👤 Yang M

Drug-drug interactions (DDIs) are a significant source of morbidity and adverse drug events (ADEs), particularly in situations of polypharmacy and complex medication regimens. While rules-based software integrated in electronic health records (EHRs) has demonstrated proficiency in identifying DDIs present in medication regimens, large language model (LLM) based identification requires thorough benchmarking and performance evaluation using high-quality datasets for safe use. The purpose of this study was to develop a series of performance benchmarking experiments specifically for LLM performance in identification and management of DDIs using a specifically curated clinician-annotated dataset of clinically-relevant DDIs. Show less

Biomedical research benefits from the rapid growth and diversity of experimentally detected protein-protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PPI networks can be challenging to interpret and apply. The 2025 update of the Integrated Interactions Database (IID) enhances accessibility and utility through several new features. We identify and incorporate network structural components from co-purified protein sets, as well as curated and predicted complexes, enabling users to explore network organization beyond binary interactions. Functional, pathway, and disease associations of these components can be analyzed, enabling interactions to be grouped into higher-order structures with known or provisional biological roles. Users can now filter interactions by five detection types: pairwise, co-purification, colocalization, proximity, and other evidence. To extend the value and information of predicted interactions, we include interaction interface predictions for 53 647 PPIs, generated using the MEGADOCK docking algorithm, adding molecular detail for structural biology and variant impact studies. Finally, we map PPIs to 15 immune cell types and 12 additional normal tissues, offering tissue-specific views of interaction networks increasingly relevant in disease and immunology research. IID 2025 now includes over 1 million experimentally detected human PPIs, representing an 83% increase from the previous release, alongside expanded non-human networks. The portal remains publicly available at https://ophid.utoronto.ca/iid. Show less

Ferroptosis is a type of programmed cell death characterized by accumulation of free iron, reactive oxygen species generation and lipid peroxidation and is distinct from other types of regulated cell deaths such as apoptosis, necrosis and autophagy. Ferroptosis is distinct from other programmed cell deaths for its iron dependence and its significant role in tumor suppression. Therefore, harnessing ferroptosis may offer promising avenues for cancer therapy. In the present review, the different pathways that lead to ferroptosis, the genes and transcription factors involved in both iron and lipid metabolism, as well as the impact of small‑molecule alterations on the regulation of ferroptotic cell death, were discussed. Furthermore, the emergence of combination therapies with ferroptosis‑inducing molecules that overcome resistance to conventional chemotherapy, particularly in solid tumors, were highlighted. Show less

Corrinoids are cobalt-containing tetrapyrroles. They include adenosylcobalamin (vitamin B12) and cobamides that function as cofactors and coenzymes for methyl transfer, radical-dependent and redox reactions. Though cobamides are the most complex cofactors in nature, they are essential in the acetyl-CoA pathway, thought to be the most ancient CO2-fixation pathway, where they perform a pterin-to-cobalt-to-nickel methyl transfer reaction catalyzed by the corrinoid iron-sulphur protein (CoFeS). CoFeS occurs in H2-dependent archaeal methanogens, the oldest microbial lineage by measure of physiology and carbon isotope data, dating corrinoids to ca. 3.5 billion years. However, CoFeS and cobamides are also essential in the acetyl-CoA pathway of H2-dependent bacterial acetogens. To determine whether corrin biosynthesis was established before archaea and bacteria diverged, whether the pathways arose independently or whether cobamide biosynthesis was transferred from the archaeal to the bacterial lineage (or vice versa) during evolution, we investigated phylogenies and structural data for 26 enzymes of corrin ring and lower ligand biosynthesis. The data trace cobamide synthesis to the common ancestor of bacteria and archaea, placing it in the last universal common ancestor of all lifeforms (LUCA), while pterin-dependent methyl synthesis pathways likely arose independently post-LUCA in the lineages leading to bacteria and archaea. Enzymes of corrin biosynthesis were recruited from preexisting ancient pathways. Evolutionary forerunners of CoFeS function were likely Fe-, Ni- and Co-containing solid-state surfaces, which, in the laboratory, catalyze the reactions of the acetyl-CoA pathway from CO2 to pyruvate under serpentinizing hydrothermal conditions. The data suggest that enzymatic corrin biosynthesis replaced insoluble solid-state catalysts that tethered primordial CO2 assimilation to the Earth's crust, suggesting a role for corrin synthesis in the origin of free-living cells. Show less

