搜索结果：Current drug targets

Mutation-induced drug resistance challenges both pandemic surveillance and drug discovery. While experimental assays are resource-intensive, current computational predictions remain limited by the scarcity of 3D mutant protein structures. We present DeepMutDTA, a structure-independent model pre-trained on 1.5 million data points to predict drug-target affinity and uncover underlying interaction mechanisms. However, like other sequence-based approaches, it often falls short in predicting mutant affinities due to the overwhelming sequence similarity between wild-type (WT) and mutant (MT) targets. To bridge this gap, we introduce SimSiam-MuTF, a novel fine-tuning framework to enhance the detection of resistance variants by explicitly aligning latent embedding distances with the corresponding shifts in binding affinity between WT and MT targets. Compared to representative baselines, our model exhibits remarkable robustness across varied sequence identities and unseen data splits, yielding average performance gains of 2.47% (PCC) and 5.10% (SCC) in regression tasks, alongside 4.00% (AUC) and 4.17% (AUPR) in classification tasks. Applications to SARS-CoV-2, HIV-1, and cancer-related targets highlight its generalization potential and utility in informing therapeutic strategies against drug resistance. Collectively, this robust computational pipeline and fine-tuning framework deepen our understanding of mutation-induced resistance and may serve as a powerful platform to accelerate drug discovery against mutant targets.

Our study aims to explore the early genomic diagnostic markers of OSA and the corresponding drug prediction targets using network pharmacology analysis, and to elucidate the etiology and pathogenesis of OSA from the genetic level. We selected OSA-related gene datasets (GSE135917 and GSE38792) from the Gene Expression Omnibus (GEO). Principal component analysis (PCA) was performed to remove outlier samples, and batch correction was applied to the two datasets. The raw expression matrix was log2-transformed, and samples were divided into normal and OSA groups. Differentially expressed genes (DEGs) were identified, and WGCNA analysis was performed on these DEGs to identify mitochondria-associated hub genes, followed by functional enrichment analysis, PPI network construction, core lncRNA-related ceRNA network construction. We then screened core genes with a high risk of OSA. Based on the core genes, we established an easy-to-use nomogram and verified its accuracy in identifying OSA patients then performed a differential expression analysis of the core genes, GSEA and GSVA analyses, and immune infiltration analysis. Finally, we constructed the disease prediction model and predicted the drug targets, thereby obtain a genomic prediction model for OSA. After PCA and batch correction, an expression matrix comprising 13 normal samples and 19 OSA patient samples was finally included. We identified 1500 differentially expressed genes (DEGs) through differential expression analysis, then screened 61 hub genes by WGCNA analysis, and established an OSA-associated ceRNA network containing 75 predictive miRNAs, 129 lncRNAs and 5 mRNAs. Six robust key genes were identified through PPI network construction: TUFM, CYCS, UQCRC1, COX4I1, TIMM50, and NDUFV1. Finally, after LASSO regression and nomogram validation, a predictive model containing 2 core genes (UQCRC1 and COX4I1) was obtained, and its area under the ROC curve (AUC) was 0.919. Drug target prediction of the core genes showed that 1-Methyl-4-phenyl-2,3-dihydropyridinium CTD 00002003, Cube root extract CTD 00006707, Disodium selenite CTD 00007229, and mitotane CTD 00006344 had good effects. Our current findings provide a rationale for identifying therapeutic targets in the diagnosis and treatment of OSA. In addition, these findings have the potential to facilitate the translation of our study to clinical applications in the future. Insight Box Different from other single-gene predictors of OSA, network pharmacological analysis identified differential genes and explored biomolecular markers of OSA from multi-gene and multi-target perspectives through enrichment analysis, construction of ceRNA gene network, and correlation analysis and explore early genomic diagnostic indicators of OSA and corresponding drug prediction targets using network pharmacological analysis and to elucidate the etiology and pathogenesis of OSA from the genetic level. To provide a more accurate method for the diagnosis, prevention, and treatment of clinical OSA, it is expected to provide a research basis for the accurate diagnosis of clinical OSA and the pathogenesis of OSA.

