Current Drug Targets[JOURNAL]
Sun
200 papers
Chronic Inflammation (A Silent Killer) - Molecular Mechanisms and Emerging Therapeutic Approaches.
Singh R, Monika, Mazumder R … +5 more , Mazumder A, Singh M, Majee C, Padhi S, Das S
Curr Drug Targets · 2026 May · PMID 42136241 · Publisher ↗
Chronic inflammation is a dysregulated and persistent immune response that underlies numerous serious health conditions, like heart problems, diabetes, nerve damage, cancer, or conditions where the body attacks itself. R...
Chronic inflammation is a dysregulated and persistent immune response that underlies numerous serious health conditions, like heart problems, diabetes, nerve damage, cancer, or conditions where the body attacks itself. Recently, scientists have gained a better understanding of how molecules such as cytokines and chemokines, along with dysregulated immune cells, contribute to excessive oxidative stress and impaired healing processes. New tools now help identify this condition as early as possible through biomarkers, advanced laboratory techniques, integrated data approaches, and smart sensors that track biological changes in real time. However, despite this knowledge, effective strategies for early prevention and long-term treatment remain limited. Daily habits, particularly anti-inflammatory dietary patterns, regular physical activity, and stress management, play a critical role in reducing the risk of disease. Emerging therapies, including inflammasome inhibitors, cytokine-targeted biologics, immunometabolic modulators, and specialized pro-resolving mediators, may restore immune homeostasis rather than merely suppressing symptoms. Additionally, microbiome-targeted interventions-such as probiotics, prebiotics, bacteriophage therapy, and fecal microbiota transplantation-are increasingly being recognized as potential strategies to modulate systemic inflammation. Daily habits, especially eating patterns that fight inflammation, walking regularly, or handling stress, are critically important for lowering the chances of illness. Chronic inflammation is a complex, multifactorial process; therefore, its effective management requires integrated efforts in basic research, therapeutic innovation, and population- level healthcare strategies. Innovations in personalized medicine, AI-based analytics, digital health technologies, and microbiome science are poised to significantly enhance diagnostic and therapeutic approaches. Sustained cross-disciplinary collaboration will be critical in mitigating the worldwide impact of chronic inflammatory disorders and improving long-term health outcomes.
Drug Repurposing in Lung Cancer (NSCLC): Dual CDK1/TOP2A Targeting by Sertraline and Enoxacin.
Kar M
Curr Drug Targets · 2026 May · PMID 42136240 · Publisher ↗
INTRODUCTION: Non-small cell lung cancer (NSCLC), encompassing lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), remains a global health challenge due to subtype-specific resistance. Targeting shared mo...
INTRODUCTION: Non-small cell lung cancer (NSCLC), encompassing lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), remains a global health challenge due to subtype-specific resistance. Targeting shared molecular machinery between these subtypes offers a strategic advantage to overcome histological differences and bypass signalling. METHODS: We employed an integrated in silico pipeline: transcriptomic analysis of GSE159857 validated against large-scale TCGA-LUAD and TCGA-LUSC cohorts, protein-protein interaction (PPI) network construction (STRING confidence ≥ 0.7), and ADMET filtering. Structure-based molecular docking was performed on CDK1 (PDB 5LQF) and TOP2A in both apo- (PDB 9BQB) and DNA-bound (PDB 4FM9) states to validate target engagement. RESULTS: A core set of 1105 commonly upregulated genes was identified. Topological analysis prioritised CDK1 (Degree 232) and TOP2A (Degree 219) as central hub proteins. Sertraline and Enoxacin exhibited potent binding affinities (-9.7 to -8.3 kcal/mol). Validation using the DNAbound TOP2A complex confirmed stable ternary interactions at the catalytic interface with affinities of -6.3 to -6.5 kcal/mol and a redocking RMSD < 2.0 Å. DISCUSSION: The predicted engagement is driven by polypharmacology and structural mimicry rather than functional serotonin signalling. This dual-inhibitory mechanism likely reconciles previously reported anti-neoplastic phenotypes like ROS formation and autophagy by acting as an upstream enzymatic blockade. CONCLUSION: This study identifies sertraline and enoxacin as high-priority, dual-target candidates, providing a robust structural rationale for their rapid clinical repositioning in NSCLC therapy.
(E)-Labda dial-Loaded Nanoparticles for Triple Negative Breast Cancer.
Munir A, Rizwan M, Janbey A
Curr Drug Targets · 2026 Apr · PMID 42003077 · Publisher ↗
INTRODUCTION: Triple-negative breast cancer (TNBC) is the most aggressive kind of breast cancer, with no hormone receptors and resistance to targeted therapy. Chemotherapy is the current standard; however, it is limited...
