Targeting Necroptosis as a Promising Therapy for Alzheimer's Disease

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease

Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

Discovery of potential RIPK1 inhibitors by machine learning and molecular dynamics simulations

Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) plays a crucial role in inflammation and cell death, so it is a promising candidate for the treatment of autoimmune, inflammatory, neurodegenerative, and ischemic diseases. So far, there are no approved RIPK1 inhibitors available. In this study, four machine learning algorithms were employed (random forest, extra trees, extreme gradient boosting and light gradient boosting machine) to predict small molecule inhibitors of RIPK1. The statistical metrics revealed similar performance and demonstrated outstanding predictive capabilities in all four models. Molecular docking and clustering analysis were employed to confirm six compounds that are structurally distinct from existing RIPK1 inhibitors. Subsequent molecular dynamics simulations were performed to evaluate the binding ability of these compounds. Utilizing the Shapley additive explanation (SHAP) method, the 1855 bit has been identified as the most significant molecular fingerprint fragment. The findings propose that these six small molecules exhibit promising potential for targeting RIPK1 in associated diseases. Notably, the identification of Cpd-1 small molecule (ZINC000085897746) from the Musa acuminate highlights its natural product origin, warranting further attention and investigation.

Profiling of small-molecule necroptosis inhibitors based on the subpockets of kinase-ligand interactions

Necroptosis is a highly regulated cell death (RCD) form in various inflammatory diseases. Receptor-interacting protein kinase 1 (RIPK1) and RIPK3 are involved in the pathway. Targeting the kinase domains of RIPK1 and/or 3 is a drug design strategy for related diseases. It is generally accepted that essential reoccurring features are observed across the human kinase domains, including RIPK1 and RIPK3. They present common N- and C-terminal domains that are built up mostly by α-helices and β-sheets, respectively. The current RIPK1/3 kinase inhibitors mainly interact with the kinase catalytic cleft. This article aims to present an in-depth profiling for ligand-kinase interactions in the crucial cleft areas by carefully aligning the kinase-ligand cocrystal complexes or molecular docking models. The similarity and differential structural segments of ligands are systematically evaluated. New insights on the adaption of the conserved and selective kinase domains to the diversity of chemical scaffolds are also provided. In a word, our analysis can provide a better structural requirement for RIPK1 and RIPK3 inhibition and a guide for inhibitor discovery and optimization of their potency and selectivity.

Unwinding the modalities of necrosome activation and necroptosis machinery in neurological diseases

Necroptosis, a regulated form of cell death, is involved in the genesis and development of various life-threatening diseases, including cancer, neurological disorders, cardiac myopathy, and diabetes. Necroptosis initiates with the formation and activation of a necrosome complex, which consists of RIPK1, RIPK2, RIPK3, and MLKL. Emerging studies has demonstrated the regulation of the necroptosis cell death pathway through the implication of numerous post-translational modifications, namely ubiquitination, acetylation, methylation, SUMOylation, hydroxylation, and others. In addition, the negative regulation of the necroptosis pathway has been shown to interfere with brain homeostasis through the regulation of axonal degeneration, mitochondrial dynamics, lysosomal defects, and inflammatory response. Necroptosis is controlled by the activity and expression of signaling molecules, namely VEGF/VEGFR, PI3K/Akt/GSK-3β, c-Jun N-terminal kinases (JNK), ERK/MAPK, and Wnt/β-catenin. Herein, we briefly discussed the implication and potential of necrosome activation in the pathogenesis and progression of neurological manifestations, such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, traumatic brain injury, and others. Further, we present a detailed picture of natural compounds, micro-RNAs, and chemical compounds as therapeutic agents for treating neurological manifestations.

Structure-Based Design of Novel Alkynyl Thio-Benzoxazepinone Receptor-Interacting Protein Kinase-1 Inhibitors: Extending the Chemical Space from the Allosteric to ATP Binding Pockets

Systemic inflammatory response syndrome (SIRS), characterized by severe systemic inflammation, represents a major cause of health loss, potentially leading to multiple organ failure, shock, and death. Exploring potent RIPK1 inhibitors is an effective therapeutic strategy for SIRS. Recently, we described thio-benzoxazepinones as novel RIPK1 inhibitors and confirmed their anti-inflammatory activity. Herein, we further synthesized novel thio-benzoxazepinones by introducing substitutions on the benzene ring by an alkynyl bridge in order to extend the chemical space from the RIPK1 allosteric to ATP binding pockets. The in vitro cell and kinase assays found that compounds 2 and 29 showed highly potent activity against necroptosis (EC₅₀ = 3.7 and 3.2 nM) and high RIPK1 inhibitory activity (K_d = 9.7 and 70 nM). Prominently, these two analogues possessed better in vivo anti-inflammatory effects than the clinical candidate GSK'772 and effectively blocked hypothermia and deaths in a TNFα-induced SIRS model.