The ubiquitously distributed ammonia-oxidizing archaea generate energy from ammonia and build cell mass from inorganic carbon sources, thereby contributing to both the global nitrogen and carbon cycles. However, little is known about the regulation of their predicted core carbon metabolism. A thermodynamic model for Nitrososphaera viennensis was developed to estimate the consumption of inorganic carbon in relation to ammonia consumed for energy and was tested experimentally by growing cells in carbon-limited and excess conditions. A combined proteomic and metabolomic approach to the experimental conditions revealed distinct metabolic adaptation depending on the amount of carbon supplied, either in a catalase or pyruvate background as a reactive oxygen species scavenger. Integration of protein and metabolite dynamics revealed a cellular strategy under carbon limitation to maintain a pool of amino acids and an upregulation of proteins necessary for translation initiation to stay primed for protein synthesis. The combination of modeling and functional genomics fills gaps in the understanding of the central metabolism and its regulation in a chemolithoautotrophic, ammonia-oxidizing archaeon, even in the absence of available genetic tools.IMPORTANCELittle is known about the regulation of carbon metabolism within ammonia-oxidizing archaea (AOA), a widespread clade that plays a critical role in the global nitrogen cycle while also fixing inorganic carbon. To address this missing knowledge, the soil AOA Nitrososphaera viennensis was subjected to various levels of inorganic carbon and analyzed via a systems biology approach to better understand how its core metabolism is regulated. The results demonstrate a strong dependence on the carbon fixation cycle and highlight key connection points between the core metabolic pathways. The analysis additionally revealed tight control on translational processes and elucidated unique cellular responses when the organism was exposed to either exogenous catalase or pyruvate to relieve oxidative stress from reactive oxygen species. The presented data highlight metabolic responses of N. viennensis and provide a better understanding of how the organism, and likely other AOA, respond to various environmental conditions. Show less

The tumor suppressor protein, p53, which is mutated in half of human tumors, plays a critical role in cellular responses to DNA damage and maintenance of genome stability. Therefore, increasing our understanding of the p53 pathway is essential for improving cancer treatment and diagnosis. Show less

Adverse drug reactions (ADRs) are harmful side effects of medications. Social media provides real-time, patient-generated data, though its unstructured format presents challenges. Natural language processing and transfer learning offer promising solutions. Show less

In the healthcare industry, the ever-increasing volume of clinical trial data presents challenges for ensuring drug safety and detecting adverse drug reactions (ADRs). This study aims to address the challenge of accurately detecting Serious Adverse Events (SAEs) in pharmacovigilance, a critical component in ensuring drug safety during and after clinical trials. The key problem lies in the underreporting and delayed detection of Adverse Drug Reactions (ADRs) due to the heterogeneous nature of medical data, class imbalance, and the limited scope of traditional monitoring techniques. This study proposes a hybrid AI-driven framework that integrates structured (e.g., patient demographics, lab results) and unstructured data (e.g., clinical notes) to detect ADRs using advanced deep learning and NLP methods. The objective is to outperform traditional signal detection methods and provide interpretable predictions to aid clinicians in real-time. By leveraging advanced Machine Learning (ML) and Deep Learning (DL) techniques, including Random Forests, Gradient Boosting Machines, and Convolutional Neural Networks (CNNs), our model aims to identify potential ADRs across different patient subgroups. Through meticulous feature engineering and the application of techniques to address data imbalance, our model demonstrates improved accuracy and interpretability in predicting ADRs. The CNN model achieved an accuracy of 85 %, outperforming traditional models, such as Logistic Regression (78 %) and Support Vector Machines (80 %). These findings suggest that specific demographic and clinical factors significantly influence the likelihood of adverse reactions, offering valuable insights for targeted monitoring and risk mitigation strategies[11]. This research underscores the potential of predictive modeling to enhance pharmacovigilance efforts and ensure safer clinical trial outcomes.•The research methodology includes a comparison of supervised learning algorithms, such as Logistic Regression, Random Forest, Gradient Boost, CNN, and genetic algorithms, to identify patterns and anomalies in clinical trial data. BERT and GPT, were also employed to provide the functionality of textual interactions over medical data.•Performance metrics such as accuracy, precision, recall, and F1-score were systematically applied to evaluate each model's performance. Among the models tested, the CNN model with BERT achieved the highest accuracy, providing valuable insights into the potential of deep learning for enhancing pharmacovigilance practices.•These findings suggest that an inclusion of diverse clinical data when supplied to advanced ML and NLP techniques can significantly improve the detection of ADRs, leading to better alignment with the fundamental principles of Good Clinical Practice (GCP). Show less

The use of multiple medications increases the risk of harmful drug-drug interactions (DDIs). Conventional DDI screening databases vary in coverage and often trigger low-relevance alerts, contributing to alert fatigue. Large language models (LLMs) have emerged as potential tools for DDI identification, however, their performance compared to established databases using real-world patient data remains under-explored. Show less