INTRODUCTION: Triple-negative breast cancer (TNBC) is the most aggressive kind of breast cancer, with no hormone receptors and resistance to targeted therapy. Chemotherapy is the current standard; however, it is limited by toxicity, poor response, and high recurrence, emphasising the need for innovative methods. METHODS: This study investigates the therapeutic potential of (E)-labda-8(17), 12-diene-15,16-dial ((E)-labda dial), a bioactive chemical found in Curcuma amada (mango ginger) that was formulated into nanoparticles to increase transport and effectiveness. Whole-genome sequencing of TNBC cell lines was used to detect protein-altering mutations, which were then assessed using molecular docking and dynamics simulations to assess (E)-labda dial interactions with key mutant proteins (BRCA1, BRCA2, BARD1, PALB2, TP53, CHEK2). Lipid-based nanoparticles (LNPs) and polymeric nanoparticles (PNPs) were developed and tested for drug encapsulation, release kinetics, and stability. MTT and other functional tests were used to assess cytotoxic effects, and in silico pharmacokinetic models were carried out to anticipate treatment results. RESULTS: Results showed that PNPs outperformed LNPs in terms of encapsulation efficiency, sustained drug release, and tumour inhibition. Docking investigations demonstrated that mutant CHEK2, BARD1, and PALB2 bind to (E)-labda dial more strongly, indicating that carcinogenic pathways may be disrupted. DISCUSSION: These data, taken together, emphasise the abilities of (E)-labda dial-loaded nanoparticles as a targeted treatment method for TNBC, with potential effectiveness and toxicity benefits over traditional chemotherapy. CONCLUSION: This work lays the basis for precision and personalised treatment for TNBC patients. However, future optimisation and clinical validation of these nanoparticles can be done in future to determine their translational potential for use in practice.
Review on Chalcone as Carbonic Anhydrase Inhibitors.
Suresh Kumar SS, Sudevan ST, Kumar S … +3 more , Maliyakkal N, K Pappachen L, Mathew B
Curr Drug Targets · 2026 Apr · PMID 41944105 · Publisher ↗
Over the last decade, research on Carbonic Anhydrases (CAs) has focused on designing and developing novel inhibitors that are specific to certain isoforms to prevent non-specific binding. Many studies have employed compu...
Over the last decade, research on Carbonic Anhydrases (CAs) has focused on designing and developing novel inhibitors that are specific to certain isoforms to prevent non-specific binding. Many studies have employed computer-assisted drug design to develop selective inhibitors, including non-zinc binding inhibitors. Discrimination of selectivity and bioavailability, along with decreased toxicity optimization, is still lacking. Understanding of isoform-specific structural variation and the lack of corresponding resistance mechanisms, as well as further studies on allosteric modulation and novel binding interactions, are needed. The aim of this review is to investigate the link between chalcone structures and CA inhibition and explore their potential as selective inhibitors. Structural modifications with diverse functional groups are thought to bridge gaps in the discovery of chalcone-based carbonic anhydrase inhibitors. The study emphasizes further exploration of the development of chalcone-based carbonic anhydrase inhibitors.
Molecular Glues for Undruggable Targets: Mechanisms, Clinical Applications, and AI-driven Design.
Chen Z, Meng W, Chen M … +2 more , Wang C, Shi M
Curr Drug Targets · 2026 Apr · PMID 41935369 · Publisher ↗
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Investigating Alternative Treatments for Dyslipidemia Using Bioactive Compounds Derived from Kiwifruit (Actinidia chinensis): A Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation Analysis.
Zamudio-Felix I, González-Becerra K, Martínez-Esquivias F … +4 more , Oviedo-Tapia OD, Alviz-Amador AA, Isiordia-Espinoza M, Guzmán-Flores JM
Curr Drug Targets · 2026 Mar · PMID 41930644 · Publisher ↗
INTRODUCTION: Kiwi has many bioactive compounds that may improve blood lipid levels and help treat dyslipidemia, but its molecular mechanism is not fully understood. This study explores these mechanisms using pharmacolog...