Nanoparticle-based drug delivery has emerged as a transformative approach in modern therapeutics, offering improved targeting efficiency, enhanced pharmacokinetics, and reduced systemic toxicity compared to conventional drug delivery systems. This review comprehensively examines major nanocarrier platforms, including lipid-based, polymeric, inorganic, and hybrid systems, with emphasis on their structural design and functional properties. It further explores current advancements in targeting strategies, including passive targeting via the enhanced permeability and retention (EPR) effect and active targeting through ligand-receptor interactions involving antibodies, peptides, aptamers, and small molecules. Key biological and technological barriers to clinical translation are also discussed, such as tumor heterogeneity, abnormal vasculature, dense extracellular matrix, immune clearance, and limited cellular uptake. Additionally, emerging stimuli-responsive systems, including pH-, redox-, and enzyme-sensitive nanocarriers, are highlighted for their role in controlled and site-specific drug release. Despite significant progress, the clinical translation of nanomedicine remains constrained by biological complexities and scalability challenges. Future advancements integrating biomimetic strategies, multifunctional design, and artificial intelligence-driven modeling are expected to enhance targeting precision, biocompatibility, and translational success. A lot of drugs fail to reach the area where they are most needed. Rather, they percolate throughout the body, which can diminish the effectiveness of the treatment and lead to side effects. To solve the problem, researchers have tried to create tiny medicine carriers known as nanoparticles that carry medicines more accurately to diseased tissues.In this review, the mechanism of design of nanoparticles and their size, shape, surface properties, and composition will be explained, which affect their ability to carry drugs and interact with the body. A variety of nanoparticles, such as lipid-based, polymer-based, inorganic, and hybrid, are reviewed, and their pros and cons are summarized.Also discussed are strategies for delivering nanoparticles to specific targets, including the delivery of nanoparticles to tumors without exposing healthy tissues. These methods involve passive targeting, active targeting with the help of certain molecules that bind to diseased cells, and stimuli-responsive systems that release drugs when certain stimuli are present.Nanomedicine drug delivery has been demonstrated in laboratory and clinical trials to be a promising approach, but there are several challenges associated with it. These include biological barriers in the body, manufacturing complexity, safety issues, regulatory requirements, patient responses, and more.In conclusion, NP-DD systems could enhance the efficacy and safety of many therapies. Further research and development in nanotechnology, biology, and pharmaceuticals are likely to help advance the development of more targeted and customized treatments in the future.

Radionuclide drug conjugates (RDCs) are emerging molecular platforms for diagnostic imaging, targeted radionuclide therapy, and precision-oncology theranostics. Theranostic applications typically employ matched diagnostic and therapeutic radionuclides conjugated to the same or closely related targeting scaffolds. An RDC generally comprises a targeting ligand, a linker, a chelator, and a radionuclide, thereby enabling selective tumor targeting for either diagnostic imaging or targeted radiotherapy depending on the conjugated radionuclide. This review summarizes recent advances in RDC design, with particular emphasis on radionuclide selection, linker chemistry, and ligand-engineering strategies. Clinically relevant molecular targets, including prostate-specific membrane antigen (PSMA), somatostatin receptors (SSTRs), cholecystokinin-2 receptor (CCK2R), gastrin-releasing peptide receptor (GRPR), and fibroblast activation protein (FAP), are discussed alongside representative diagnostic, therapeutic, and theranostic platforms. These platforms include 68Ga/177Lu-PSMA systems, 68Ga/177Lu-DOTATATE or OPS202/OPS201 pairs, 68Ga/177Lu-NeoBOMB1, and 18F/177Lu-fibroblast activation protein inhibitor (FAPI) systems. Despite their potential to improve patient stratification and therapeutic efficacy while reducing systemic toxicity, RDCs face substantial challenges, including tumor heterogeneity, radiochemical instability, renal toxicity, and constraints on the large-scale production of radionuclides. Future advances will depend on the development of multitargeting strategies, novel radionuclides, and artificial intelligence (AI)-assisted rational design.

