Search Results (1,723)

Drug–target affinity (DTA) prediction is one of the core components of drug discovery. Despite considerable advances in previous research, DTA tasks still face several limitations with insufficient multi-modal information of drugs, the inherent sequence length limitation of protein language models, and single attention mechanisms that fail to capture critical multi-scale features. To alleviate the above limitations, we developed a multi-granularity fusion model for drug–target binding affinity prediction, termed MGF-DTA. This model is composed of three fusion modules, specifically as follows. First, the model extracts deep semantic features of SMILES strings through ChemBERTa-2 and integrates them with molecular fingerprints by using gated fusion to enhance the multi-modal information of drugs. In addition, it employs a residual fusion mechanism to integrate the global embeddings from ESM-2 with the local features obtained by the k-mer and principal component analysis (PCA) method. Finally, a hierarchical attention mechanism is employed to extract multi-granularity features from both drug SMILES strings and protein sequences. Comparative analysis with other mainstream methods on the Davis, KIBA, and BindingDB datasets reveals that the MGF-DTA model exhibits outstanding performance advantages. Further, ablation studies confirm the effectiveness of the model components and case study illustrates its robust generalization capability. Full article

Cisplatin (CDDP) is a cornerstone chemotherapeutic drug, yet its efficacy is frequently compromised by renal toxicity, primarily manifesting as acute kidney injury (AKI). Magnolol (MG) is a polyphenol from Magnolia officinalis and has been widely documented for its pronounced antioxidant and anti-inflammatory properties. This study evaluated the renoprotective effects of MG in a murine model of CDDP-induced AKI. Male C57BL/6 mice received MG (20 mg/kg) via daily intraperitoneal injection for four consecutive days, starting one day before a single CDDP injection. MG significantly reduced the serum concentrations of blood urea nitrogen and creatinine. Histopathological assessment revealed attenuated tubular damage and reduced expression of tubular injury markers. MG inhibited pro-inflammatory cytokines at both systemic and renal levels, alleviated endoplasmic reticulum stress, and suppressed activation of mitogen-activated protein kinase signaling pathways. Apoptotic damage was mitigated, as shown by the fewer TUNEL-positive cells and lowered expression of pro-apoptotic markers. In parallel, ferroptotic processes were alleviated through downregulation of pro-ferroptotic proteins and preservation of key antioxidant regulators. Importantly, MG restored nuclear factor erythroid 2-related factor 2 activity and upregulated downstream antioxidant effectors. These findings highlight the multi-targeted renoprotective actions of MG and support its possible utility as a therapeutic agent to prevent CDDP-induced renal injury. Full article

The continuous emergence of SARS-CoV-2 variants, especially the Omicron strain with its heightened transmissibility, has posed ongoing challenges to the efficacy of existing vaccine and drug regimens. This situation highlights the pressing demand for antiviral drugs employing novel mechanisms of action. Pentacyclic triterpenoids (PTs), a structurally varied group of compounds derived from plants, exhibit both antiviral and anti-inflammatory activities, making them attractive candidates for further therapeutic development. These natural products, along with their saponin derivatives, show broad-spectrum inhibitory effects against multiple SARS-CoV-2 variants (from Alpha to Omicron) via interactions with multiple targets, such as the spike protein, main protease (Mpro), RNA-dependent RNA polymerase (RdRp), and inflammatory signaling pathways. This review consolidates recent findings on PTs and their saponins, emphasizing their influence on the key structural features required for inhibiting viral attachment, membrane fusion, reverse transcription, and protease function. We systematically summarized the structure–activity relationships and their antiviral results of PTs based on different target proteins in existing studies. Furthermore, this work points toward new strategies for designing multi-target PT-based inhibitors with improved efficacy against Omicron and future variants. Full article