INTRODUCTION: Kiwi has many bioactive compounds that may improve blood lipid levels and help treat dyslipidemia, but its molecular mechanism is not fully understood. This study explores these mechanisms using pharmacological network analysis. METHODS: Bioactive compounds of kiwi were obtained from the IMPPAT website, and molecular targets were identified using Swiss Target Prediction and PharmMapper. Genes associated with dyslipidemia were searched in the DISGENET database. Subsequently, an enrichment analysis was conducted, and a protein-protein interaction network was constructed. Hub genes were identified. Subsequently, a molecular docking analysis was performed, followed by a molecular dynamics simulation. RESULTS: Six bioactive compounds in kiwifruit showed good oral bioavailability and drug-likeness. Thirty-five genes linked to dyslipidemia and kiwi's targets were identified. Enrichment analysis highlighted the PPAR signaling pathway, lipid metabolism, and atherosclerosis. Hub genes included ALB, PPARG, AKT1, MMP9, PPARA, HMGCR, GSK3B, NOS3, PPARD, ACE, JAK2, and DPP4, with their interactions verified by molecular docking. Interactions between JAK2, ACE, and bioactive compounds (quinic acid and citric acid) involved spontaneous binding. Molecular dynamics simulations assessed conformational stability, mobility, solvation, and compaction of top-scoring protein-compound complexes. DISCUSSION: Bioactive compounds in kiwifruit can modulate dyslipidemia via PPAR pathways, JAK2, and ACE, supported by docking analyses and simulations. They show therapeutic potential, pending experimental validation. CONCLUSION: Our findings suggest how kiwi affects dyslipidemia. In silico analysis is a first step in exploring food compounds like kiwi as potential alternative treatments.
Advances in Target Identification and Drug Development for Depression.
Hu K, Wang X, Yu W … +8 more , Liu Q, Cheng Y, Song Y, Liang L, Liu W, Zhang J, Chang S, Hu J
Curr Drug Targets · 2026 Mar · PMID 41930643 · Publisher ↗
Depression is a prevalent mental disorder that is devastating to mental health. The high prevalence and multifactorial nature of causation pose significant challenges for developing effective treatment strategies. This r...
Depression is a prevalent mental disorder that is devastating to mental health. The high prevalence and multifactorial nature of causation pose significant challenges for developing effective treatment strategies. This review provides a first approach survey of the epidemiological nature of depression. It then attempts to delineate the interrelated biological, psychological, and environmental factors that stimulate its pathogenesis. Both traditional and new clinical and basic research therapeutic targets that are taking center stage today are highlighted. A review of the evolution of different antidepressant drugs targeting these molecular targets is provided. Emphasis is placed on current developments in Quantitative Structure-Activity Relationship (QSAR) modeling. A detailed study of representative compounds shows critical structure-activity relationships useful for designing effective drugs. We also consider some of the murine models of depression that are not particularly new, their applicability, and their limitations across various research environments. A particular barrier that is highlighted as an issue in the delivery of new antidepressant agents is the Blood-Brain Barrier (BBB). Creative methods of enhancing penetration of the central nervous system are also discussed. In general, this review provides a rational and prospective review of mechanistic literature and treatment innovation in non-depression studies.
Systematic Identification and Characterization of Causal Risk Genes Implicated in Colorectal Cancer by Integrating GWAS, eQTL, and mQTL Data.
Xu S, Guo G, Gao J … +7 more , Fang Z, Chai L, Gao Y, Liu J, Wang J, Siqinbateer, Zhang L
Curr Drug Targets · 2026 Mar · PMID 41930642 · Publisher ↗
INTRODUCTION: Knowledge of the mechanisms through which common single-nucleotide polymorphisms (SNPs) modulate colorectal cancer (CRC) susceptibility is central to elucidating the molecular basis of this disease. Genome-...
INTRODUCTION: Knowledge of the mechanisms through which common single-nucleotide polymorphisms (SNPs) modulate colorectal cancer (CRC) susceptibility is central to elucidating the molecular basis of this disease. Genome-wide association studies (GWAS) reveal noncoding SNPs influencing CRC susceptibility, yet their functional mechanisms, particularly through gene expression dysregulation, DNA methylation alterations, and interactions with gut microbiota, remain uncharacterized. Through integrative analysis, systematically exploring the effects of genetic variations on gene expression heterogeneity, DNA methylation, and gut microbiome is expected to yield potential biomarkers for early diagnosis and intervention of CRC. METHODS: An integrative framework is developed to prioritize causal risk genes at CRC-associated GWAS loci, applying the SMR&HEIDI (Summary-data-based Mendelian randomization and heterogeneity in dependent instruments) and TSMR (Two-sample Mendelian Randomisation) methods. The findings were validated via gene expression and TF binding affinity. RESULTS: 10 tissue-specific gene-SNP pairs, 3 blood eQTL-gene pairs, 26 gene-CpG-SNP regulatory modules, and 39 microbiota-associated gene-SNP pairs are identified. A few potential regulatory influences on CRC development associated with genes and variants, such as POU5F1B and rs10797801, were identified. Moreover, the genetic variants disrupted TF binding affinity while only a few promoted the binding of transcription factors (TFs). DISCUSSION: The data integration enabled us to prioritize genes according to different regulatory mechanisms, such as gene expression and DNA methylation, and bridge the gap between statistical associations and biological functionality. CONCLUSION: Multi-omics integration reveals some causal risk genes and variants implicated in CRC. These findings offer novel insight into the molecular mechanisms underlying CRC susceptibility and provide valuable clues for diagnosis and therapeutic intervention strategies.