Drug-resistant epilepsy (DRE) affects approximately one-third of patients with epilepsy and represents a major unmet clinical need. While traditional hypotheses of pharmacoresistance have focused on alterations in drug targets, efflux transporter overexpression, and intrinsic disease severity, the gut microbiome has recently emerged as a potentially modifiable factor that may function as a systems-level modifier of these established mechanisms rather than a standalone pathway. The gut microbiome harbors a vast repertoire of drug-metabolizing enzymes capable of directly biotransforming orally administered antiseizure medications (ASMs)-including valproic acid, lamotrigine, carbamazepine, and oxcarbazepine-thereby altering their pharmacokinetics, bioavailability, and therapeutic efficacy. Additionally, microbial metabolites modulate host cytochrome P450 enzymes, nuclear receptors, and efflux transporters such as P-glycoprotein, while bacterial β-glucuronidases influence the enterohepatic recirculation of glucuronidated ASMs. Conversely, chronic ASM exposure reshapes the gut microbial ecosystem, creating a self-perpetuating cycle of dysbiosis and pharmacoresistance. This narrative review synthesizes current evidence on microbiome-ASM interactions in DRE, proposes a concrete experimental pipeline for characterizing ASM-specific microbial biotransformation, and outlines a framework for integrating physiologically based pharmacokinetic modeling with microbiome data. We discuss clinical implications for epileptologists-including the role of therapeutic drug monitoring in detecting microbiome-mediated pharmacokinetic variability, the concept of microbiome-neutral ASM selection, and earlier deployment of the ketogenic diet as a microbiome-targeted intervention. We highlight the translational potential of pharmacomicrobiomics-the study of how microbiome variation influences drug disposition and response-and identify critical knowledge gaps that warrant future investigation. PLAIN LANGUAGE SUMMARY: About one in three people with epilepsy continue to have seizures despite treatment. This review summarizes growing evidence that the gut microbiome-the community of bacteria living in the intestines-can influence how seizure medications work by altering their absorption, metabolism, and clearance. The medications themselves can reshape the microbiome in return, creating a cycle that may sustain treatment failure. Understanding this gut-drug relationship may open new paths to personalized epilepsy care through diet, probiotics, and microbiome-guided prescribing.

Mycobacterium tuberculosis remains the leading cause of death from a single infectious pathogen globally despite decades of effective chemotherapy. In 2024, an estimated 10·7 million people developed tuberculosis, including approximately 620 000 people living with HIV (PLHIV), and tuberculosis caused an estimated 1·23 million deaths overall, including approximately 150 000 deaths among PLHIV. Men accounted for more than half of the cases, and children represented a substantial burden, reflecting ongoing transmission and diagnostic gaps. Approximately a quarter of the world's population has been infected with M tuberculosis, with immunological evidence of previous or current infection. This population includes groups at increased risk of progression to tuberculosis disease, particularly those with recent infection, HIV, undernutrition, young age, or other clinical and social vulnerabilities. Following 3 years of COVID-19-related setbacks, global tuberculosis incidence declined modestly (1%) from 2023 to 2024 but remains higher than in 2020 and far off-track to meet the 2025 WHO End TB Strategy milestones. Case detection improved to 8·3 million notifications (78% of estimated incident cases), supported by expanded molecular diagnostics; however, prevalence surveys continue to reveal substantial proportions of bacteriologically confirmed but asymptomatic tuberculosis, highlighting persistent transmission and missed diagnoses. 30 high-burden countries accounted for 87% of cases, led by India, Indonesia, the Philippines, China, Pakistan, Nigeria, the Democratic Republic of the Congo, and Bangladesh. M tuberculosis-HIV co-infection remains a major driver of mortality in sub-Saharan Africa. Drug-resistant tuberculosis threatens progress: of 390 000 estimated multidrug-resistant or rifampicin-resistant tuberculosis cases in 2024, only 42% initiated treatment, although treatment success improved to 71%. Tuberculosis-preventive treatment reached 5·3 million people, including 58% of PLHIV and 25% of eligible household contacts, well below global targets. Persistent undernutrition, poverty, HIV, diabetes, smoking, alcohol use, air pollution, migration, and conflict continue to shape tuberculosis epidemiology. With financing at only 27% of global targets, accelerated prevention, proactive case finding, social protection, and sustained political commitment are essential to eliminate tuberculosis.