Nonsteroidal anti-inflammatory drugs (NSAIDs) can exacerbate urticaria and/or angioedema in up to 30% of patients with chronic urticaria (CU), representing a distinct subtype characterized by heightened inflammation and leukotriene-driven pathophysiology. MicroRNAs (miRNAs) are post-transcriptional regulators that modulate immune and inflammatory responses. This study aimed to identify differentially expressed miRNAs (DEMs) according to NSAID hypersensitivity status and to elucidate their molecular networks in CU. Serum miRNA profiles were analyzed in 14 NSAID-exacerbated CU (NECU) and 16 NSAID-tolerant CU (NTCU) patients using an Affymetrix GeneChip^® miRNA 4.0 Array. DEMs were identified (fold difference > 1.5, p < 0.05), and validated targets were retrieved from the multiMiR database for network construction and Gene Ontology enrichment analyses. NECU patients exhibited a higher frequency of angioedema and systemic corticosteroid use than NTCU patients. Eight DEMs were identified, including upregulated miR-5001-5p, miR-4270, and miR-6869-5p, and downregulated miR-6511b-5p, miR-2277-5p, and miR-378h in NECU. Network integration revealed AGO2-BTG2-LMNB2, NFIC-ZZZ3, and NUFIP2-GLG1 as central clusters, implicating dysregulation of mRNA decay and inflammatory signaling pathways. Reduced miR-6511b-5p expression may derepress BRG1, enhancing chromatin accessibility for inflammatory and leukotriene-synthetic genes. Distinct miRNA signatures differentiate NECU from NTCU, implying a miR-5001-5p/miR-6511b-5p–mRNA decay axis that links impaired post-transcriptional regulation with leukotriene-driven inflammation in CU. These findings highlight candidate miRNAs as potential biomarkers for disease endotyping and therapeutic stratification. Full article

Background: Gastric signet-ring cell carcinoma (GSRCC) is a distinct subtype of gastric cancer characterized by unique biological features, leading to low rates of early diagnosis, poor prognosis, and limited response to chemotherapy and immunotherapy. Effective targeted therapies for GSRCC remain scarce. Given these treatment challenges and the potential efficacy of antibody-drug conjugates (ADCs) in clinical settings, this study focuses on identifying novel ADCs with significant potential to improve the treatment outcomes of GSRCC. Methods: We conducted a comprehensive bioinformatics analysis of GSRCC using multi-omics data (including transcriptomics and proteomics) and identified the poliovirus receptor (PVR) as a potential therapeutic target for GSRCC. We selected deruxtecan (DXd) as an effective carrier for developing an ADC targeting GSRCC. The synthesized PVR monoclonal antibody-DXd complex (PVR-DXd) has a drug-to-antibody ratio (DAR) of 4. Results: PVR-DXd demonstrated potent antitumor activity in a human GSRCC xenograft model, effectively eliminating tumors while sparing normal tissue, highlighting its potential as a novel and impactful targeted therapy for this aggressive subtype of gastric signet ring cell carcinoma. Conclusions: This preliminary study supports the further development of PVR-DXd as a candidate therapy for advanced GSRCC. Full article

Multidrug resistance (MDR) is a central cause of chemotherapy failure and tumor recurrence and metastasis, and its mechanism involves enhanced drug efflux, target mutation, upregulation of DNA repair and remodeling of the tumor microenvironment. ABC transporter protein (P-gp, MRP, and BCRP)-mediated efflux of drugs is the most intensively researched aspect of the study, but the first three generations of small-molecule reversal agents were stopped in the clinic because of toxicity or pharmacokinetic defects. Natural products are considered as the fourth generation of MDR reversal agents due to their structural diversity, multi-targeting and low toxicity. In this paper, we systematically summarize the inhibitory activities of monoterpenes, sesquiterpenes, diterpenes and triterpenes against ABC transporter proteins in in vitro and in vivo models and focus on the new mechanism of reversing drug resistance by blocking efflux pumps, modulating signaling pathways such as PI3K-AKT, Nrf2, NF-κB and remodeling the tumor microenvironment. For example, Terpenoids possess irreplaceable core advantages over traditional multidrug resistance (MDR) reversers: Compared with the first three generations of synthetic reversers, natural/semisynthetic terpenoids integrate low toxicity (mostly derived from edible medicinal plants, half-maximal inhibitory concentration IC₅₀ > 50 μM), high target specificity (e.g., oleanolic acid specifically inhibits the ATP-binding cassette (ABC) transporter subtype ABCC1 without cross-reactivity with ABCB1), and multi-mechanistic synergistic effects (e.g., β-caryophyllene simultaneously mediates the dual effects of “ABCB1 efflux inhibition + apoptotic pathway activation”). These unique characteristics enable terpenoids to effectively circumvent key limitations of traditional synthetic reversers, such as high toxicity and severe drug–drug interactions. Among them, lupane-type derivative BBA and euphane-type sooneuphanone D (triterpenoids), as well as dihydro-β-agarofuran-type compounds and sesquiterpene lactone Conferone (sesquiterpenoids), have emerged as the core lead compounds with the greatest translational potential in current MDR reverser research, attributed to their potent in vitro and in vivo MDR reversal activity, low toxicity, and excellent druggable modifiability. At the same time, we point out bottlenecks, such as low bioavailability, insufficient in vivo evidence, and unclear structure–activity relationship and put forward a proposal to address these bottlenecks. At the same time, the bottlenecks of low bioavailability, insufficient vivo evidence and unclear structure–activity relationship have been pointed out, and future research directions such as nano-delivery, structural optimization and combination strategies have been proposed to provide theoretical foundations and potential practical pathways for the clinical translation research of terpenoid compounds, whose clinical application still requires further in vivo validation and translational research support. Full article

