors of these enzymes are lacking. Here, we use cysteine-directed activity-based protein profiling (ABPP) to discover azetidine acrylamides that act as stereoselective covalent inhibitors of human NSUN2. Despite targeting a conserved catalytic cysteine in the NSUN family, the NSUN2 inhibitors show negligible cross-reactivity with other human NSUNs and exhibit good proteome-wide selectivity. We verify that the azetidine acrylamides inhibit the catalytic activity of recombinant NSUN2, but not NSUN6, and demonstrate that these compounds stereoselectively disrupt NSUN2-tRNA interactions in cancer cells, leading to a global reduction in tRNA m5 C content. Our findings thus highlight the potential to create isotype-selective and cell-active inhibitors of NSUN2 with covalent chemistry targeting a conserved catalytic cysteine.

Targeted Protein Degradation by Electrophilic PROTACs that Stereoselectively and Site-Specifically Engage DCAF1.

Targeted protein degradation induced by heterobifunctional compounds and molecular glues presents an exciting avenue for chemical probe and drug discovery. To date, small-molecule ligands have been discovered for only a limited number of E3 ligases, which is an important limiting factor for realizing the full potential of targeted protein degradation. We report herein the discovery by chemical proteomics of azetidine acrylamides that stereoselectively and site-specifically react with a cysteine (C1113) in the E3 ligase substrate receptor DCAF1. We demonstrate that the azetidine acrylamide ligands for DCAF1 can be developed into electrophilic proteolysis-targeting chimeras (PROTACs) that mediated targeted protein degradation in human cells. We show that this process is stereoselective and does not occur in cells expressing a C1113A mutant of DCAF1. Mechanistic studies indicate that only low fractional engagement of DCAF1 is required to support protein degradation by electrophilic PROTACs. These findings, taken together, demonstrate how the chemical proteomic analysis of stereochemically defined electrophilic compound sets can uncover ligandable sites on E3 ligases that support targeted protein degradation.

Total Synthesis and Anticancer Activity of (+)-Hypercalin†C and Congeners.

The hypercalins are dearomatized acylphloroglucinols with a pendant complex cyclopentane ring that exhibit activity against several cancer cell lines. We report the first total synthesis of (+)-hypercalin C employing a convergent strategy that enabled the dissection of the essential structural features required for the observed anticancer activity. A strategic disconnection involving an unusual C sp3 -C sp2 Suzuki-Miyaura coupling with an α-bromo enolether also revealed an unexpected C-H activation. This strategy targeted designed analogues along the synthetic route to address particular biological questions. These results support the hypothesis that hypercalin C may act as a proton shuttle with the dearomatized acylphloroglucinol moiety being essential for this activity.

Detecting depression based on facial cues elicited by emotional stimuli in video.

Recently, depression research has received considerable attention and there is an urgent need for objective and validated methods to detect depression. Depression detection based on facial expressions may be a promising adjunct to depression detection due to its non-contact nature. Stimulated facial expressions may contain more information that is useful in detecting depression than natural facial expressions. To explore facial cues in healthy controls and depressed patients in response to different emotional stimuli, facial expressions of 62 subjects were collected while watching video stimuli, and a local face reorganization method for depression detection is proposed. The method extracts the local phase pattern features, facial action unit (AU) features and head motion features of a local face reconstructed according to facial proportions, and then fed into the classifier for classification. The classification accuracy was 76.25%, with a recall of 80.44% and a specificity of 83.21%. The results demonstrated that the negative video stimuli in the single-attribute stimulus analysis were more effective in eliciting changes in facial expressions in both healthy controls and depressed patients. Fusion of facial features under both neutral and negative stimuli was found to be useful in discriminating between healthy controls and depressed individuals. The Pearson correlation coefficient (PCC) showed that changes in the emotional stimulus paradigm were more strongly correlated with changes in subjects' facial AU when exposed to negative stimuli compared to stimuli of other attributes. These results demonstrate the feasibility of our proposed method and provide a framework for future work in assisting diagnosis.

Three-Stream Convolutional Neural Network for Depression Detection With Ocular Imaging.

Depression is a prevalent and severe mental disorder that significantly affects both mind and body, leading to persistent feelings of sadness, despair, and impaired functionality. Diagnosis of depression primarily relies on clinical assessment and observation of symptoms. However, due to the lack of objective indicators, the experience and skills of doctor may lead to misdiagnosis. Current researches indicate that eye movement patterns and pupil dilation can serve as potential biomarkers for emotional and cognitive dysregulation in individuals with depression. However, most studies are based on manually extracted eye movement features, overlooking a significant portion of information available in ocular imaging. This paper proposes Three-Stream Convolutional Neural Network (TSCNN) for detecting depression, leveraging both spatio-temporal information of raw ocular imaging and paradigmatic semantic features. We suggest using optical flow with different sampling intervals to capture temporal features. In the third stream, we employ an encoder to learn semantic information from paradigm images and use it as prior knowledge. Finally, we utilize a fully connected network for classification, achieving an accuracy of 79.3% on our self-collected dataset. The proposed method may demonstrate significant clinical utility in the future.