Colorectal cancer (CRC) is a highly prevalent gastrointestinal malignancy worldwide, characterised by insidious onset, rapid progression, high tendency for recurrence and metastasis, and resistance to chemotherapy. It poses significant challenges for clinical management and has become a major public health issue threatening human health. Current clinical treatments for CRC remain significantly limited. Traditional chemotherapeutic agents exhibit poor selectivity and pronounced toxic side effects, and long-term use readily induces tumour resistance, resulting in suboptimal therapeutic outcomes. Consequently, the identification of highly effective and safe core therapeutic targets and novel intervention strategies holds significant clinical value. The Nrf2 signalling axis is a core pathway regulating the body's redox homeostasis, inflammatory responses, and the biological behaviour of tumour cells. Abnormal activation of this pathway can drive the proliferation, invasion, and metastasis of CRC cells, inhibit tumour cell apoptosis, and simultaneously mediate the development of chemotherapy resistance, making it a key molecular target involved in the onset and progression of CRC. Due to their widespread sources, structural diversity, low toxicity, and unique ability to exert synergistic regulation across multiple targets and pathways, natural products represent a vital resource for the development of novel anticancer drugs. A substantial body of research has demonstrated that various bioactive natural products can modulate the mode of cell death in CRC cells, inhibit malignant progression, reverse drug-resistant phenotypes, and improve the tumour immune microenvironment by specifically regulating Nrf2 and the expression of its downstream target genes. This article elucidates the core regulatory mechanisms of the Nrf2 signalling axis in the progression of CRC and summarises the anti-CRC effects and molecular mechanisms of various natural products that target this pathway. It analyses the application advantages and translational bottlenecks of natural products, providing a theoretical basis and new research insights for the development of novel natural anti-CRC drugs and the optimisation of clinical combination therapy regimens.

Non-small cell lung cancer (NSCLC) constitutes approximately 85% of all lung cancer cases and remains a major clinical challenge with a poor overall prognosis. Molecular targeted therapy has thus emerged as a cornerstone of its treatment. This review summarizes the research progress of advances in small-molecule targeted agents against major driver oncogenes in NSCLC, including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), and Kirsten rat sarcoma viral oncogene homolog (KRAS). We elaborate on the mechanism of action, clinical efficacy and treatment-related adverse events (TRAEs) of each generation of inhibitors, while updating the developmental status of innovative therapies and emerging. Notably, this article further integrates clinical data of investigational small-molecule targeted drugs that address emerging oncogenic drivers such as rat sarcoma viral oncogene homolog (RAS), human epidermal growth factor receptor 2 (HER2), and v-src avian sarcoma viral oncogene homolog (SRC), which have demonstrated promising clinical activity in early-phase trials. These findings highlight potential avenues for future development of NSCLC-targeted therapies. Despite iterative optimization across multiple generations, current targeted drugs for NSCLC still face prominent limitations, including acquired drug resistance and insufficient penetration across the blood-brain barrier (BBB). Moving forward, future research should prioritize accelerating the clinical translation of investigational drugs, exploring combination treatment regimens, identifying novel molecular targets, and optimizing the overall system of molecular targeted therapy. These efforts will help further improve clinical outcomes for patients with NSCLC.