Psychiatric diseases are often treated with several drugs. In addition, the risk of developing somatic comorbidities which may require drug therapy is higher in patients with than in patients without psychiatric diseases. Further on, the risk of drug-drug interactions (DDI) increases with the number of drugs taken. The aim of this study was to analyze whether already known DDI between psychiatric drugs and somatic medications still occur in everyday clinical practice. Show less

Drug-drug interactions (DDI) are an important cause of adverse drug reactions (ADRs). Could large language models (LLMs) serve as valuable tools for pharmacovigilance specialists in detecting DDIs that lead to ADR notifications? Show less

Computational drug discovery is essential for screening potential treatments and reducing the costs and time associated with proposing or combining drugs for disease management. Despite the extensive research conducted in this field, it remains an emerging area, particularly with the advent of machine learning, deep learning, and large language models (LLMs). This systematic review examines the integration of machine learning and deep learning techniques in drug discovery, concentrating on three critical areas: drug-drug interactions (DDIs), drug-target interactions (DTIs), and adverse drug reactions (ADRs). The review analyzes over 100 papers published between 2020 and 2025, categorizing the methods into deep learning, machine learning, graph learning, and hybrid models. It highlights the transformative impact of natural language processing (NLP) and LLMs in extracting meaningful insights from biomedical literature and chemical data. Furthermore, this work introduces key databases and data sets widely utilized in drug discovery. Additionally, this review identifies gaps in the existing research, such as the lack of comprehensive studies that simultaneously address DDI, DTI, and ADR extraction, and it proposes a more holistic approach to fill these gaps. The paper concludes by thoroughly evaluating various models, underscoring their performance metrics. Show less

Predicting protein‒protein interactions (PPIs) plays a crucial role in understanding biological processes. Although biological experimental methods can identify PPIs, they are costly, time-consuming, labor-intensive, and often lack stability. In contrast, computational approaches for PPI prediction, particularly deep learning methods, can efficiently learn representations from protein sequences. However, the generalizability, robustness, and stability of computational PPI prediction models still need improvement, especially for species with limited verified PPI data. Protein embeddings generated by protein language models can extract features from protein sequences and reflect hierarchical biological structures, making them suitable for predicting PPIs. Therefore, in this study, we propose a novel protein sequence-based PPI prediction framework designed for generalized PPI assessment by integrating two protein language models (PLMs) and an enhanced deep neural network (MPIDNN-GPPI). Specifically, the sequences are embedded using two protein language models, Ankh and ESM-2. A deep neural network is then used to learn representations from the feature vectors produced by PLMs. Subsequently, a multi-head attention mechanism is introduced to capture long-range dependencies and fuse them with DNN-derived representations. Finally, a deep neural network is applied to assess the probability of interaction between two proteins. To evaluate the performance of MPIDNN-GPPI, nine PPI datasets were collected from the STRING database, covering a diverse set of species: five datasets from mammals (D. melanogaster, C. elegans, S. cerevisiae, H. sapiens, and M. musculus), and four datasets from plants (O. sativa, A. thaliana, G. max, and Z. mays). When trained on H. sapiens, MPIDNN-GPPI achieved AUC values of 0.959, 0.966, 0.954, and 0.916 on independent test sets for M. musculus, D. melanogaster, C. elegans, and S. cerevisiae, respectively. These results represent the best performance among all PPI models compared in this study. Similarly, when trained on O. sativa, the model achieved AUC values of 0.96, 0.95, and 0.913 on independent datasets for A. thaliana, G. max, and Z. mays, respectively. Ablation experiments demonstrated that models combining Ankh and ESM-2 outperformed those relying on a single protein language model. Furthermore, MPIDNN-GPPI, which incorporates multi-head attention and deep neural networks (DNN), achieved superior performance compared to models using DNN alone. These findings indicate that MPIDNN-GPPI possesses strong generalization capability for cross-species PPI prediction. The proposed model, trained on one species, can be effectively applied to accurately predict PPIs in other species. Show less