PTP1B Inhibitors for Type 2 Diabetes: From Natural Products, Synthetic Inhibitors, and Multi-Target Drug Design Strategies to Clinical Translation.
Joshi P, Mazumder A, Pentela B … +1 more , Debnath A
Curr Drug Targets · 2026 Mar · PMID 41918194 · Publisher ↗
INTRODUCTION: Type 2 Diabetes Mellitus (T2DM) still exists as a worldwide health problem, and the current therapeutic options have selectivity and bioavailability issues. Protein Tyrosine Phosphatase 1B (PTP1B) emerged a...
INTRODUCTION: Type 2 Diabetes Mellitus (T2DM) still exists as a worldwide health problem, and the current therapeutic options have selectivity and bioavailability issues. Protein Tyrosine Phosphatase 1B (PTP1B) emerged as an important therapeutic target for T2DM. METHODS: In this study, we analyzed all publications between 2021 and 2025 available in the Scopus database, and the search was limited to English-language articles that were also indexed in PubMed. The search strategy employed multiple keyword combinations, including "PTP1B" OR "Protein Tyrosine Phosphatase 1B" OR "PTPN1", combined with inhibitor, drug discovery, type 2 diabetes, insulin resistance, and structural biology terms. RESULTS: Natural products from plant, marine, and microbial sources demonstrate diverse PTP1B inhibitory mechanisms through their active compounds, which include terpenoids, flavonoids, alkaloids, and diarylheptanoids. The development of synthetic approaches that combine thiazole derivatives with coumarin-based compounds and peptide inhibitors has produced promising scaffolds. The researchers used computational methods to find new allosteric binding sites through molecular docking and molecular dynamics simulations. The four clinical candidates Ertirprotafib, Trodusquemine, ISIS-113715, and JTT-551 all failed because their selectivity and efficacy were insufficient, but the dual PTPN2/PTPN1 inhibitor ABBV-CLS-484 shows oncology treatment potential. DISCUSSION: Beyond diabetes, PTP1B inhibition shows medical value for cancer immunotherapy treatment, together with neurodegenerative disorders, inflammation, and cardiovascular diseases. The development of PROTAC degraders, glycosylation-lipidation modifications, and multi-target inhibitors represents a new approach to solving past problems. CONCLUSION: The development of PTP1B inhibitors requires integrated approaches that include allosteric modulation, tissue-specific delivery, and patient stratification to achieve successful clinical translation across multiple disease indications.
Beyond AlphaFold: Charting the Future of AI in Protein Structure Prediction.
Kumar A, Kaur R, Bhatia R
Curr Drug Targets · 2026 Mar · PMID 41879448 · Publisher ↗
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Robust Association of Breast Cancer Co-morbidity Using Subtype-specific Expressed Genes.
Gupta M, Verma S, Rao S … +1 more , Kumar R
Curr Drug Targets · 2026 Mar · PMID 41879447 · Publisher ↗
INTRODUCTION: Breast cancer is a heterogeneous disease characterized by complex genetic and molecular alterations that drive its progression and metastasis to distant organs. It frequently cooccurs with comorbid conditio...
INTRODUCTION: Breast cancer is a heterogeneous disease characterized by complex genetic and molecular alterations that drive its progression and metastasis to distant organs. It frequently cooccurs with comorbid conditions, which complicates diagnosis, treatment planning, and overall prognosis. Understanding the genetic overlap between breast cancer and comorbid diseases is therefore critical for improving precision medicine approaches and clinical outcomes. METHODS: We performed a comprehensive comorbidity assessment for breast cancer using gene-level associations and identified 194 diseases strongly associated with the disease. Gene Ontology and pathway-based analyses were conducted to explore functional overlaps. In addition, differential gene expression profiles were analyzed across major breast cancer subtypes, Luminal, HER2-enriched, and Basal-like, to investigate subtype-specific molecular contributions to comorbidity and metastasis. RESULTS: We identified strong associations between breast cancer and several disease classes, including neoplastic, respiratory, digestive, cardiovascular, and musculoskeletal disorders. Distinct organspecific metastatic patterns were observed across subtypes: Basal-like tumors showed lung metastasis, HER2-enriched subtypes favored liver metastasis, and Luminal subtypes preferentially metastasized to bone. These metastatic patterns were supported by subtype-specific gene expression profiles, suggesting that key genes may drive both comorbidity and metastasis. DISCUSSION: The integration of gene expression and comorbidity profiling highlights the molecular mechanisms that link breast cancer progression with associated diseases. These findings provide valuable insights into how comorbid conditions may influence therapeutic responses and treatment planning. Subtype-specific metastasis further emphasizes the role of molecular drivers in determining clinical outcomes and offers an avenue for more tailored interventions. CONCLUSION: This study underscores the importance of comorbidity profiling in breast cancer. Our findings provide perspectives for developing personalized therapeutic strategies and may aid in improving clinical management and long-term outcomes for breast cancer patients.