Profiling of the chemical space on the phenyl group of substituted benzothiazole RIPK3 inhibitors

Necroptosis is confirmed as a precisely programmed cell death that is activated in caspase-deficient conditions. Receptor-interacting protein kinase 1 (RIPK1), RIPK3 and mixed-lineage kinase domain-like pseudokinase (MLKL) are the key regulators involved in the signaling pathway. However, accumulating evidence suggests that RIPK1 also works in apoptosis and inflammation pathways independent of necroptosis. Differently, RIPK3 signals necroptosis independent of RIPK1. Thus, identification of specific RIPK3 inhibitors is of great importance for the drug development associated with necroptosis. The benzothiazole carboxamide is a privileged scaffold as RIPK3 inhibitors developed by our group recently. In this study, we work on the phenyl group in-between of benzothiazole and carboxamide to profile the chemical space. Finally, a chlorinated derivative XY-1-127 was found to specifically inhibit necroptosis rather than apoptosis with an EC₅₀ value of 676.8 nM and target RIPK3 with a K_d of 420 nM rather than RIPK1 (K_d = 4300 nM). It was also confirmed to block the formation of necrosome by inhibiting RIPK3 phosphorylation at 1 μM in necroptosis cells. This work discovers the chemical space insights on the phenyl group of the substituted benzothiazole RIPK3 inhibitors and provides a new lead compound for further development.

Role of Necroptosis in Central Nervous System Diseases

Necroptosis is a type of precisely regulated necrotic cell death activated in caspase-deficient conditions. Multiple factors initiate the necroptotic signaling pathway, including toll-like receptor 3/4, tumor necrosis factor (TNF), dsRNA viruses, and T cell receptors. Presently, TNF-induced necroptosis via the phosphorylation of three key proteins, receptor-interacting protein kinase 1, receptor-interacting protein kinase 3, and mixed lineage kinase domain-like protein, is the best-characterized process. Necroptosis induced by Z-DNA-binding protein 1 (ZBP-1) and toll/interleukin-1 receptor (TIR)-domain-containing adapter-inducing interferon (TRIF) plays a significant role in infectious diseases, such as influenza A virus, Zika virus, and herpesvirus infection. An increasing number of studies have demonstrated the close association of necroptosis with multiple diseases, and disrupting necroptosis has been confirmed to be effective for treating (or managing) these diseases. The central nervous system (CNS) exhibits unique physiological structures and immune characteristics. Necroptosis may occur without the sequential activation of signal proteins, and the necroptosis of supporting cells has more important implications in disease development. Additionally, necroptotic signals can be activated in the absence of necroptosis. Here, we summarize the role of necroptosis and its signal proteins in CNS diseases and characterize typical necroptosis regulators to provide a basis for the further development of therapeutic strategies for treating such diseases. In the present review, relevant information has been consolidated from recent studies (from 2010 until the present), excluding the patents in this field.

Paradoxical roles for programmed cell death signaling during viral infection of the central nervous system

Programmed cell death (PCD) is an essential mechanism of antimicrobial defense. Recent work has revealed an unexpected diversity in the types of PCD elicited during infection, as well as defined unique roles for different PCD modalities in shaping the immune response. Here, we review recent work describing unique ways in which PCD signaling operates within the infected central nervous system (CNS). These studies reveal striking complexity in the regulation of PCD signaling by CNS cells, including both protective and pathological outcomes in the control of infection. Studies defining the specialized molecular mechanisms shaping PCD responses in the CNS promise to yield much needed new insights into the pathogenesis of neuroinvasive viral infection, informing future therapeutic development.

A novel necroptosis-related LncRNA signature for prediction of prognosis and therapeutic responses of head and neck squamous cell carcinoma

Background: Long non-coding RNAs (lncRNAs) play an essential role in the occurrence and prognosis of tumors, and it has great potential as biomarkers of tumors. However, the roles of Necroptosis-related lncRNA (NRLs) in Head and neck squamous cell carcinoma (HNSCC) remain elusive. Methods: We comprehensively analyzed the gene expression and clinical information of 964 HNSCC in four cohorts. LASSO regression was utilized to construct a necroptosis-related lncRNA prognosis signature (NLPS). We used univariate and multivariate regression to assess the independent prognostic value of NLPS. Based on the optimal cut-off, patients were divided into high- and low-risk groups. In addition, the immune profile, multi-omics alteration, and pharmacological landscape of NLPS were further revealed. Results: A total of 21 NRLs associated with survival were identified by univariate regression in four cohorts. We constructed and validated a best prognostic model (NLPS). Compared to the low-risk group, patients in the high group demonstrated a more dismal prognosis. After adjusting for clinical features by multivariate analysis, NLPS still displayed independent prognostic value. Additionally, further analysis found that patients in the low-risk group showed more abundant immune cell infiltration and immunotherapy response. In contrast, patients in the high-risk group were more sensitive to multiple chemotherapeutic agents. Conclusion: As a promising tool, the establishment of NLPS provides guidance and assistance in the clinical management and personalized treatment of HNSCC.