Search Results (842)

Phthalocyanines (Pcs) are well-established photosensitizers in photodynamic therapy, valued for their strong light absorption, high singlet oxygen generation, and photostability. Recent advances have focused on covalently conjugating Pcs, particularly zinc phthalocyanines (ZnPcs), with a wide range of small bioactive molecules to improve selectivity, efficacy, and multifunctionality. These conjugates combine light-activated reactive oxygen species (ROS) production with targeted delivery and controlled release, offering enhanced treatment precision and reduced off-target toxicity. Chemotherapeutic agent conjugates, including those with erlotinib, doxorubicin, tamoxifen, and camptothecin, demonstrate receptor-mediated uptake, pH-responsive release, and synergistic anticancer effects, even overcoming multidrug resistance. Beyond oncology, ZnPc conjugates with antibiotics, anti-inflammatory drugs, antiparasitics, and antidepressants extend photodynamic therapy’s scope to antimicrobial and site-specific therapies. Targeting moieties such as folic acid, biotin, arginylglycylaspartic acid (RGD) and epidermal growth factor (EGF) peptides, carbohydrates, and amino acids have been employed to exploit overexpressed receptors in tumors, enhancing cellular uptake and tumor accumulation. Fluorescent dye and porphyrinoid conjugates further enrich these systems by enabling imaging-guided therapy, efficient energy transfer, and dual-mode activation through pH or enzyme-sensitive linkers. Despite these promising strategies, key challenges remain, including aggregation-induced quenching, poor aqueous solubility, synthetic complexity, and interference with ROS generation. In this review, the examples of Pc-based conjugates were described with particular interest on the synthetic procedures and optical properties of targeted compounds. Full article

Background: Antibacterial resistance (ABR) poses a major challenge to global health, with methicillin-resistant Staphylococcus aureus (MRSA) being one of the prominent multidrug-resistant strains. MRSA has developed resistance through the expression of Penicillin-Binding Protein 2a (PBP2a), a key transpeptidase enzyme involved in bacterial cell wall biosynthesis. Objectives: The objective was to design and characterize a novel small-molecule inhibitor targeting PBP2a as a strategy to combat MRSA. Methods: We synthesized a new indole triazole conjugate (ITC) using eco-friendly and click chemistry approaches. In vitro antibacterial tests were performed against a panel of strains to evaluate the ITC antibacterial potential. Further, a series of in silico evaluations like molecular docking, MD simulations, free energy landscape (FEL), and principal component analysis (PCA) using the crystal structure of PBP2a (PDB ID: 4CJN), in order to predict the mechanism of action, binding mode, structural stability, and energetic profile of the 4CJN-ITC complex. Results: The compound ITC exhibited noteworthy antibacterial activity, which effectively inhibited the selected strains. Binding score and energy calculations demonstrated high affinity of ITC for the allosteric site of PBP2a and significant interactions responsible for complex stability during MD simulations. Further, FEL and PCA provided insights into the conformational behavior of ITC. These results gave the structural clues for the inhibitory action of ITC on the PBP2a. Conclusions: The integrated in vitro and in silico studies corroborate the potential of ITC as a promising developmental lead targeting PBP2a in MRSA. This study demonstrates the potential usage of rational drug design approaches in addressing therapeutic needs related to ABR. Full article

High-mobility group box 1 (HMGB1) is a nuclear protein that can interact with a transmembrane cell surface receptor for advanced glycation end products (RAGEs) and mediates the inflammatory pathways that lead to various pathological conditions like cancer, diabetes, cardiovascular diseases, and neurodegenerative disorders. Blocking the HMGB1/RAGE axis using various small synthetic or natural molecules has been proven to be an effective therapeutic approach to treating these inflammatory conditions. However, the low water solubility of these pharmacoactive molecules limits their clinical use. Pharmaceutically active molecules with low solubility and bioavailability in vivo convey a higher risk of failure for drug development and drug innovation. The pharmacokinetic and pharmacodynamics parameters of these compounds are majorly affected by their solubility. Enhancement of the bioavailability and solubility of drugs is a significant challenge in the area of pharmaceutical formulations. This review mainly describes various technologies utilized to improve the bioavailability of synthetic or natural molecules which have been particularly used in various inflammatory conditions acting specifically through the HMGB1/RAGE pathway. Full article