Accurate prediction of drug-target binding affinity (DTA) is a key task in virtual screening. However, current computational methods face a key challenge: sequence-based approaches often fail to capture critical spatial information, while structure-based models rely on computationally expensive 3D coordinates, which restrict their scalability. To address this issue, we propose StructuraDTA, a novel multimodal framework that adopts an implicit structure modeling strategy. Instead of using static protein folding data, our method encodes drug molecular graphs via Graph Isomorphism Networks (GINs) to capture fine-grained topological features. Meanwhile, we optimize protein representations by integrating probabilistic structural priors into a pretrained language model, which effectively simulates thermodynamic conformational flexibility without relying on explicit 3D structural data. A bidirectional cross-attention mechanism is then used to dynamically align these heterogeneous feature modalities. Comprehensive evaluations on the Davis and KIBA benchmark datasets show that StructuraDTA stably outperforms state of-the-art comparison methods. Importantly, the model exhibits strong robustness in cold-start scenarios, and can accurately predict binding affinities for previously unseen drugs and targets. By retaining the predictive performance of structure based models while maintaining the high inference efficiency of sequence-based methods, we provide an accurate and scalable solution to accelerate genome-scale drug discovery research.

Escherichia coli (E. coli) is an important pathogen responsible for foodborne disease outbreaks and can be transmitted through the food chain via the fecal-oral route, causing both intestinal and extraintestinal infections in warm-blooded animals. Against the backdrop of improper use of antibiotics in medicine, agriculture, and animal husbandry, together with the adaptive evolutionary capacity of E. coli, the increasing detection rate of multidrug-resistant E. coli and the shifting of dominant clones among regions have posed a great challenge to the treatment and control of infections. Against this background, this comprehensive narrative review takes the molecular epidemiological characteristics of E. coli as an entry point to systematically summarize its biological features and epidemiological patterns and then explains the mechanisms of antibiotic resistance from the molecular level, including intrinsic resistance conferred by its inherent structural features, acquired resistance (acquisition of drug resistance genes, alteration of drug targets, production of target protection proteins, enzymatic modification and inactivation of antibiotics, changes in cell membrane permeability, and upregulation of active efflux pump systems) and biofilm-mediated adaptive resistance. Finally, this review summarizes current antibiotic treatment strategies and emerging therapeutic approaches for E. coli infections. Within a One Health framework, this review highlights the resistance characteristics and transmission dynamics of E. coli to inform prevention strategies and antimicrobial development.

Antimicrobial resistance (AMR) has diminished the effectiveness of present antibiotics, posing a huge threat to global community health and economic stability. This study investigates the CRISPR-Cas framework's potential as a cutting-edge tactic to fight antimicrobial resistance. Current applications, limitations, and prospective future uses are analyzed. CRISPR antimicrobial strategies, which bring together the latest developments in gene-targeting strategies, engineered delivery platforms, and translational applications to fight multidrug-resistant pathogens. CRISPR technology is different from traditional antimicrobial treatments that target general antimicrobial resistance genes, instead allowing targets to be eliminated specifically by sequence, while retaining beneficial microbial communities, which has the potential to be a transformative precision antimicrobial treatment. Nevertheless, there is still a need for optimization of delivery systems, specificity of targets, biosafety, and regulations to ensure successful clinical translation, especially given their amazing advances. Recent research confirms that CRISPR-based mechanisms also affect different bacterial species, including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species, playing a key function in averting the emergence of resistance genes in these bacteria. Changes to CRISPR loci affect how resistance genes are targeted in ESKAPE pathogens, and CRISPR-Cas9 successfully lowers resistance by focusing on genes like tetM and ermB. A promising application of CRISPR-Cas systems in combating antimicrobial resistance (AMR) is the precise targeting of plasmid-borne mcr-1 resistance genes and other mobile genetic elements that facilitate the dissemination of colistin resistance. But the efficiency of CRISPR-Cas is diminished in some bacterial strains due to variations in their CRISPR loci. Enhancing transformation approaches and minimizing off-target impacts are critical challenges to confirm the precision and safety of CRISPR-based mechanisms in therapeutic applications. Advances in these areas are likely to continue to enable the development of next-generation CRISPR therapeutics for the effective management of multidrug-resistant bacterial infections.