Background: Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disease characterized primarily by intravascular hemolysis, thrombosis, and bone marrow failure. Complement inhibitors are commonly used in clinical treatment and show limited efficacy, highlighting the urgent need to identify new therapeutic targets and explore alternative treatment strategies to provide theoretical guidance for clinical practice. Methods: We established a PNH cell model and constructed an miRNA–mRNA regulatory network to identify key miRNAs and core target genes. Single-cell sequencing data were analyzed to further clarify the critical genes. Finally, integrated drug database analysis identified potential therapeutic agents for PNH, which were validated by molecular docking and molecular dynamics simulations. Results: Using CRISPR/RNP technology, we successfully constructed a PIGA-knockout (PIGA-KO) THP-1 cell model. Differential expression analysis identified 1979 differentially expressed mRNAs (DEmRNAs) and 97 differentially expressed miRNAs (DEmiRNAs). The multiMiR package in R was used to predict the target genes of DEmiRNAs, from which those experimentally validated through dual-luciferase reporter assays were selected. After integration with the DEmRNAs, an miRNA–mRNA regulatory network was constructed, comprising 26 miRNAs and 38 mRNAs. Subsequent miRNA pathway enrichment analysis identified hsa-miR-23a-3p as a key miRNA, with CXCL12, CXCL8, HES1, and TRAF5 serving as core target genes. The integration of single-cell sequencing datasets (PRJNA1061334 and GSE157344) was performed, followed by cell communication and enrichment analysis. This approach, combined with clinical relevance, identified the neutrophil cluster as the key cluster. Intersection analysis of neutrophil cluster differential analysis results with key modules from hdWGCNA further clarified the critical genes. Drug prediction using EpiMed, CMap, and DGIdb identified Leflunomide, Dipyridamole, and Pentoxifylline as potential therapeutic agents. Molecular docking and molecular dynamics simulations showed stable binding of these potential drugs to the critical molecules, indicating a viable molecular interaction foundation. Conclusions: Leflunomide, Dipyridamole, and Pentoxifylline may serve as promising therapeutic agents for PNH, and the hsa-miR-23a-3p/CXCL8 regulatory axis could play a pivotal role in the pathogenesis and progression of PNH. Full article

