Multi-omics dissection of stage-specific artemisinin tolerance mechanisms in Kelch13-mutant Plasmodium falciparum

The rheumatoid arthritis drug Auranofin targets peroxiredoxin 1 and peroxiredoxin 2 to trigger ROS-endoplasmic reticulum stress axis-mediated cell death and cytoprotective autophagy

Auranofin (AF) is a gold-based compound and it has been used in the treatment of rheumatoid arthritis for over four decades. Recently, it has been demonstrated to show significant antitumor activity across various cancer types and is being repurposed as an anticancer drug. However, the precise mechanisms underlying its antitumor effects, particularly its binding targets, remain poorly understood. Here, we demonstrate that Auranofin (AF) exerts cytotoxic effects in 786-O renal cancer cells via inducing apoptosis. Mechanistic studies reveal that AF induces reactive oxygen species (ROS) accumulation, which is a key factor in mediating AF-induced stress and subsequently apoptosis. Notably, both ROS and ER stress induce autophagy, and inhibition of autophagy further enhances AF-induced cytotoxicity. Interestingly, activity-based protein profiling (ABPP) analysis identifies two key antioxidant enzymes, peroxiredoxin 1 (PRDX1) and peroxiredoxin 2 (PRDX2), as direct binding targets of AF. Importantly, overexpression of PRDX1 or PRDX2 inhibits AF-induced ROS accumulation and subsequent apoptosis. Overall, our findings demonstrate that AF induces apoptosis by covalently binding to PRDX1/2 to inhibit its activity, leading to ROS accumulation, which triggers ER stress and apoptosis. At the same time, ER stress triggers a cytoprotective autophagic response. These findings provide novel insights into the mechanism of AF-induced cytotoxicity and suggest PRDX1/2 as critical targets for the development of anti-renal cancer therapies.

Network pharmacology and AI in cancer research uncovering biomarkers and therapeutic targets for RALGDS mutations

The lack of target therapies is accountable for the higher mortality of various types of cancer. To address this issue, we selected a target mutated Kirsten rat sarcoma virus oncogene homologue, which plays a significant role in various cancers. Our study aims to identify selective biomarkers and develop diagnostic and therapeutic strategies for KRAS-associated genes using artificial intelligence. Initially, Genomic data, cancer epidemiology, proteomics network interactions, and omics enrichment were analyzed. Structured E-pharmacophore model aided in capturing the binding cavity using eraser algorithms and fabricating a new selective lead compound for the KRSA. The selective molecule was abridged inside the binding cavity and stability was validated through 100 ns molecular dynamics simulations. Epidemiological-neural network studies indicated KRAS mutations leads 40 types of cancer, exclusively pancreatic and colorectal cancers, with diploid and missense mutations as primary factors. Pathway analysis highlighted the involvement of the MAPK and RAS signaling pathways in cancer development and proteomics analysis identified RALGDS as a key protein. Protein-based pharmacophore analysis mapped the biologically active features such as donor, acceptor and aromatic ring with the designed ligands. The results of interaction interpretation illustrate that the amino acid Tyr566 formed an H-bond interaction with the amine group of the octyl ring system and 20 amino acids crafted to properly orient the molecule to fit inside the polar cavity of KRAS protein. The MMGBSA score of - 53.33 kcal/mol conformed to the well-configured binding with KRSA and realistic model simulation exposed the π-π, π-cationic and hydrophobic interactions stabilised the molecule inside the KRSA protein throughout 100 ns simulation. The study demonstrates the vitality of AI and network pharmacology to identify potential-target biomarkers for KRAS-associated genes, paving the way for improved cancer diagnostics and therapeutics.

Target Discovery Driven by Chemical Biology and Computational Biology

Target identification is crucial for drug screening and development because it can reveal the mechanism of drug action and ensure the reliability and accuracy of the results. Chemical biology, an interdisciplinary field combining chemistry and biology, can assist in this process by studying the interactions between active molecular compounds and proteins and their physiological effects. It can also help predict potential drug targets or candidates, develop new biomarker assays and diagnostic reagents, and evaluate the selectivity and range of active compounds to reduce the risk of off-target effects. Chemical biology can achieve these goals using techniques such as changing protein thermal stability, enzyme sensitivity, and molecular structure and applying probes, isotope labeling and mass spectrometry. Concurrently, computational biology employs a diverse array of computational models to predict drug targets. This approach also offers innovative avenues for repurposing existing drugs. In this paper, we review the reported chemical biology and computational biology techniques for identifying different types of targets that can provide valuable insights for drug target discovery.