Therapy resistance and relapse remain major obstacles in the treatment of lymphoid malignancies. While the cancer stem cell (CSC) hypothesis has long served as a conceptual framework for understanding chemoresistance, evidence for its direct applicability in lymphoid malignancies is still limited. More recently, drug-tolerant persister (DTP) cells have emerged as an important model for exploring resistance mechanisms, offering complementary perspectives beyond the CSC paradigm. In this review, we summarize recent advances in the study of DTP cells in lymphoid malignancies, including their progression to drug-tolerant expanded persister (DTEP) cells. We discuss experimental models and methodological approaches for investigating DTP cells, as well as the underlying mechanisms of persistence and resistance, which encompass gene-regulatory changes, cell surface remodeling, and immune evasion strategies. Finally, we highlight potential therapeutic avenues such as targeting glycosylation-related pathways, exploiting immunotherapeutic glycopeptide targets, and implementing rational combination regimens. By integrating insights from DTP biology, this review aims to broaden current theories to therapy resistance in lymphoid malignancies and inform the development of innovative treatment strategies.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global health challenge due to persistent diagnostic gaps. CRISPR-Cas-based diagnostics have emerged as highly sensitive and programmable platforms for nucleic acid detection, enabling rapid identification of Mtb targets, including drug-resistance-associated mutations. These systems integrate isothermal amplification, diverse Cas effectors, and multiple signal readout strategies to achieve high analytical performance. This review provides a comparative analysis of clinically evaluated CRISPR-based TB diagnostic platforms, highlighting substantial variability in assay design, performance, and translational readiness. While many platforms demonstrate strong analytical sensitivity, their implementation remains constrained by workflow complexity and limited integration into true point-of-care formats. This highlights that successful clinical translation of CRISPR-based TB diagnostics is determined more by real-world adaptability than by analytical performance alone. The current review presents a comparative analysis of CRISPR-based diagnostic platforms for tuberculosis, evaluating the variability in assay design, analytical and clinical performance, and translational readiness across currently available systems.

Many diseases, including cancer, are characterized by increased or decreased expression of specific genes. These changes can occur without genome alteration, primarily modulated by the addition or removal of epigenetic markers, which influence chromatin condensation and architecture. Genes in more condensed chromatin regions have lower expression and the opposite also applies. In the last twenty-two years, small molecule inhibitors of enzymes responsible for chromatin deacetylation or methylation have successfully moved from preclinical discovery to clinical therapy. This review explores the ten epigenetic drugs that have attained worldwide regulatory approval for human therapy: the DNA methyltransferase inhibitors azacitidine (2004) and decitabine (2006), the histone deacetylase inhibitors vorinostat (2006), romidepsin (2009), belinostat (2014), panobinostat (2015) tucidinostat (2015) and givinostat (2024), and the histone methyltransferase inhibitors tazemetostat (2020) and valemetostat (2022). The history and strategy of their discovery and development, their biological targets and mechanisms of action and their therapeutic use. In addition, current advancements and efforts, as well as future perspectives in the design and clinical approval of new epigenetic drugs are discussed.

Sickle cell disease (SCD) is an inherited hemolytic hemoglobinopathy characterized by chronic hemolysis, vaso-occlusive pain crises, and progressive organ damage. Hydroxyurea, often combined with analgesics, remains a mainstay therapy, but may provide insufficient relief during active disease episodes. Drug repurposing offers a practical alternative where de novo drug development is limited, providing faster and more cost-effective therapeutic options. Imatinib (Gleevec), a tyrosine kinase inhibitor primarily used for chronic myeloid leukemia, has gained attention as a potential repurposed therapy for SCD. This narrative review provides a theoretical framework for evaluating imatinib's potential applications in mitigating key pathophysiological processes in SCD. Examination of the molecular pathways shared between imatinib's targets and the pathogenesis of SCD has yielded mixed findings: some studies suggest imatinib may reduce hemolysis and alleviate pain crises, while others have not supported such benefits. Direct investigations of imatinib in the context of SCD are limited, yet available evidence has reported potentially valuable outcomes, including decreased hospitalization rates, shorter hospital durations, and reduced organ damage. Current evidence remains insufficient for definitive conclusions, underscoring the need for well-designed clinical and translational studies to clarify the feasibility of incorporating imatinib into SCD management. SUMMARY: Imatinib has actions on signaling pathways with potential clinical relevance to sickle cell disease, such as reduction of inflammation, vaso-occlusive crises, and opioid tolerance. Reports of use in patients with sickle cell disease suggest potential for reducing the frequency of vaso-occlusive crises.