Background/Objectives: Obstructive sleep apnea (OSA) affects approximately 1 billion adults worldwide with extensive comorbidities, including cardiovascular disease, metabolic disorders, and cognitive decline, yet pharmacological therapies remain limited. Conventional bottom-up omics approaches identify numerous genes overlapping with other diseases, hindering therapeutic translation. This study introduces a top-down, comorbidity-driven approach to identify actionable molecular targets and develop rational dual kinase inhibitors for OSA management. Methods: We implemented a five-tier modeling workflow: (1) comorbidity network analysis, (2) disease module identification through NetworkAnalyst, (3) mechanistic pathway reconstruction of the CK1δ-(HIF1A)-PINK1 signaling cascade, (4) molecular docking analysis of Nigella sativa alkaloids and reference inhibitors (IC261, PF-670462) against CK1δ (PDB: 3UYS) and PINK1 (PDB: 5OAT) using AutoDock Vina, and (5) rational design and computational validation of novel dual inhibitors (ICL, PFL) integrating pharmacophoric features from natural alkaloids and established kinase inhibitors. Results: Extensive network analysis revealed a discrete OSA disease module centered on two interconnected protein kinases—CK1δ and PINK1—that mechanistically bridge circadian disruption and neurodegeneration. Among natural alkaloids, Nigellidine showed strongest CK1δ binding (−8.0 kcal/mol) and Nigellicine strongest PINK1 binding (−8.6 kcal/mol). Rationally designed dual inhibitors demonstrated superior binding: ICL (−7.2 kcal/mol PINK1, −8.9 kcal/mol CK1δ) and PFL (−10.8 kcal/mol CK1δ, −11.2 kcal/mol PINK1), representing −2.6–2.8 kcal/mol improvements over reference compounds. Conclusions: This study establishes a comorbidity-driven translational framework identifying the CK1δ-PINK1 axis as a therapeutic target in OSA. The rationally designed dual inhibitors represent third-generation precision therapeutics addressing OSA’s multi-dimensional pathophysiology, while the five-tier workflow provides a generalizable template for drug discovery in complex multimorbid diseases. Full article

The emergence of multidrug-resistant (MDR) bacterial pathogens has heightened the urgency for novel antibacterial agents. The bacterial cell wall usually comprises peptidoglycan, which presents a prime target for antibacterial drug development due to its indispensable role in maintaining cellular integrity. Conventional antibiotics such as β-lactams and glycopeptides hinder peptidoglycan synthesis through competitive binding of penicillin-binding proteins (PBPs) and sequestration of lipid-linked precursor molecules. Nevertheless, prevalent resistance mechanisms including target modification, β-lactamase hydrolysis, and multi-drug efflux pumps have limited their clinical utility. This comprehensive analysis explicates the molecular machinery underlying bacterial cell wall assembly, evaluates both explored and unexplored enzymatic nodes within this pathway, and highlights the transformative impact of high-resolution structural elucidation in accelerating structure-guided drug discovery. Novel targets such as GlmS, GlmM, GlmU, Mur ligases, D,L-transpeptidases are assessed for their inclusiveness for the discovery of next-generation antibiotics. Additionally, cell wall inhibitors are also examined for their mechanisms of action and evolutionary constraints on MDR development. High-resolution crystallographic data provide valuable insights into molecular blueprints for structure-guided optimization of pharmacophores, enhancing binding affinity and circumventing resistance determinants. This review proposes a roadmap for future innovation, advocating for the convergence of computational biology platforms, machine learning-driven compound screening, and nanoscale delivery systems to improve therapeutic efficacy and pharmacokinetics. The synergy of structural insights and cutting-edge technologies offers a multidisciplinary framework for revitalizing the antibacterial arsenal and combating MDR infections efficiently. Full article