As two pivotal regulatory factors in cancer biology, oxidative stress and inflammation interact dynamically through complex network mechanisms to influence tumor initiation, progression, and treatment resistance. Oxidative stress induces genomic instability, oncogenic signaling activation, and tumor microenvironment (TME) remodeling via the abnormal accumulation of reactive oxygen species (ROS) or reactive nitrogen species (RNS). Conversely, inflammation sustains malignant phenotypes by releasing pro-inflammatory cytokines and chemokines and promoting immune cell infiltration. These processes create a vicious cycle via positive feedback loops whereby oxidative stress initiates inflammatory signaling, while the inflammatory milieu further amplifies ROS/RNS production, collectively promoting proliferation, migration, angiogenesis, drug resistance, and immune evasion in tumor cells. Moreover, their crosstalk modulates DNA damage repair, metabolic reprogramming, and drug efflux pump activity, significantly impacting the sensitivity of cancer cells to chemotherapy, radiotherapy, and targeted therapies. This review systematically discusses these advances and the molecular mechanisms underlying the interplay between oxidative stress and inflammation in cancer biology. It also explores their potential as diagnostic biomarkers and prognostic indicators and highlights novel therapeutic strategies targeting the oxidative stress-inflammation axis. The goal is to provide a theoretical framework and translational roadmap for developing synergistic anti-tumor therapies. Show less

The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication, we describe ongoing changes to our production pipeline to limit the sequences available in UniProtKB to high-quality, non-redundant reference proteomes. We continue to manually curate the scientific literature to add the latest functional data and use machine learning techniques. We also encourage community curation to ensure key publications are not missed. We provide an update on the automatic annotation methods used by UniProtKB to predict information for unreviewed entries describing unstudied proteins. Finally, updates to the UniProt website are described, including a new tab linking protein to genomic information. In recognition of its value to the scientific community, the UniProt database has been awarded Global Core Biodata Resource status. Show less

To mimic the structural aspects of staurosporine, a potent but unspecific kinase inhibitor, several coordination compounds based on two readily available diimine ligands containing hydrogen bonding donor/acceptor sites (NH-CO fragment) have been designed and synthesized. These complexes are constructed around Ru(II) and Pt(II) metal centers. A total of 9 compounds, named Ru(1)-(5) and Pt(1)-(4), were obtained through straightforward synthetic approaches. The cytotoxicity of the compounds was evaluated on AGS gastric cancer cells (GC) through standard MTT assays. All ruthenium and platinum complexes with low toxicity, i.e.Ru(3), Ru(5), Pt(3) and Pt(4), were docked in the ATP binding pocket of two protein kinases (S6K1 and MST2). The docking scores highlighted a preferred affinity of Ru(5) for the MST2 binding pocket, whereas the platinum compounds are predicted to bind stronger to the S6K1 binding site. Inhibitory activity of the metal complexes on the MST2 and S6K1 signaling pathways was evaluated by analyzing via western blot experiments the phosphorylation state of YAP, a downstream component of the Hippo pathway and the protein expression of S6 and its phosphorylated analogue p-S6. A clear difference of behavior between the Pt(II) and the Ru(II) complexes depending on the type of kinase was observed. Show less

Background

Melanoma is the most aggressive and lethal skin cancer that affects thousands of people worldwide. Ruthenium complexes have shown promising results as cancer chemotherapeutics, offering several advantages over platinum drugs, such as potent efficacy, low toxicity, and less drug resistance. Additionally, anthraquinone derivatives have broad therapeutic applications, including melanoma.

Objectives

Thus, two new ruthenium complexes with 1-hydroxy-9,10-anthraquinone were obtained: trans-[Ru(HQ)(PPh₃)₂(bipy)]PF₆ (1) and cis-[RuCl₂(HQ)(dppb)] (2), where HQ = 1-hydroxy-9,10-anthraquinone, PPh₃ = triphenylphospine, bipy = 2,2'-bipyridine, PF₆ = hexafluorophosphate, and dppb = 1,4-bis(diphenylphosphine)butane.

Methods

The complexes were characterized by infrared (IR), UV-vis, ¹H, ¹³C{¹H}, and ³¹P{¹H} NMR spectroscopies, molar conductivity, cyclic voltammetry, and elemental analysis. Furthermore, density functional theory (DFT) calculations were performed.

Results

Compound (2) was determined by single-crystal X-ray diffraction, which confirms the bidentate coordination mode of HQ through the carbonyl and phenolate oxygens. Additionally, DNA-binding experiments yielded constants of 10⁵ M^-1 (Kb = 6.93 × 10⁵ for (1) and 1.60 × 10⁵ for (2)) and demonstrate that both complexes can interact with DNA through intercalation, electrostatic attraction, or hydrogen bonding.