Animal venoms are complex biochemical secretions rich in highly potent and selective bioactive molecules, including peptides, enzymes, and small organic compounds. Once associated primarily with toxicity, these venoms are now recognized as a promising source of therapeutic agents for a wide range of medical conditions. This review provides a comprehensive analysis of the pharmacological potential of venom-derived compounds, highlighting their mechanisms of action, such as ion channel modulation, receptor targeting, and enzyme inhibition. Successful venom-derived drugs like captopril and ziconotide exemplify the translational potential of this biological arsenal. We discuss therapeutic applications in cardiovascular diseases, chronic pain, cancer, thrombosis, and infectious diseases, as well as emerging peptide candidates in clinical development. Technological advancements in omics, structural biology, and synthetic peptide engineering have significantly enhanced the discovery and optimization of venom-based therapeutics. Despite challenges related to stability, immunogenicity, and ecological sustainability, the integration of AI-driven drug discovery and personalized medicine is expected to accelerate progress in this field. By synthesizing current findings and future directions, this review underscores the transformative potential of animal venoms in modern pharmacotherapy and drug development. We also discuss current therapeutic limitations and how venom-derived compounds may address unmet needs in specific disorders. Full article

Background/Objective: In the pursuit of identifying novel therapeutic agents against breast cancer, a major priority is finding agents that effectively and safely inhibit the signaling pathways sustaining cancer cells. To better focus research efforts in validating such candidates, this in silico study assessed the pharmacokinetic profiles, thermodynamics, and binding affinity of chlorogenic acid and cinnamaldehyde with the upstream mediators of the Akt pathway implicated in breast cancer cells. Methods: Various software and online tools were used to conduct molecular docking of the small molecules with the proteins PI3K, Akt, and PDK1, and to examine their absorption, distribution, metabolism, elimination, and toxicity (ADMET) profile. Results: The results show strong binding energy (all within the range of those of FDA-approved drugs) and thermostability between the compounds and the proteins. The phytochemicals were predicted to have moderate oral bioavailability and tissue distribution, and were identified as substrates of drug metabolizing enzymes, but not deactivated. Conclusion: Although these predictive data warrant confirmation in a biological system, they suggest that the compounds have good pharmacokinetics and are strong inhibitors of the Akt pathway, with great potential to shut down breast cancer cell invasion and migration. These data also inform more efficient experimental designs for our planned in vivo studies. Full article

Polypharmacology, the rational design of small molecules that act on multiple therapeutic targets, offers a transformative approach to overcome biological redundancy, network compensation, and drug resistance. This review outlines the scientific rationale for polypharmacology, highlighting its success across oncology, neurodegeneration, metabolic disorders, and infectious diseases. Emphasis is placed on how polypharmacological agents can synergize therapeutic effects, reduce adverse events, and improve patient compliance compared to combination therapies. We also explore how computational methods—spanning ligand-based modeling, structure-based docking, network pharmacology, and systems biology—enable target selection and multi-target ligand prediction. Recent advances in artificial intelligence (AI), particularly deep learning, reinforcement learning, and generative models, have further accelerated the discovery and optimization of multi-target agents. These AI-driven platforms are capable of de novo design of dual and multi-target compounds, some of which have demonstrated biological efficacy in vitro. Finally, we discuss the integration of omics data, CRISPR functional screens, and pathway simulations in guiding multi-target design, as well as the challenges and limitations of current AI approaches. Looking ahead, AI-enabled polypharmacology is poised to become a cornerstone of next-generation drug discovery, with potential to deliver more effective therapies tailored to the complexity of human disease. Full article

In this study, we report for the first time a brand-new protocol for the multigram-scale synthesis of 5-methyl-6-oxo-1,6-dihydropyridazine-3-carboxylic and 2,8-dimethylimidazo[1,2-b]pyridazine-6-carboxylic acids, without the utilization of metal-complex catalysts. The developed technology for the production of the aforementioned acids is of great importance for two reasons. Firstly, these acids serve as intermediates in the synthesis of risdiplam, the first small-molecule drug approved for the treatment of spinal muscular atrophy. Secondly, they themselves are valuable building blocks right from a broader medicinal chemistry perspective. The synthesis of risdiplam was carried out using a modified synthetic protocol, utilizing the acids indicated above as the key intermediates. The protocols presented in this study enable the production of target compounds with high purity and an acceptable yield. Full article

Network theory analysis has emerged as a powerful approach for investigating the complex behavior of dynamic and interactive systems, including proteomic systems. One key application of these methods is the study of long-range signaling dynamics in proteins, a phenomenon known as allostery. In this study, we applied computational models using network theory analysis to explore long-range electrostatic interactions and allosteric drug rescue mechanisms in the DNA-binding domain (DBD) of the p53 protein, a critical tumor suppressor whose dysfunction, often caused by missense mutations, is implicated in over 50% of human cancers. Using heat kernel and Wasserstein distance-based analyses, we explored the allosteric behavior of p53-DBD constructs with the Y220C mutation in the presence or absence of allosteric effector drugs. Our results demonstrated that these network theory-based protocols effectively detected the differential efficacies of small molecule allosteric effector drug compounds in restoring long-range electrostatic dynamics in the Y220C mutant. Furthermore, our approach identified key long-range electrostatic interactions critical to both the nominal and drug-rescued functionality of the p53-DBD, providing valuable insights into allosteric modulation and its therapeutic potential. Full article

Diabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease (ESKD) globally. Despite advances in our understanding of its pathophysiology, current therapies are often insufficient to stop its progression. In recent years, microRNAs (miRNAs)—small, non-coding RNA molecules involved in post-transcriptional gene regulation—have emerged as critical modulators of key pathogenic mechanisms in DKD, including fibrosis, inflammation, oxidative stress, and apoptosis. Numerous studies have identified specific miRNAs that either exacerbate or mitigate renal injury in DKD. Among them, miR-21, miR-192, miR-155, and miR-34a are associated with disease progression, while miR-126-3p, miR-29, miR-146a, and miR-215 demonstrate protective effects. These molecules are also detectable in plasma, urine, and renal tissue, making them attractive candidates for diagnostic and prognostic biomarkers. Advances in therapeutic technologies such as antagomiRs, mimics, locked nucleic acids, and nanoparticle-based delivery systems have opened new possibilities for targeting miRNAs in DKD. Additionally, conventional drugs, including SGLT2 inhibitors, metformin, and GLP-1 receptor agonists, as well as dietary compounds like polyphenols and sulforaphane, may exert nephroprotective effects by modulating miRNA expression. Recent evidence also highlights the role of gut microbiota in regulating miRNA activity, linking metabolic and immune pathways relevant to DKD progression. Further research is needed to define stage-specific miRNA signatures, improve delivery systems, and develop personalized therapeutic approaches. Modulation of miRNA expression represents a promising strategy to slow DKD progression and improve patient outcomes. Full article

Stroke poses a serious threat to human health, while there are very few drugs that can directly alleviate ischemia/reperfusion injury and improve the prognosis. Studies have shown that small-molecule activators of aldehyde dehydrogenase 2 (ALDH2) have the potential to become novel therapeutic drugs for ischemic stroke. In this study, through the systematic structural optimization of novel N-benzylaniline-based ALDH2 activators obtained from our previous virtual screening, ALDH2 activators with improved water solubility and activity were obtained. Among them, compound D10 exhibits the best activity, with a maximum activation fold reaching 114% relative to Alda-1. And the water solubility of its hydrochloride salt D27 was increased by more than 200-fold. The intravenous injection of this compound can significantly reduce the infarct area in the rat model of cerebral infarction compared with the model group. This study lays a good foundation for the future research on ALDH2 activators used in the treatment of stroke. Full article

Rabies, a viral encephalitis caused by rabies virus (RABV), is 100% fatal upon the onset of symptoms. Effective post-exposure prophylaxis (PEP) measures are available, but they are often difficult to access in low-income countries. WHO estimates about 59,000 deaths due to rabies globally, and the majority are contributed by developing countries. Hence, developing drugs for the treatment of post-symptomatic rabies is an urgent and unmet demand. It is worth noting that previous efforts regarding antiviral strategies, such as small-interfering RNA, antibodies and small-molecule inhibitors, against the rabies virus have failed to show efficacy in pre-clinical studies, especially when the virus has reached the central nervous system (CNS). Therefore, drug repurposing seems to be an alternative tool for the development of new anti-rabies drugs. We validated and used a high-throughput, FITC-conjugated antibody-based flow cytometry assay to expedite the identification of repurposable new drug candidates against the RABV. The assay was validated using ribavirin and salinomycin as reference compounds, which showed EC50 values of 10.08 µM and 0.07 µM, respectively. We screened a SelleckChem library comprising 3035 FDA-approved compounds against RABV (CVS-11) at 10 µM concentration. Five compounds (clofazimine, tiamulin, difloxacin, harringtonine and homoharringtonine) were active against RABV, with greater than 90% inhibition. Homoharringtonine (HHT) identified in the present study is active against laboratory-adapted RABV (CVS-11) and clinical isolates of RABV, with an average EC50 of 0.3 µM in both BHK-21 and Neuro-2a cell lines and exhibits post-entry inhibition. Full article