Background: β-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitors demonstrated amyloid-lowering efficacy but failed in phase II/III clinical trials due to adverse effects and limited disease-modifying outcomes. This study employed an integrated network pharmacology and molecular docking approach to quantitatively elucidate the multitarget mechanisms of 4 (phase II/III) discontinued BACE1 inhibitors (Verubecestat, Lanabecestat, Elenbecestat, and Umibecestat) and the preclinical compound AM-6494 in Alzheimer’s disease (AD). Methods: Drug-associated targets were intersected with AD-related genes to construct a protein–protein interaction (PPI) network, followed by topological analysis to identify hub proteins. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed using statistically significant thresholds (p < 0.05, FDR-adjusted). Molecular docking was conducted using AutoDock Vina to quantify binding affinities and interaction modes between the selected compounds and the identified hub proteins. Results: Network analysis identified 10 hub proteins (CASP3, STAT3, BCL2, AKT1, MTOR, BCL2L1, HSP90AA1, HSP90AB1, TNF, and MDM2). GO enrichment highlighted key biological processes, including the negative regulation of autophagy, regulation of apoptotic signalling, protein folding, and inflammatory responses. KEGG pathway analysis revealed significant enrichment in the PI3K–AKT–MTOR signalling, apoptosis, and TNF signalling pathways. Molecular docking demonstrated strong multitarget binding, with binding affinities ranging from approximately −6.6 to −11.4 kcal/mol across the hub proteins. Umibecestat exhibited the strongest binding toward AKT1 (−11.4 kcal/mol), HSP90AB1 (−9.5 kcal/mol), STAT3 (−8.9 kcal/mol), HSP90AA1 (−8.5 kcal/mol), and MTOR (−8.3 kcal/mol), while Lanabecestat showed high affinity for AKT1 (−10.6 kcal/mol), HSP90AA1 (−9.9 kcal/mol), BCL2L1 (−9.2 kcal/mol), and CASP3 (−8.5 kcal/mol), respectively. These interactions were stabilized by conserved hydrogen bonding, hydrophobic contacts, and π–alkyl interactions within key regulatory domains of the target proteins, supporting their multitarget engagement beyond BACE1 inhibition. Conclusions: This study demonstrates that clinically failed BACE1 inhibitors engage multiple non-structural regulatory proteins that are central to AD pathogenesis, particularly those governing autophagy, apoptosis, proteostasis, and neuroinflammation. The identified ligand–hub protein complexes provide a mechanistic rationale for repurposing and optimization strategies targeting network-level dysregulation in Alzheimer’s disease, warranting further in silico refinement and experimental validation. Full article

Peptide-based biomaterials have emerged as versatile tools for pharmaceutical drug delivery due to their biocompatibility and tunable sequences, yet a comprehensive overview of their categories, mechanisms, and optimization strategies remains lacking to guide clinical translation. This review systematically collates advances in peptide-based biomaterials, covering peptide excipients (cell penetrating peptides, tight junction modulating peptides, and peptide surfactants/stabilizers), self-assembling peptides (peptide-based nanospheres, cyclic peptide nanotubes, nanovesicles and micelles, peptide-based hydrogels and depots), and peptide linkers (for antibody drug-conjugates, peptide drug-conjugates, and prodrugs). We also dissect sequence-based optimization strategies, including rational design and biophysical optimization (cyclization, stapling, D-amino acid incorporation), functional motif integration, and combinatorial discovery with AI assistance, with examples spanning marketed drugs and research-stage candidates. The review reveals that cell-penetrating peptides enable efficient intracellular payload delivery via direct penetration or endocytosis; self-assembling peptides form diverse nanostructures for controlled release; and peptide linkers achieve site-specific drug release by responding to tumor-associated enzymes or pH cues, while sequence optimization enhances stability and targeting. Peptide-based biomaterials offer precise, biocompatible and tunable solutions for drug delivery, future advancements relying on AI-driven design and multi-functional modification will accelerate their transition from basic research to clinical application. Full article

Drug discovery is a complex and expensive process in which only a small proportion of candidate molecules reach clinical approval. Computational methods, particularly computer-aided drug design (CADD), have become fundamental to accelerate and optimize early stages of discovery by integrating chemical, biological, and pharmacokinetic information into predictive models. This review outlines a complete computational workflow for chemical compound analysis, covering molecular structure generation, database selection, evaluation of absorption, distribution, metabolism, excretion and toxicity (ADMET), target prediction, and molecular docking. It focuses on freely accessible and web-based tools that enable reproducible, cost-effective, and scalable in silico studies. Key platforms such as PubChem, ChEMBL, RDKit, SwissADME, TargetNet, and SwissDock are highlighted as examples of how different resources can be integrated to support rational compound design and prioritization. The article also discusses essential methodological principles, data curation strategies, and common limitations in virtual screening and docking analyses. Finally, it explores future directions in computational drug discovery, including the incorporation of artificial intelligence, multi-omics integration, and quantum simulations, to enhance predictive accuracy and translational relevance. Full article