Conclusions

The cytotoxicity profiles of the compounds were evaluated in human melanoma cell lines (SK-MEL-147, CHL-1, and WM1366), revealing greater cytotoxic activity for (1) on the CHL-1 cell line with an IC₅₀ of 14.50 ± 1.09 µM. Subsequent studies showed that (1) inhibits the proliferation of CHL-1 cells and induces apoptosis, associated at least in part with the pro-oxidant effect and cell cycle arrest at the G1/S transition. Show less

Hypoxia, a hallmark of many solid tumors, is linked to increased cancer aggressiveness, metastasis, and resistance to conventional therapies, leading to poor patient outcomes. This challenges the efficiency of photodynamic therapy (PDT), which relies on the generation of cytotoxic reactive oxygen species (ROS) through the irradiation of a photosensitizer (PS), a process partially dependent on oxygen levels. In this work, we introduce a novel family of potent PSs based on ruthenium(II) polypyridyl complexes with 2,2'-bipyridyl ligands derived from COUPY coumarins, termed COUBPYs. Ru-COUBPY complexes exhibit outstanding in vitro cytotoxicity against CT-26 cancer cells when irradiated with light within the phototherapeutic window, achieving nanomolar potency in both normoxic and hypoxic conditions while remaining nontoxic in the dark, leading to impressive phototoxic indices (>30,000). Their ability to generate both Type I and Type II ROS underpins their exceptional PDT efficiency. The lead compound of this study, SCV49, shows a favorable in vivo pharmacokinetic profile, excellent toxicological tolerability, and potent tumor growth inhibition in mice bearing subcutaneous CT-26 tumors at doses as low as 3 mg/kg upon irradiation with deep-red light (660 nm). These results allow us to propose SCV49 as a strong candidate for further preclinical development, particularly for treating large hypoxic solid tumors. Show less

Title: The role of ancillary ligands on benzodipyridophenazine-based Ru(II)/Ir(III) complexes in dark and light toxicity against TNBC cells. Abstract: In this study, we investigated the impact of ancillary ligands on the anticancer activity of benzodipyridophenazine-based Ru(II) and Ir(III) complexes (Ru1, Ru2, Ir1, and Ir2). These metal complexes displayed three significant absorption bands attributed to the ligand-centered (LC) transitions, ligand-to-ligand charge transfer (LLCT), and metal-to-ligand charge transfer (MLCT). Binding studies of biomolecules were performed with the complexes along with the ligand, and it was found that after binding with Ru(II)/Ir(III), the properties of the ligands were enhanced. In vitro screening revealed that complex [(η5-Cp*)IrIIICl(κ2-N,N-benzo[i]dipyrido[3,2-a:2',3'-c])phenazine] (Ir1) exhibited the highest potency and selectivity (IC50 ∼ 2.14 μM, PI > 13) under yellow light irradiation. The photo-toxicity trend was Ir1 > Ru1 > Ir2 ≫ Ru2, which was found to be directly correlated with the singlet oxygen quantum yield (1O2). Chloro-substituted complexes (Ir1 and Ru1) were effective for hypoxic tumor treatment, particularly Ir1, which could generate high amounts of reactive oxygen species (ROS, type I PDT) in cells under photo irradiation. The high value of fluorescence quantum yield (fφ = 0.26) and significant emission at λ = 571 nm of Ir1 were certainly useful for bio-imaging applications. Colocalisation and DCFDA studies of Ir1 revealed that it can accumulate in the mitochondria, leading to depolarization of the mitochondrial membrane. These studies confirm that the complex Ir1 is a promising candidate for TNBC treatment in hypoxic tumors, with efficacy comparable to the current PDT drug Photofrin. Show less

In order to discover new dual-active agents, novel ruthenium (η⁶-p-cymene) complexes of the general formula [(η⁶-p-cym)Ru(OO)Cl] with O,O-diketo ester ligands ethyl 2-hydroxy-4-aryl-4-oxobut-2-enoate (1-3), were synthesized. The complexes 1-3 were characterized by spectral techniques (UV-Vis, IR, ¹H and ¹³C NMR, and ESI-HRMS), elemental analysis, and X-ray crystallography. Based on in vitro DNA/HSA experiments, complex 1 exhibited the highest DNA/HSA-activity, suggesting that the presence of an alkene chain contributes to increased activity. The cytotoxic activity of 1-3 was evaluated in a panel of human cancer cell lines (A549, MDA-MB-231, LS-174, HeLa), and in one normal cell line (MRC-5), both in the absence and presence of biocompatible ionic liquids (BIO-ILs) such as cholinium glycinate (Cho-Gly), cholinium β-alaninate (Cho-Ala), and cholinium glutamate (Cho-Glu). Complex 1 exhibited the highest cytotoxicity and demonstrated selectivity toward HeLa cells. Additionally, its cytotoxicity was enhanced when combined with the BIO-ILs Cho-Gly and Cho-Ala. This study suggests that ionic liquids can influence the efficacy and selectivity of cancer treatments, highlighting the potential for enhancing therapeutic outcomes. However, it also emphasizes the need for a deeper understanding of BIO-IL interactions with cellular processes. Furthermore, compound 1 displayed strong antimicrobial activity against Staphylococcus aureus and Escherichia coli (MIC = 0.078 mg/mL). Among the assessed species, Candida albicans showed the highest sensitivity to antifungal activity. These results suggest that investigated compounds may have potential for further development as clinical candidates, pending additional studies. Show less