Bee Venom and Cancer: A Mini-review Focusing on Melittin Antitumoral Effects.
de Oliveira AMB, Amparo TR, Sant'Anna MBM … +2 more , Picolo G, Almeida TC
Curr Drug Targets · 2026 Mar · PMID 41879446 · Publisher ↗
Cancer remains a major concern, accounting for one in six deaths globally. Developing effective treatments is challenging due to the complex mechanisms involving environmental, genetic, and epigenetic factors. Animal tox...
Cancer remains a major concern, accounting for one in six deaths globally. Developing effective treatments is challenging due to the complex mechanisms involving environmental, genetic, and epigenetic factors. Animal toxins have been utilized as pharmacological agents for treating several diseases. Among these compounds, melittin, derived from bee venom, exhibits significant therapeutic potential against cancer. This efficacy is attributed to its multifaceted nature, enabling it to function as a multi-target modulator of oncogenic signaling pathways and exert a broad spectrum of anticancer effects. In vitro studies have demonstrated that melittin treatment reduces cell viability, adhesion, clonogenic survival, migration, and invasion in various cancer cell types. Additionally, in vitro experiments have demonstrated that melittin induces apoptosis through multiple mechanisms, such as upregulating TNF-α and BAX, triggering ferroptosis, activating the mitochondrial pathway, initiating endoplasmic reticulum stress, and inhibiting METTL3. Furthermore, in vivo assays indicate that melittin reduces angiogenesis and tumor growth, enhances the effects of chemotherapy, and prolongs survival. The effects of melittin on the tumor microenvironment, modulation of the epigenetic process, and inhibition of the epithelial-mesenchymal transition have also been demonstrated. Overall, melittin shows potential as a therapeutic agent for breast, lung, gastric, cervical, colorectal, and bladder cancers by targeting multiple pathways involved in cancer progression. Moreover, other bee venom components, such as apamin and bee venom phospholipase A2, also exhibit potential anticancer effects. In this review, a comprehensive overview of the various actions of melittin and other components of bee venom on different types of cancer is provided. The research discusses their mechanisms of action and potential strategies to enhance efficacy and minimize toxicity.
E2 Protein of Chikungunya Virus: A Narrative Review of Its Potential as a Therapeutic Target.
Yaekashi KM, Carneiro JA, Martelossi-Cebinelli G … +6 more , Bertozzi MM, Ribas MSR, Zanluca C, Duarte Dos Santos CN, Casagrande R, Verri WA
Curr Drug Targets · 2026 Mar · PMID 41879445 · Publisher ↗
INTRODUCTION: Chikungunya Virus (CHIKV), an enveloped RNA virus transmitted by Aedes mosquitoes, has become an increasing global health concern, particularly in South America, where cases and fatalities have risen (PAHO,...
INTRODUCTION: Chikungunya Virus (CHIKV), an enveloped RNA virus transmitted by Aedes mosquitoes, has become an increasing global health concern, particularly in South America, where cases and fatalities have risen (PAHO, 2023). This review focuses on therapeutic strategies targeting the CHIKV E2 protein, including vaccines, antibodies, and antiviral approaches tested in vitro and in vivo. METHODS: Literature reporting on the E2 protein, including studies on viral structure, host interactions, symptoms, and treatments under development, was analyzed. RESULTS: The E2 protein, a major structural component of CHIKV, is critical for viral entry and virulence, mediating interactions with host factors (Glycosaminoglycans (GAGs) and C-type lectins) and receptors (Matrix Remodeling-Associated Protein 8 (Mxra8) and Prohibitin-1 (PHB1)). It also elicits robust antibody responses, making it a key target for therapeutic intervention. DISCUSSION: The E2 protein is essential for CHIKV entry and virulence, making it a key target for vaccines, antibodies, and antivirals. While preclinical studies show promise, efficacy varies and clinical translation remains limited. Challenges include viral diversity, immune escape, and the need for integrated strategies combining different therapeutic approaches. CONCLUSION: Given the absence of licensed vaccines and antivirals for alphaviruses, the E2 protein represents a promising therapeutic target while inhibiting E2 could block viral entry and infection. However, current strategies show variable efficacy and inconclusive results, highlighting the need for further research to validate and optimize E2-targeted therapies.
Research on the Anti-breast Hyperplasia Mechanism of Liqi Sanjie Granules Based on Network Pharmacological Analysis and Experimental Verification.