Cancer metastasis contributes to the high mortality rate in patients and remains a significant challenge in treating solid malignancies. The limitations of current therapeutic interventions are underscored by the mere 5% survivorship of patients with metastatic disease. Since cancer stem cells (CSCs) are the major cause of metastatic spread, emerging therapeutic modalities specifically targeting CSCs present a lucrative approach to curtail metastatic disease. The literature demonstrating the promise of targeting CSCs to limit metastatic spread holds immense potential but remains scattered. This review provides concise knowledge of CSC targeting strategies and their impact on the metastatic burden in cancer patients. Current therapeutic strategies, early screening of cancer and reduction in smoking have drastically reduced the cancer-associated deaths by 34% in the US [1]. However, CSCs and therapy resistance pose major clinical challenges. Therefore, new way to address CSCs such as targeting stemness pathways, cellular plasticity and stress tolerance, nano theranostic approaches, the effect of phytochemicals and new radiotherapy technologies such as microbeam radiotherapy are being extensively studied. The detailed molecular studies on CSCs provide a platform for identifying factors intrinsic to cancer cells, host cells, and tumor microenvironment (TME) influencing stemness and overall metastasis. In addition to emerging anti-metastasis therapeutic modalities, the review provides information regarding exclusive targets and signalling molecules involved in metastasis. Simultaneous targeting of factors regulating CSCs and TME, along with standard of care therapies, proves a better strategy to tackle CSC heterogeneity and their adaptation for metastatic disease. Further approaches impacting CSCs offer a promising avenue for enhancing the effectiveness of cancer therapeutics and discovering new anti-metastatic drug candidates.

Triosephosphate isomerase (TIM) is a very efficient catalyst due to its precise dynamic architecture. Most of the structural, functional, and physicochemical information about TIM has been obtained from eukaryotic organisms. In this review, we summarize current knowledge regarding Bacterial TIMs (BacTIMs), a very diverse but underrepresented group of TIMs. We discuss reported examples linking BacTIMs to pathogenesis-related processes and its influence on cellular physiology, particularly in those characteristics that potentiate their role as pharmacological targets. Finally, we discuss how recent advances in artificial intelligence assisted-virtual screening and fragment-based drug may accelerate the development of selective BacTIM inhibitors against non-conserved regions in the oligomeric interface.

Small-molecule chemical probes are foundational to biomedical research as they enable interrogation of the function of individual proteins within biological systems. However, the utility of these tools is constrained by their limited coverage of the proteome. To overcome this limitation, chemogenomic sets, collections of molecules annotated for their activity against a range of biological targets, have emerged to expand the coverage and interrogation of the proteome by small molecules. Unlike traditional chemical probes, these sets leverage annotated polypharmacology to allow for identification of therapeutic vulnerabilities in phenotypic screening. The present review summarizes the current landscape of chemogenomic sets, including open-science initiatives and target-class-focused libraries, and proteome-wide collections developed by academic and industrial efforts. We highlight key applications of these sets in phenotypic screening, target identification, and computational modeling, demonstrating how these resources allow for target identification in disease-relevant pathways. We envision that the data generated by these sets will facilitate the use of machine learning to fuel early-stage drug discovery.

Sepsis is marked by high morbidity and mortality rates, representing a significant contributor to the global disease burden. However, due to an incomplete understanding of its pathological mechanisms, current treatments remain predominantly symptomatic and supportive, lacking effective targeted therapies. Recent advances in research have brought the role of free heme in sepsis progression into focus. Free heme is now recognized as a critical mediator of sepsis exacerbation, with its biological properties and pathological mechanisms both playing pivotal roles. This review synthesizes evidence from foundational studies and clinical investigations to elucidate how free heme aggravates sepsis through direct cytotoxic effects and interactions with regulated cell death pathways. Furthermore, based on these mechanisms, potential therapeutic targets are proposed, alongside a summary of promising pharmaceutical candidates currently under investigation.