Acute leukemia, a cancer originating in the bone marrow and blood-forming tissues, poses a significant threat to human health. Chemotherapy may cause a range of side effects and further cause greater suffering to the patients. Thus, reducing the toxicity of the drugs for treating leukemia has become a significant challenge. In this study, we developed two non‑platinum anticancer agents, ole-Ru and ole-Ir, by fusing the natural product oleanolic acid as the ligand into two metal (ruthenium and iridium) precursors. Ole-Ru and ole-Ir not only exhibited remarkable selectivity and cytotoxicity against NB4 cells through the apoptosis pathway, but also demonstrated low toxicity towards normal lung fibroblast cells, suggesting their potential for targeted treatment of acute leukemia cells. This work presents a rational design strategy for metal-based anticancer complexes aimed at inhibiting NB4 cells and expanded the scope of metallodrugs used in the treatment of leukemia. Show less

Title: Systematic Investigation of Coordination Chemistry in Iridium(III) and Ruthenium(II) Complexes Derived from Pyridyl-Amine Ligands and Their Anticancer Evaluation. Abstract: A systematic investigation of the coordination chemistry of iridium(III) and ruthenium(II) complexes synthesized from pyridyl-amine ligands was performed, focusing on how ligand steric hindrance and metal centers affect oxidation behavior, coordination modes, and biological activities. The study revealed that steric hindrance at the ligand's bridge carbon strongly influenced both oxidation behavior and coordination modes. Smaller substituents (e.g., H and Me) facilitated oxidation to form pyridyl-imine species under adventitious oxygen, whereas bulky substituents (e.g., i-Bu and mesityl) suppressed oxidation, yielding stable pyridyl-amine or 16-electron pyridyl-amido complexes. Moreover, iridium(III) complexes were more prone to oxidation than the corresponding ruthenium(II) complexes under similar conditions. The aqueous stability of the newly synthesized complexes was confirmed. Cytotoxicity assays demonstrated that most of the complexes exhibited notable anticancer potency against A549, HeLa and cisplatin-resistant A549/DDP cancer cells. Mechanistic studies suggested a redox-driven pathway involving the catalytic oxidation of NADH to NAD+, the elevation of ROS levels and depolarization of the mitochondrial membrane. Notably, pyridyl-amine complexes induced apoptosis, while 16-electron pyridyl-amido complexes did not, though both caused S phase cell cycle arrest. Additionally these complexes can inhibit A549 cell migration, suggesting their potential to reduce cancer metastasis. Show less

Title: Ruthenium(II) and copper(II) polyamine complexes as promising antitumor agents: synthesis, characterization, and biological evaluation. Abstract: Ruthenium or copper complexes have emerged as some of the most promising alternatives for the treatment of many types of cancer. They have enhanced activity, greater selectivity and reduced side effects compared to their predecessors, cisplatin and its analogues. On the other hand, polyamine metabolism is often deregulated in cancer, leading to increased intracellular concentrations of polyamines that promote cell proliferation, differentiation, and tumorigenesis. In the present work, we report the synthesis and characterization of a family of mono- and binuclear Ru(II) and Cu(II) complexes functionalized with polyamine ligands derived from norspermine. The computer-aided analysis of the electron paramagnetic resonance (EPR) spectra provided magnetic and dynamic parameters, which helped to identify prevalent Cu-N2 coordination in a partially distorted square planar geometry of the Cu(II) complexes and the flexibility of the complexes in solution, slowed down by both the complex size and the hydrophobic interactions between chains. In vitro studies focused on advanced prostate cancer have demonstrated that these new metal complexes present a high level of cytotoxicity against PC3 cells. Furthermore, these metallic compounds exhibit the ability to inhibit cell adhesion and migration while reducing intracellular reactive oxygen species levels, which are key factors of metastasis. Show less