Phosphatidylinositol-3-kinases (PI3Ks) constitute an important validated therapeutic class involved in crucial cellular processes, and their dysregulation is associated with cancer initiation and progression. Nonetheless, intrinsic and acquired resistance mechanisms associated with PI3K pathway modulation have underscored the need for alternative therapeutic strategies. In this context, recent studies have shown that simultaneous inhibition of PI3K and histone deacetylases (HDAC) promotes synergistic antitumor effects in different cancer cell lines. HDACs are validated epigenetic targets that are extensively explored in clinical practice and have a pharmacophore with versatility for structural modifications, which facilitates the design of multitarget inhibitors. This review examines the rational design and synthetic evolution of dual PI3K/HDAC inhibitors, an area catalyzed by the development of fimepinostat, the first clinically evaluated agent exhibiting potent and balanced inhibition of both targets. We provide a critical overview of PI3K/HDAC multitarget inhibitors reported in recent years that have progressed to preclinical or clinical investigation, discussing the structural frameworks employed, medicinal chemistry strategies adopted, and structure–activity relationships established. Particular attention is given to advantageous molecular features as well as challenges related to toxicity, pharmacokinetic behavior, and pharmacodynamic modulation. From this comprehensive analysis, we outline key considerations and emerging design principles that may inform the next generation of PI3K/HDAC multitarget drug candidates. Insights derived from the diversity of chemical scaffolds, activity profiles, and selectivity patterns described herein may support the development of innovative therapeutic agents capable of overcoming current limitations in anticancer treatment. Full article

Arthropod-borne orthoflaviviruses, including dengue, Zika, Japanese encephalitis, yellow fever and West Nile viruses, pose a significant global public health threat, causing hundreds of millions of infections annually with severe clinical symptoms. However, the lack of effective vaccines and antiviral drugs, coupled with the biosafety risks associated with handling live highly pathogenic strains, hinders progress in antiviral research. Pseudovirus technology, which uses single-round infectious viral particles lacking replication competence, has thus gained prominence as a safe and versatile tool for antiviral research. This review systematically summarizes the construction, optimization, and applications of orthoflavivirus pseudoviruses in antiviral research. The primary construction strategies of orthoflavivirus pseudoviruses rely on multi-plasmid co-transfection of viral replicons and structural protein expression vectors, leveraging the host cell secretory pathway to mimic natural viral assembly and maturation. The core applications of pseudovirus technology are highlighted, including high-throughput screening and detection of neutralizing antibodies, identification of antiviral drugs targeting viral entry or replication, and evaluation of vaccine immunogenicity. Despite these strengths, the approach still faces limitations, such as incomplete simulation of native viral structures and batch-to-batch titer variability, which may affect the physiological relevance of findings. In summary, orthoflavivirus pseudovirus technology has become an essential platform in both basic virology research and translational medicine, providing critical insights and tools in the ongoing fight against arthropod-borne orthoflaviviruses diseases. Full article

S. suis is a prominent zoonotic pathogen responsible for diseases such as arthritis in piglets, swine septicemia, and meningitis. The emergence of multi-drug resistance (MDR) underscores the urgent need for the development of novel antibacterial strategies. In this context, a systematic evaluation of the antibacterial potential of the bacteriophage lytic enzyme Ply900 was conducted in this study, along with an analysis of its domain functions and an in vivo study of its therapeutic dynamics. Ply900 exhibits potent in vitro lytic activity against multiple bacteria, including Streptococcus suis, Streptococcus agalactiae, and Staphylococcus aureus. Notably, it possesses broad biochemical stability, with tolerance to diverse environmental conditions. In a mouse model of S. suis serotype 2 SC19 infection, both the direct Ply900 treatment group and the triple therapy group achieved effective eradication of S. suis, with markedly improved survival rates. The remaining bacteria remained susceptible to Ply900, with no evidence of induced resistance development. Mechanistic analysis revealed that the SH3B domain of Ply900 enhances targeted cleavage efficiency by binding synergistically to peptidoglycan with the CHAP domain, with CYS-34, HIS-59, and ASP-28 serving as key amino acid sites for Ply900’s cleavage activity. Collectively, these findings lay the foundation for the potential dual applications of the lysin Ply900, both in the clinical treatment of S. suis infections and in the prevention and control of these pathogenic bacteria in livestock farming. Full article