Hu X, Liu X, Yan R … +12 more , Li X, Zhou Y, Chen F, Xu M, Xiao C, Wang Y, Wang Z, Liu Y, Zhong B, Hu X, Zhou Q, Wei T
Curr Drug Targets · 2026 Mar · PMID 41879444 · Publisher ↗
BACKGROUND: Breast hyperplasia has become a major public health challenge due to changes in dietary patterns. However, there is still a lack of effective pharmacotherapy for Breast hyperplasia. METHODS: The chemical comp...
BACKGROUND: Breast hyperplasia has become a major public health challenge due to changes in dietary patterns. However, there is still a lack of effective pharmacotherapy for Breast hyperplasia. METHODS: The chemical components of Liqi Sanjie Granules (LSG) were quantified through HPLC. Three key components were screened out by combining network pharmacology methods and experimental determination methods, whereas key components in sera were quantified through LC-MS. The potential molecular mechanisms of LSG and these three blood-entering chemicals for the treatment of breast hyperplasia were predicted by network pharmacology. Estradiol benzoate and progesterone were injected intramuscularly to establish a breast hyperplasia model. Serum estradiol (E2), progesterone (P), testosterone (T), and prolactin (PRT) were detected by ELISA. H&E was used in monitoring the hyperplasia of rat mammary gland tissues. Immunohistochemistry and RT-PCR were used to detect the protein and mRNA expression levels of estrogen receptors (ERs) and progesterone receptors (PR) in rat mammary glands. RESULTS: The contents of seven components in LSG were quantified. After administration, the levels of paeoniflorin, glycyrrhizin, and ferulic acid were 280.16 ± 64.77, 101.87 ± 7.88, and 253.28 ± 17.64 μg per 200 μL, respectively. Network pharmacology studies have shown that LSG treats breast hyperplasia by acting on 63 targets in 36 signaling pathways, and the blood-entering chemicals of LSG involve 18 potential targets and 5 signaling pathways. Histopathological analysis revealed that rats in the LSG group had fewer mammary lobules and acini. Additionally, the proliferation of glandular epithelial cells was reduced. No significant changes were found in the serum levels of E2, P, PRT, and T in the LSG group. Concurrently, LSG can reduce the expression levels of PR protein and the mRNA of ESR1 and PGR in the rat mammary glands. DISCUSSION: This study suggests that the blood-entering chemicals paeoniflorin, glycyrrhizin, and ferulic acid may alleviate breast hyperplasia through decreasing the expression levels of ER, ESR1, and PGR in the mammary tissues, reducing the number of mammary lobules and alveoli, and inhibiting pathological changes in vacuolar degeneration, hyperplasia, and detachment of glandular epithelial cells. CONCLUSIONS: This study quantitatively analysed the seven chemical components of LSG and determined the contents of paeoniflorin, glycyrrhizin, and ferulic acid in the medicated serum. Furthermore, it demonstrates that LSG improves breast hyperplasia by regulating ER and PR expression levels.
Rheumatoid Arthritis Management: Emerging Drug Therapies and Innovations.
Dushyant, Narwal S, Singh G … +4 more , Kaur T, Dhingra AK, Grewal N, Jangra G
Curr Drug Targets · 2026 Mar · PMID 41832732 · Publisher ↗
INTRODUCTION: Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease characterized by persistent joint inflammation. Genetically predisposed conditions like Human Leukocyte Antigen DR1 (HLA-DR1) and Human Leu...
INTRODUCTION: Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease characterized by persistent joint inflammation. Genetically predisposed conditions like Human Leukocyte Antigen DR1 (HLA-DR1) and Human Leukocyte Antigen DR4 (HLA-DR4), coupled with environmental insults like infection, smoking, diet, and stress, are etiological factors in immune dysregulation. It results in the overproduction of pro-inflammatory cytokines and autoantibodies, ultimately causing synovial inflammation and joint destruction. The objective of this review is to highlight the latest developments in RA management through new drug formulations, targeted biologics, and novel Drug Delivery Systems (DDS). METHODS: A systematic literature search of scientific articles, registered trials, and published patents related to RA treatments was conducted. This review specifically focused on biologic Disease- Modifying Anti-Rheumatic Drugs (biologic DMARDs), small-molecule inhibitors, biomarker- directed personalized medicine, and DDS technologies. RESULTS: Biologic DMARDs, like Tumor Necrosis Factor (TNF) and interleukin inhibitors, have completely transformed the management of RA by targeting disease mechanisms. Small-molecule inhibitors became available with a similar efficacy to orally bioavailable forms. ADI has improved drug specificity, increased therapeutic efficacy, and decreased systemic toxicity. Biomarker- directed therapy has promise for improving treatment benefit. DISCUSSION: Current RA therapies highlight a shift toward biologics, personalized medicine, and advanced drug-delivery systems, enabling targeted action, reduced toxicity, and improved longterm disease management outcomes. CONCLUSION: Biologic drugs, small-molecule inhibitors, and DDS technology are revolutionizing treatment for RA. These strategies increase efficacy, decrease side effects, and provide cost-effective, sustained therapy. The intersection of personalized medicine and advanced drug delivery is a future solution for enhancing patient outcomes and quality of life.