The clinical success of metal-based anticancer agents can be achieved by developing not only an efficient metallodrug but also a suitable drug delivery system (DDS). Although spatiotemporal delivery, enhancing the efficacy, and alleviating toxicity are achievable, modifying the mechanism of action of metallodrugs using a nano DDS remains scarce. With all this in mind, a series of cyclometalated ruthenium(II) half-sandwich complexes of the type [(η⁶-p-cymene)Ru(L)Cl] Ru(1)-Ru(4), where L is 2-phenylquinoline (L1), 2-(thiophen-2-yl)quinoline (L2), 4-methyl-2-phenylquinoline (L3), or 2,4-diphenylquinoline (L4), have been isolated and characterized by analytical and spectroscopic methods. Ru(1) and Ru(2) have been structurally characterized, and their coordination geometries around the ruthenium(II) are described as pseudo-octahedral geometry. Only the Ru(1) complex, which exhibited substantial cytotoxicity in non-cancerous cells and low cytotoxicity in breast cancer cells, is encapsulated into a hybrid nanosystem comprising phospholipid and polydiacetylene. The Ru(1)-entrapped nanoassembly (PDL-Ru(1)) is found to show pH-induced emission and higher release of the complex in a simulated tumor environment than in a physiological environment. Even though such a halochromic character failed to benefit cell imaging, the nanocarrier-mediated delivery has been proven to improve the cytotoxicity of Ru(1) in breast cancer cells, modulate the mode of cell death, and reduce toxicity in normal cells. Zebrafish embryo toxicity studies revealed that polydiacetylene-lipid nanoassembly could be useful for in vivo biocompatibility applications of ruthenodrug candidates. Show less

We introduce ruthenosomes, a fusion of liposomal and reactive oxygen species (ROS)-generating properties meticulously engineered as potent ferroptosis inducers (FINs), marking a significant advancement in metallodrug design for cancer therapy. Formed through the self-assembly of oleate-conjugated ruthenium complexes, these ruthenosomes exhibit exceptional cellular uptake, selectively accumulating in mitochondria and causing substantial disruption. This targeted mitochondrial damage significantly elevates ROS levels, triggering autophagy and selectively activating ferritinophagy. Together, these processes sensitize cancer cells to ferroptosis. In vivo, ruthenosomes effectively suppress colorectal tumor growth, underscoring their therapeutic potential. Our study pioneers a design strategy that transforms ruthenium complexes into liposome-like structures capable of inducing ferroptosis independent of light activation. By leveraging ruthenosomes as multifunctional nanocarriers, this research offers a versatile and powerful platform for ROS-mediated, ferroptosis-driven cancer cell eradication. Show less

Ferroptosis is a unique cell death mode that relies on iron and lipid peroxidation (LPO) and is extensively utilized to treat drug-resistant tumor. However, like the other antitumor model, requirement of oxygen limited its application in treating the malignant tumors in anaerobic environments, just as photodynamic therapy, a very promising anticancer therapy. Here, we show that an iridium(III) complex (Ir-dF), which was often used in proton-coupled electron transport (PCET) process, can induce efficient cell death upon photo irradiation, which can be effectively protected by the typical ferroptosis inhibitor Fer-1 but not by the classic iron chelating agents and ROS scavengers. Surprisingly, LPO was further demonstrated to be directly induced by Ir-dF/light activation via PCET, by utilizing a model polyunsaturated fatty acid. Ir-dF was found to be accumulated preferentially in mitochondria and the endoplasmic reticulum (ER), leading to mitochondrial swelling and ER stress accompanied by obvious LPO accumulation and downregulation of the characteristic ferroptosis protein GPX4. More interestingly, Ir-dF was also found to induce photocytotoxicity under hypoxia, and an in vivo experiment further confirmed that Ir-dF can effectively inhibit the growth of tumor under two-photon laser irradiation. Taken together, for the first time, this article introduces a new mechanism of inducing the LPO through a photoactivated PCET process, leading to a ferroptosis-like cell death which is independent of the iron and oxygen. This innovative mechanism holds great potential as a future treatment option for hypoxic malignant tumors and drug-resistant tumors. Show less

S: Mercury ions (Hg²⁺) are highly toxic and prone to bioaccumulation, showing a strong attraction to proteins and enzymes that contain sulfur. Even minute quantities of Hg²⁺ can lead to severe health issues. Given that mitochondria are a primary target organelle of Hg²⁺, it is essential to create a probe that can accurately detect Hg²⁺ within intracellular mitochondria. In this study, we developed two innovative Ir(III) complex probes that emit near-infrared light. The crystal structure of Ir2 was determined using X-ray techniques, which reveals that Ir2 contains a pyridine group capable of recognizing Hg²⁺ and targeting mitochondria, allowing for the precise identification of Hg²⁺ both in vitro and within the mitochondria of living cells. Additionally, these two novel near-infrared phosphorescent Ir(III) complexes demonstrate significant capabilities in producing ROS including singlet oxygen, ·O₂^- and ·OH, which renders them effective photosensitizers under visible light exposure for photodynamic therapy (PDT). This research offers a promising approach for detecting Hg²⁺ in vitro and in the mitochondrial microenvironment of living cells, which have some implications for the future development of pertinent transition metal complexes for mitochondria-targeted photodynamic therapy in cancer cells. Show less