The spatiotemporal transcriptional profiling of murine brain during cerebral malaria progression and after artemisinin treatment

Cerebral malaria (CM) is a severe encephalopathy caused by Plasmodium parasite infection, resulting in thousands of annual deaths and neuro-cognitive sequelae even after anti-malarial drugs treatment. Despite efforts to dissect the mechanism, the cellular transcriptomic reprogramming within the spatial context remains elusive. Here, we constructed single-cell and spatial transcriptome atlases of experimental CM (ECM) male murine brain tissues with or without artesunate (ART) treatment. We identified activated inflammatory endothelial cells during ECM, characterized by a disrupted blood-brain barrier, increased antigen presentation, and leukocyte adhesion. We also observed that inflammatory microglia enhance antigen presentation pathway such as MHC-I to CD8+ cytotoxic T cells. The latter underwent an inflammatory state transition with up-regulated cytokine expression and cytotoxic activity. Multi-omics analysis revealed that the activated interferon-gamma response of injured neurons during ECM and persisted after ART treatment. Overall, our research provides valuable resources for understanding malaria parasite-host interaction mechanisms and adjuvant therapy development.

Multimodal lung cancer theranostics via manganese phosphate/quercetin particle

The diagnosis and treatment of non-small cell lung cancer in clinical settings face serious challenges, particularly due to the lack of integration between the two processes, which limit real-time adjustments in treatment plans based on the patient's condition and drive-up treatment costs. Here, we present a multifunctional pH-sensitive core-shell nanoparticle containing quercetin (QCT), termed AHA@MnP/QCT NPs, designed for the simultaneous diagnosis and treatment of non-small cell lung cancer. Mechanistic studies indicated that QCT and Mn2+ exhibited excellent peroxidase-like (POD-like) activity, catalysing the conversion of endogenous hydrogen peroxide into highly toxic hydroxyl radicals through a Fenton-like reaction, depleting glutathione (GSH), promoting reactive oxygen species (ROS) generation in mitochondria and endoplasmic reticulum, and inducing ferroptosis. Additionally, Mn2+ could activate the cGAS-STING signalling pathway and promote the maturation of dendritic cells and infiltration of activated T cells, thus inducing tumor immunogenic cell death (ICD). Furthermore, it exhibited effective T2-weighted MRI enhancement for tumor imaging, making them valuable for clinical diagnosis. In vitro and in vivo experiments demonstrated that AHA@MnP/QCT NPs enabled non-invasive imaging and tumor treatment, which presented a one-stone-for-two-birds strategy for combining tumor diagnosis and treatment, with broad potential for clinical application in non-small cell lung cancer therapy.

The pharmacodynamic and pharmacological mechanisms underlying nanovesicles of natural products: Developments and challenges

Natural products such as Traditional Chinese Medicines (TCMs) show great advantages in the treatment and prevention of diseases, but the unclear effective ingredients and mechanisms are key obstacles to restrict their rapid development. Under the guidance of the theoretical guidance of reductionism and the theoretical of allopathic medicine, some researches have indeed achieved some breakthrough results. However, these incomplete methods mainly limited to direct actions or indirect actions (such as the intermediated substances mediated cross-organ or cross-system regulation) mechanism of single active ingredient derived from natural products, which are often inconsistent with Systemism and Harmonizing Medicine and make it difficult to reasonably explain the pharmacodynamics and pharmacological mechanism of most natural products. Actually, effective pharmaceutical ingredients often do not exist in the form of free monomers, but prefer to assembly nanovesicles (NVs) for a combinational pharmacological effect, mainly including self-assembled nanoparticles (SANs) and exosome-like nanoparticles (ELNs). These developments of NVs-based application are a good supplement to existing pharmacological mechanism research. Hence, this review focuses on the developments and strategies of the pharmacodynamics and pharmacological mechanism of NVs-based TCMs under the combining theory of traditional Chinese and western medicine. On this basis, a novel "multidimensional combination" research approach is proposed firstly, which will provide new strategies and directions for breaking through the bottleneck of pharmacological mechanism research, and promote the clinical application of innovative natural products including TCMs.

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanisms-are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.

High-dimensional deconstruction of ovarian cancer at single-cell precision reveals HEBP2 that reshape the TIME and drive carboplatin resistance

BACKGROUND

Single-cell sequencing was employed to analyze the tumor immune microenvironment in ovarian cancer (OC) patients, exploring the evolutionary roles of various macrophage subgroups in OC progression and their correlation with fatty acid metabolism-related genes in contributing to drug resistance.

METHODS

This study aimed to decipher the mechanisms underlying OC chemoresistance (OC-CR) and carboplatin resistance by integrating and analyzing multiple single-cell RNA sequencing datasets from OC patients. The tumor immune microenvironment in OC-CR patients exhibited notable alterations in cellular interactions and the proportions of different immune cell populations, in contrast to the cohort sensitive to OC chemotherapy.