The Computational Journey of siRNA Silencing Efficiency: Resources, Methods, and Future Directions.
Ren L, Li H, Zhang Y … +2 more , Luo N, Zhang Y
Curr Drug Targets · 2026 Mar · PMID 41832731 · Publisher ↗
Accurate prediction of small interfering RNA (siRNA) silencing efficiency is critical for accelerating nucleic acid drug development. Over the past two decades, the field has transitioned from empirical sequence-derived...
Accurate prediction of small interfering RNA (siRNA) silencing efficiency is critical for accelerating nucleic acid drug development. Over the past two decades, the field has transitioned from empirical sequence-derived heuristics to data-driven methods such as deep learning and graph neural networks. In this review, we systematically discuss current research from three integrated perspectives: data resources, design rules, and computational algorithms. Firstly, we summarize strengths, biases, and gaps in existing datasets, including low-throughput saturation scanning data, high-throughput panels, and specialized repositories for chemically modified siRNAs. Next, we outline the evolution of siRNA design principles, from classical guidelines such as GC content windows, terminal thermodynamic asymmetry, and positional base preferences, to more sophisticated thermodynamic-structural features incorporating target mRNA accessibility, and finally, to advanced clinical GalNAc-siRNA strategies involving seed destabilization and stereochemically purified backbones. Regarding computational algorithms, the progression is categorized into three stages: early linear regression models, traditional machine learning approaches, and modern deep learning frameworks, alongside various specialized algorithms tailored for chemically modified siRNAs. Current studies demonstrate steadily improving prediction accuracy, yet significant challenges persist, including insufficient data coverage for disease-relevant targets and hard-to-transfect cells, limited paired measurements of bare versus modified sequences, and inadequate integration of off-target effects and immunogenicity metrics. Moving forward, there is an urgent need to establish highquality, dose- and time-resolved datasets across diverse tissues, embed biophysical priors into interpretable deep-learning architectures, and adopt multi-task modeling approaches to optimize efficiency, safety, and delivery simultaneously. Collectively, these advancements promise to propel siRNA design beyond liver-centric applications towards precision therapeutics targeting multiple tissues and diseases.
Targeting the cGAS-STING Pathway in Gastrointestinal Cancers: Modulating Tumor-associated Inflammation for Therapeutic Effect.
Rathod H, Jain P, Verma D … +3 more , Verma G, Dharme KK, Ajazuddin
Curr Drug Targets · 2026 Mar · PMID 41832730 · Publisher ↗
INTRODUCTION: Gastrointestinal (GI) tumours are a significant contributor to cancer-related mortality, underscoring the necessity for novel therapeutic approaches. The cGAS-STING pathway, a cytosolic DNA-sensing mechanis...
INTRODUCTION: Gastrointestinal (GI) tumours are a significant contributor to cancer-related mortality, underscoring the necessity for novel therapeutic approaches. The cGAS-STING pathway, a cytosolic DNA-sensing mechanism, has two effects: it boosts antitumor immunity and also helps the tumour microenvironment inhibit the immune system. METHODS: This review integrates recent preclinical and clinical evidence regarding cGAS-STING signalling in gastrointestinal cancers, emphasising therapeutic strategies including STING agonists, immune checkpoint combinations, nanoparticle delivery, and pathway interactions with DNA damage response, autophagy, and immune surveillance. RESULTS: Evidence indicates that cGAS-STING activation can improve immune surveillance and therapeutic efficacy; nevertheless, sustained activation may facilitate tumour growth via immune evasion and chronic inflammation. Preclinical evidence indicates the promise of STING agonists and combination treatments, whereas initial clinical trials yield optimistic, although constrained, results. Toxicity, tumour heterogeneity, and resistance mechanisms remain obstacles. DISCUSSION: For therapy to work, it is important to find a balance between the two effects of cGAS- STING. Biomarker-guided medication development, rational combinations, and enhanced delivery technologies are some of the strategies that could lead to better outcomes. Predictive models powered by artificial intelligence also enable grouping patients and tailoring treatments to their needs. CONCLUSION: One promising avenue for advancing precision oncology in gastrointestinal malignancies is targeting the cGAS-STING pathway. Enhancing efficacy and reshaping cancer treatment could be achieved by overcoming present limits through integrated therapeutic approaches and personalised medicine.