A novel bioorganometallic PNA conjugate (Ir-PNA) was synthesized by covalently bonding a model PNA tetramer to a luminescent bis-cyclometalated Ir(III) complex that acted as a photosensitizer under light irradiation to generate singlet oxygen (¹O₂). The conjugate was prepared using an Ir complex bearing the 1,10-phenanthroline ligand functionalized with either a free primary amine (Ir-NH₂) or a carboxyl group (Ir-COOH) for the conjugation to PNA. The photophysical studies on the Ir-COOH and the Ir-PNA demonstrated that the luminescent properties were maintained after the conjugation of the Ir fragment to PNA. Furthermore, the abilities to produce ¹O₂ of Ir-COOH and Ir-PNA were confirmed in a cuvette under visible light irradiation employing 1,5-dihydroxynaphthalene as a reporter, and the measured singlet oxygen quantum yield (Φ_Δ) supported the Ir-PNA conjugate efficacy as a photosensitizer (Φ_Δ = 0.54). Two-photon absorption microscopy on HeLa cells revealed that Ir-PNA localized in both the cytosol and nucleus, suggesting its potential as an intracellular carrier for PNA. Cytotoxicity assays by MTT tests showed that Ir-PNA was nontoxic in the absence of light, but induced cell death (EC₅₀ = 18 μM) after UV irradiation. Overall, the Ir-PNA conjugate represents a promising system for the intracellular delivery of the PNA and its application in PDT. Show less

A series of iridium(iii) complexes (Ir1-Ir3) with the formula [Ir(F₂ppy)₂(L)] (F₂ppy = 2-(2,4-difluoro-phenyl)pyridine, L = pyridine-2-aldoxime, 2-pyridylamidoxime and di-2-pyridylketoxime) were synthesized through the reaction of [(F₂ppy)₂Ir(μ-Cl)₂Ir(F₂ppy)₂] (SM1) and the respective ancillary ligands (L). All the complexes were characterised by FT-IR, ¹H & ¹⁹F-NMR analysis, electronic absorption-emission spectroscopy and cyclic voltammetric studies. Molecular structures of complexes Ir1 and Ir3 were determined by interpreting single crystal X-ray data. All the complexes were found to be luminescent with low quantum yields. Anticancer studies on cancer cell lines MDAMB, HT-29 and LN-229 revealed their effectiveness as antiproliferative agents. The cytotoxicity of the complexes was evaluated using the MTT assay and complex Ir2 showed activity similar to that of cisplatin towards the three cancer cells. The elevated level of reactive oxygen species (ROS) in the iridium complex-treated cancer cells further supported the antiproliferation efficacy of Ir1-Ir3. Further, the effectiveness of Ir1-Ir3 on cancer cells was established through a cell migration study and apoptotic induction assay on LN-229 and a colony formation assay on HT-29 cancer cells. Immunocytochemistry analysis of LN-229 cancer cells revealed apoptosis through the p53-dependent pathway. Show less

Title: Monomer Versus Dimer of Cationic Ir(III) Complexes for Photodynamic Therapy by Two-Photon Activation: A Comparative Study. Abstract: Iridium(III) complexes have been recognized as promising candidates for two-photon sensitized photodynamic therapy (PDT). In this context, we report on the study of two complexes: a monomer (IrL1) and a dimer (Ir2L2). Both complexes possess 2-phenylpyridine cyclometallating ligands and a pyridylbenzimidazole derivative as an ancillary ligand. In the dimer, the two Ir(III) centers are connected by a non-conjugated bridged bis(pyridylbenzimidazole). We compare the photophysical properties of these complexes. Both display phosphorescent emission in the orange-red part of the visible spectrum, with emissions centered at 610 nm for IrL1 and 625 nm for Ir2L2, both exhibiting quantum yields of ∼24%. However, Ir2L2 proves to be much brighter than the monomer, making the dimer four times brighter than IrL1. This trend is consistent under two-photon excitation (TPE), and the singlet oxygen generation quantum yields, with the dimer displaying a figure of merit (σTPA × ΦΔ) of 40, compared to only 5 for the monomer. Both complexes generate intracellular ROS and exhibit strong phototoxicity upon blue light activation (λ = 420 nm), achieving submicromolar IC50 values in HT29 and A549 cell lines after 24 h of incubation. Moreover, with TPE (λ = 800 nm), both complexes also generate intracellular ROS and induce cancer cell death. Show less