Trial Selection Tensor Canonical Correlation Analysis (TSTCCA) for Depression Recognition with Facial Expression and Pupil Diameter.

Facial expressions have been widely used for depression recognition because it is intuitive and convenient to access. Pupil diameter contains rich emotional information that is already reflected in facial video streams. However, the spatiotemporal correlation between pupillary changes and facial behavior changes induced by emotional stimuli has not been explored in existing studies. This paper presents a novel multimodal fusion algorithm - Trial Selection Tensor Canonical Correlation Analysis (TSTCCA) to optimize the feature space and build a more robust depression recognition model, which innovatively combines the spatiotemporal relevance and complementarity between facial expression and pupil diameter features. TSTCCA explores the interaction between trials and obtains an effective fusion representation of two modalities from a trial subset related to depression. The experimental results show that TSTCCA achieves the highest accuracy of 78.81% with the subset of 25 trials.

Epithelial-mesenchymal transition sensitizes breast cancer cells to cell death via the fungus-derived sesterterpenoid ophiobolin A.

The epithelial-mesenchymal transition (EMT) imparts properties of cancer stem-like cells, including resistance to frequently used chemotherapies, necessitating the identification of molecules that induce cell death specifically in stem-like cells with EMT properties. Herein, we demonstrate that breast cancer cells enriched for EMT features are more sensitive to cytotoxicity induced by ophiobolin A (OpA), a sesterterpenoid natural product. Using a model of experimentally induced EMT in human mammary epithelial (HMLE) cells, we show that EMT is both necessary and sufficient for OpA sensitivity. Moreover prolonged, sub-cytotoxic exposure to OpA is sufficient to suppress EMT-imparted CSC features including sphere formation and resistance to doxorubicin. In vivo growth of CSC-rich mammary cell tumors, is suppressed by OpA treatment. These data identify a driver of EMT-driven cytotoxicity with significant potential for use either in combination with standard chemotherapy or for tumors enriched for EMT features.

A proteome-wide atlas of lysine-reactive chemistry.

Recent advances in chemical proteomics have begun to characterize the reactivity and ligandability of lysines on a global scale. Yet, only a limited diversity of aminophilic electrophiles have been evaluated for interactions with the lysine proteome. Here, we report an in-depth profiling of >30 uncharted aminophilic chemotypes that greatly expands the content of ligandable lysines in human proteins. Aminophilic electrophiles showed disparate proteomic reactivities that range from selective interactions with a handful of lysines to, for a set of dicarboxaldehyde fragments, remarkably broad engagement of the covalent small-molecule-lysine interactions captured by the entire library. We used these latter 'scout' electrophiles to efficiently map ligandable lysines in primary human immune cells under stimulatory conditions. Finally, we show that aminophilic compounds perturb diverse biochemical functions through site-selective modification of lysines in proteins, including protein-RNA interactions implicated in innate immune responses. These findings support the broad potential of covalent chemistry for targeting functional lysines in the human proteome.

A Novel Early-Stage Lung Adenocarcinoma Prognostic Model Based on Feature Selection With Orthogonal Regression.

Carcinoma diagnosis and prognosis are still hindered by the lack of effective prediction model and integration methodology. We proposed a novel feature selection with orthogonal regression (FSOR) method to resolve predictor selection and performance optimization. Functional enrichment and clinical outcome analyses with multi-omics information validated the method's robustness in the early-stage prognosis of lung adenocarcinoma. Furthermore, compared with the classic least absolute shrinkage and selection operator (LASSO) regression method [the averaged 1- to 4-years predictive area under the receiver operating characteristic curve (AUC) measure, 0.6998], the proposed one outperforms more accurately by 0.7208 with fewer predictors, particularly its averaged 1- to 3-years AUC reaches 0.723, vs. classic 0.6917 on The Cancer Genome Atlas (TCGA). In sum, the proposed method can deliver better prediction performance for early-stage prognosis and improve therapy strategy but with less predictor consideration and computation burden. The self-composed running scripts, together with the processed results, are available at https://github.com/gladex/PM-FSOR.

Pharmacophore-Directed Retrosynthesis Applied to Ophiobolin A: Simplified Bicyclic Derivatives Displaying Anticancer Activity.

Pharmacophore-directed retrosynthesis applied to ophiobolin A led to bicyclic derivatives that were synthesized and display anticancer activity. Key features of the ultimate defensive synthetic strategy include a Michael addition/facially selective protonation sequence to set the critical C6 stereocenter and a ring-closing metathesis to form the cyclooctene. Cytotoxicity assays toward a breast cancer cell line (MDA-MB-231) confirm the anticipated importance of structural complexity for selectivity (vs MCF10A cells) while C3 variations modulate stability.