FGMA: A Functional Group-enhanced Deep Learning Method for Drug Toxicity Prediction.
Cheng Y, Qiao J, Chen S … +2 more , Wei L, Liang G
Curr Drug Targets · 2026 Mar · PMID 41820218 · Publisher ↗
INTRODUCTION: Accurate drug toxicity prediction is vital for drug discovery, but existing atom-based methods are often computationally inefficient for complex molecules. This limitation creates a need for more efficient...
INTRODUCTION: Accurate drug toxicity prediction is vital for drug discovery, but existing atom-based methods are often computationally inefficient for complex molecules. This limitation creates a need for more efficient yet powerful predictive models. We introduce FGMA, a novel framework designed to address this challenge. METHODS: FGMA integrates functional groups with molecular fingerprints for a multi-view molecular encoding. The framework extracts key functional groups, treating them as unified entities to reduce computational overhead. These are then combined with MACCS fingerprints using a crossattention mechanism to capture both local chemical motifs and global structural properties. RESULTS: Experimental results demonstrate that FGMA achieves high accuracy and robustness in toxicity prediction tasks. In addition, interpretability analyses successfully identified how specific structural features and functional groups within drug molecules contribute to toxicity outcomes. DISCUSSION: Our findings validate that combining functional groups with fingerprints is an effective strategy that balances computational efficiency and representational power. The model's interpretability offers valuable, actionable insights into structure-toxicity relationships, aiding in the design of safer compounds. CONCLUSION: FGMA offers an effective, efficient, and interpretable tool for drug toxicity analysis. It stands to accelerate the drug discovery pipeline by enabling faster and more insightful safety assessments of potential drug candidates.
CRISPR-Cas9 Gene Editing: Promising Therapeutics for HPV-driven Cervical Cancer.
Kumar V, Bharti N, Ranjan R … +2 more , Pal RR, Kumar M
Curr Drug Targets · 2026 Feb · PMID 41755409 · Publisher ↗
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Cardioprotective Potential of Hedyotis corymbosa in Drug-Induced Cardiotoxicity: Insights from Network Pharmacology and preclinical Studies.
Gupta RK, Verma H, Patra J … +4 more , Srivastava R, Mishra A, Swain SR, Rao CV
Curr Drug Targets · 2026 Feb · PMID 41742616 · Publisher ↗
INTRODUCTION: Cardiovascular diseases (CVDs) remain a major global health threat, accounting for a significant proportion of deaths worldwide. Doxorubicin (DOX) and Isoproterenol (ISO) are known to induce cardiotoxicity...
INTRODUCTION: Cardiovascular diseases (CVDs) remain a major global health threat, accounting for a significant proportion of deaths worldwide. Doxorubicin (DOX) and Isoproterenol (ISO) are known to induce cardiotoxicity primarily through the generation of reactive oxygen species (ROS). METHODS: Drug-likeness analysis of selected phytochemicals was performed using SwissTargetPrediction and SuperPred 3.0. Genes associated with DOX-induced cardiotoxicity were curated from GeneCards, OMIM (Online Mendelian Inheritance in Man), and DisGeNet. Molecular docking was performed to evaluate potential interactions with TOP2A, HIF1A, ABCB1, NOS3, PIK3R1, SRC, ABL1, and NR3C2. An in vivo cardiotoxicity model using DOX and ISO was employed to assess the cardioprotective effects of ethanolic extracts of Hedyotis corymbosa (EEHC). Wistar rats of either sex, weighing 200-220 g, were used in the study. RESULTS: Docking scores of Corycavidine against hub genes ranged from -6.66 kcal/mol to -1.26 kcal/mol, while MM-GBSA binding energies ranged from -50.22 kcal/mol to -8.28 kcal/mol, with the strongest binding observed for ABL1 (-50.22 kcal/mol). The NBE (cumulative ΔG_Coul and ΔG_vdW) was highest for NOS3 (-87.46 kcal/mol). EEHC administration significantly decreased CK-MB, malondialdehyde, and glutathione levels, while HDL, catalase, and superoxide dismutase levels were markedly increased, accompanied by reductions in total blood cholesterol and triglyceride levels. DISCUSSION: DOX and ISO treatment resulted in myocardial wall thickening and lipoprotein accumulation, suggesting cardiac dysfunction. Computational docking and MM-GBSA analyses of 16 hub genes revealed a favorable binding profile of Corycavidine with several key proteins implicated in cardiovascular regulation and injury responses. CONCLUSION: These findings suggest that Corycavidine may serve as a multi-target cardioprotective agent, potentially modulating oxidative stress, inflammation, endothelial function, and cellular survival pathways.
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