RESULTS

The study demonstrates that the fatty acid-associated gene HEBP2 not only accelerates OC progression but also modifies the immune landscape of OC, driving the polarization from M0_TAM to M2_TAM. This shift results in a diminished efficacy of chemotherapy in OC. Furthermore, both in vitro and in vivo experiments underscored HEBP2's role in boosting the proliferation of OC-resistant cell lines and suppressing apoptosis, thereby facilitating carboplatin resistance.

CONCLUSION

In conclusion, the immune microenvironments of OC-CR significantly differ from those sensitive to chemotherapy, underscoring HEBP2's role in fostering OC resistance. This establishes HEBP2 as a promising prognostic marker and a novel target for therapeutic strategies against OC resistance.

Chemoproteomics-based profiling reveals potential antimalarial mechanism of Celastrol by disrupting spermidine and protein synthesis

BACKGROUND

Malaria remains a global health burden, and the emergence and increasing spread of drug resistance to current antimalarials poses a major challenge to malaria control. There is an urgent need to find new drugs or strategies to alleviate this predicament. Celastrol (Cel) is an extensively studied natural bioactive compound that has shown potentially promising antimalarial activity, but its antimalarial mechanism remains largely elusive.

METHODS

We first established the Plasmodium berghei ANKA-infected C57BL/6 mouse model and systematically evaluated the antimalarial effects of Cel in conjunction with in vitro culture of Plasmodium falciparum. The potential antimalarial targets of Cel were then identified using a Cel activity probe based on the activity-based protein profiling (ABPP) technology. Subsequently, the antimalarial mechanism was analyzed by integrating with proteomics and transcriptomics. The binding of Cel to the identified key target proteins was verified by a series of biochemical experiments and functional assays.

RESULTS

The results of the pharmacodynamic assay showed that Cel has favorable antimalarial activity both in vivo and in vitro. The ABPP-based target profiling showed that Cel can bind to a number of proteins in the parasite. Among the 31 identified potential target proteins of Cel, PfSpdsyn and PfEGF1-α were verified to be two critical target proteins, suggesting the role of Cel in interfering with the de novo synthesis of spermidine and proteins of the parasite, thus exerting its antimalarial effects.

CONCLUSIONS

In conclusion, this study reports for the first time the potential antimalarial targets and mechanism of action of Cel using the ABPP strategy. Our work not only support the expansion of Cel as a potential antimalarial agent or adjuvant, but also establishes the necessary theoretical basis for the development of potential antimalarial drugs with pentacyclic triterpenoid structures, as represented by Cel. Video Abstract.

Chemoproteomics Reveals Glaucocalyxin A Induces Mitochondria-Dependent Apoptosis of Leukemia Cells via Covalently Binding to VDAC1

Chronic myelogenous leukemia (CML) that is resistant to tyrosine kinase inhibitors is one of the deadliest hematologic malignancies, and the T315I mutation in the breakpoint cluster region-Abelson (BCR-ABL) kinase domain is the most prominent point mutation responsible for imatinib resistance in CML. Glaucocalyxin A (GLA), a natural bioactive product derived from the Rabdosia rubescens plant, has strong anticancer activity. In this study, the effect and molecular mechanism of GLA on imatinib-sensitive and imatinib-resistant CML cells harboring T315I mutation via a combined deconvolution strategy of chemoproteomics and label-free proteomics is investigated. The data demonstrated that GLA restrains proliferation and induces mitochondria-dependent apoptosis in both imatinib-sensitive and resistant CML cells. GLA covalently binds to the cysteine residues of mitochondrial voltage-dependent anion channels (VDACs), resulting in mitochondrial damage and overflow of intracellular apoptotic factors, eventually leading to apoptosis. In addition, the combination of GLA with elastin, a mitochondrial channel VDAC2/3 inhibitor, enhances mitochondria-dependent apoptosis in imatinib-sensitive and -resistant CML cells, representing a promising therapeutic approach for leukemia treatment. Taken together, the results show that GLA induces mitochondria-dependent apoptosis via covalently targeting VDACs in CML cells. GLA may thus be a candidate compound for the treatment of leukemia.

The many paths to artemisinin resistance in Plasmodium falciparum

Emerging resistance against artemisinin (ART) poses a major challenge in controlling malaria. Parasites with mutations in PfKelch13, the major marker for ART resistance, are known to reduce hemoglobin endocytosis, induce unfolded protein response (UPR), elevate phosphatidylinositol-3-phosphate (PI3P) levels, and stimulate autophagy. Nonetheless, PfKelch13-independent resistance is also reported, indicating extensive complementation by reconfiguration in the parasite metabolome and transcriptome. These findings implicate that there may not be a single 'universal identifier' of ART resistance. This review sheds light on the molecular, transcriptional, and metabolic pathways associated with ART resistance, while also highlighting the interplay between cellular heterogeneity, environmental stress, and ART sensitivity.