The increasing diversity and escalating drug resistance of bacterial pathogens have significantly compromised the efficacy of conventional antimicrobial agents, creating formidable challenges in modern infection control. These developments underscore the critical need for innovative therapeutic strategies to address the persistent global health burden posed by microbial resistance. While metal-based compounds have been extensively studied for their anticancer properties in clinical applications, their potential in antimicrobial contexts remains relatively underexplored. This review systematically elaborates on the structure-activity relationship of metal complexes, with a focus on the unique characteristics of metal drugs that differ from organic small molecules. These drugs can overcome drug resistance through various mechanisms (such as generation of reactive oxygen species and penetration of biological membranes). Understanding these mechanisms provides a crucial basis for guiding ligand design and the development of delivery systems. Full article

Background and Objective: Dysregulated tyrosine kinase signaling is a central driver of tumorigenesis, metastasis, and therapeutic resistance. While tyrosine kinase inhibitors (TKIs) have revolutionized targeted cancer treatment, identifying compounds with optimal bioactivity remains a critical bottleneck. This study presents a robust machine learning framework—leveraging deep artificial neural networks (dANNs), convolutional neural networks (CNNs), and structural molecular fingerprints—to accurately predict TKI bioactivity, ultimately accelerating the preclinical phase of drug development. Methods: A curated dataset of 28,314 small molecules from the ChEMBL database targeting 11 tyrosine kinases was analyzed. Using Morgan fingerprints and physicochemical descriptors (e.g., molecular weight, LogP, hydrogen bonding), ten supervised models, including dANN, SVM, CatBoost, and CNN, were trained and optimized through a randomized hyperparameter search. Model performance was evaluated using F1-score, ROC–AUC, precision–recall curves, and log loss. Results: SVM achieved the highest F1-score (87.9%) and accuracy (85.1%), while dANNs yielded the lowest log loss (0.25096), indicating superior probabilistic reliability. CatBoost excelled in ROC–AUC and precision–recall metrics. The integration of Morgan fingerprints significantly improved bioactivity prediction across all models by enhancing structural feature recognition. Conclusions: This work highlights the transformative role of machine learning—particularly dANNs and SVM—in rational drug discovery. By enabling accurate bioactivity prediction, our model pipeline can effectively reduce experimental burden, optimize compound selection, and support personalized cancer treatment design. The proposed framework advances kinase inhibitor screening pipelines and provides a scalable foundation for translational applications in precision oncology. By enabling early identification of bioactive compounds with favorable pharmacological profiles, the results of this study may support more efficient candidate selection for clinical drug development, particularly in regards to cancer therapy and kinase-associated disorders. Full article

Human topoisomerase III beta (hTOP3B) is a unique and important enzyme in human cells that plays a role in maintaining genome stability, affecting cellular aging, and potentially impacting viral replication. Its dual activity on both DNA and RNA makes it a valuable target for therapeutic interventions. hTOP3B has been shown to be required for the efficient replication of certain positive-sense ssRNA viruses including Dengue. We performed in silico screening of a library comprising drugs that are FDA-approved or undergoing clinical trials as potential drugs to identify potential inhibitors of hTOP3B. The topoisomerase activity assay of the identified virtual hits showed that bemcentinib, a compound known to target the AXL receptor tyrosine kinase, can inhibit hTOP3B relaxation activity. This is the first small molecule shown to inhibit the complete catalytic cycle of hTOP3B for the potential interference of the function of hTOP3B in antiviral application. Additional small molecules that share the N⁵,N³-1H-1,2,4-triazole-3,5-diamine moiety of bemcentinib were synthesized and tested for the inhibition of hTOP3B relaxation activity. Five compounds with comparable IC₅₀ to that of bemcentinib for the inhibition of hTOP3B were identified. These results suggest that the exploration of tyrosine kinase inhibitors and their analogs may allow the identification of novel potential topoisomerase inhibitors. Full article

Zinc hydroxide has been reported as an effective precipitating reagent for removing proteins in biological samples. This procedure is quite effective for removing interfering proteins before the chromatographic separation of small organic compounds. However, preliminary data suggested that also some small molecules could precipitate together with proteins and zinc hydroxide. Therefore, herein it is reported a study on a panel of drugs having different chemical structures. The results suggest that the common trait of organic molecules coprecipitating with zinc hydroxide is to have acidic groups, while neutral or basic molecules are not affected by zinc hydroxide precipitation. Such observations were consistent with some analyses conducted on hydroalcoholic extracts prepared from natural edible materials such as green tea. In such matrices, a quantitative coprecipitation of polyphenols was obtained upon inducing the precipitation of zinc hydroxide, while alkaloids such as caffeine remained selectively isolated in the supernatants. Interestingly, the compounds coprecipitated with zinc hydroxide can be easily and quantitatively recovered as well, just by redissolving the precipitate. These findings open potential applications for the isolation of specific classes of compounds from crude natural extracts and for the use of zinc hydroxide to remove interfering compounds before chromatographic analyses. Full article