This study aimed to investigate novel therapeutic approaches for Alzheimer's disease (AD) by targeting the Transforming Growth Factor-β (TGF-β) pathway using hybrid compounds derived from oxymatrine and amino acids. AD remains a significant challenge in neurodegenerative disorders, necessitating innovative treatments that can mitigate its devastating effects. The TGF-β pathway has been implicated in AD pathogenesis, making it a promising target for therapeutic intervention. The objective of this study was to synthesize and evaluate the anti-AD activity of hybrid molecules combining oxymatrine with different amino acids. These compounds were designed to enhance blood-brain barrier permeability and selectively modulate TGF-β signaling. Hybrid compounds were synthesized based on molecular docking studies. Characterization of synthesized compounds was performed using thin-layer chromatography (TLC), infrared spectroscopy (IR), and nuclear magnetic resonance (NMR) spectroscopy. Anti-AD activity was assessed using an AD rat model induced by a high-cholesterol diet, employing behavioral tests (radial arm maze and Hebb's Williams maze) and biochemical assays to measure Aβ and TGF-β levels. All hybrid molecules exhibited significant anti-AD activity, with compound 3B demonstrating the highest efficacy at a dose of 100 mg/kg. Biochemical analyses revealed modulation of Aβ and TGF-β levels, indicating the compounds' potential therapeutic effects against AD. This study unveils a new class of hybrid compounds derived from oxymatrine and amino acids that effectively target the TGF-β pathway, offering promising therapeutic potential for AD. These compounds demonstrate neuroprotective properties, suggesting they may mitigate ADrelated pathology, including tau deposition, synaptic dysfunction, and cognitive decline.

Diabetes is a highly common chronic disorder of the endocrine system that affects 529 million people globally. Dysfunction of β-cells, impaired insulin secretion, and hyperactive α- cells are the primary reasons for this disease. Conventional therapy might fail since some drugs require specific conditions to achieve their maximum efficacy. Metallopharmaceutics is defined as the branch of pharmaceutics in which the activity of a compound is enhanced by complexation with a suitable metal. Several macrometals, such as copper, and micrometals, such as selenium, are used in this field and combined with organic ligands. Novel synthesis approaches, such as ultrasonication, have been employed to reduce the reaction time and increase the overall product yield. Even if spectral studies confirm the complexation of metals with chemically synthesized organic ligands, less medical evidence of antidiabetic activity exists. Hence, antidiabetic drugs, such as insulin, dapagliflozin, etc., exhibit better pharmacodynamics as metallocomplexes than the drugs themselves and have been chosen pharmacologically to act as ligands. Some metallocomplexes are multidimensional because they are not only antidiabetic but also antineoplastic. Thus, metallopharmaceuticals can lead to significant breakthroughs, not only in the treatment of diabetes but also in the pharmacotherapy of various diseases and disorders.

Sodium‒glucose cotransporter 2 (SGLT2) inhibitors have become viable therapeutic options for treating breast cancer. Diabetes is the primary source of these medications. This research examines how SGLT2 blockers can induce apoptosis, decrease the amount of glucose taken up by cancer cells, and modify key signaling pathways, such as the PI3K/AKT/mTOR and MAPK pathways. The effects of four different SGLT2 inhibitors on breast cancer cells were investigated in this study via both in vitro and in vivo testing: dapagliflozin, ipragliflozin, canagliflozin, and empagliflozin. The potential synergistic effects of these inhibitors with conventional chemotherapy medications were also examined. This review explores the complex relationship between SGLT2 inhibitors and breast cancer, examining how drugs interact with this disease at various stages of its development. Additionally, this study highlights how SGLT2 inhibitors may be used in conjunction with precision medicine techniques to treat breast cancer. Although encouraging outcomes have been noted, this review highlights the necessity of additional clinical studies to evaluate the safety and effectiveness of SGLT2 blockers in patients with breast cancer, in addition to ongoing research into the molecular mechanisms underlying the anticancer effects of these drugs.

Alzheimer is a progressive neurodegenerative disease characterized by change in brain that led to the buildup of specific proteins, ultimately causing brain shrinkage and the death of brain cells. It is the leading cause of dementia, manifesting as a gradual decline in memory, cognitive abilities, behavior, and social functioning, which severely impairs a person's ability to carry out daily activities. The complexity of Alzheimer's poses significant challenges to modern medicine, making the development of new therapeutic strategies crucial. Indole derivatives, with their broad spectrum of pharmacological activities, have garnered attention for their potential in treating Alzheimer's disease. This review provides a detailed summary of recent progress in developing indole derivatives as therapeutic agents for Alzheimer's disease. It thoroughly examines the pharmacological properties of various indole derivatives, including their mechanisms of action. These compounds have been shown to influence several processes, such as amyloid-beta aggregation, MAO inhibition, AChE and BuChE inhibition. Furthermore, this review discusses the structural modifications of indole derivatives designed to improve their therapeutic effectiveness.

Rheumatoid arthritis (RA) is the most prevalent form of inflammatory arthritis, characterized by chronic inflammation of the synovial membrane. Current therapeutic options have advanced RA management significantly, yet limitations like adverse effects and treatment resistance underscore the need for novel therapeutic agents. Recent advancements have introduced promising candidates, including BTK inhibitors, JAK inhibitors, TLR4 inhibitors, COX-2 inhibitors, and LOX inhibitors, which target specific pathways implicated in RA pathogenesis. This manuscript provides a comprehensive overview of RA, emphasizing its pathophysiology, diagnostic approaches, and therapeutic strategies. Special attention is given to the structural-activity relationships (SAR) and mechanistic insights underlying emerging pharmacological interventions. Moreover, current challenges and future directions in RA drug discovery are critically examined, highlighting innovative wet-lab approaches to address unmet clinical needs.

Neuropathic pain (NP) frequently coexists with major depressive disorder (MDD), sharing common molecular pathways that affect brain function. Targeting these molecular pathways through multi-target herbal remedies, such as the extract from Corydalis rhizoma (CR), may offer new therapeutic strategies; however, the variability in composition and potential toxicity of natural products, as seen with mishandled herbs, presents significant challenges in the U.S. herbal medicine landscape. This study utilized network pharmacology and molecular docking to explore the mechanisms linking NP and MDD via the herbal remedy CR, while addressing the challenges posed by natural product variability and potential toxicity. We identified potential bioactive components of CR using various databases and assessed their pharmacological properties and toxicity. Common targets of CR's bioactive components for treating MDD/NP were identified, followed by protein-protein interaction (PPI) analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to select potential pathways. Additionally, docking analyses evaluated the binding affinity between ligands and receptors, while molecular dynamics (MD) simulations were conducted to assess the stability and interactions of these complexes over time. We identified 24 active ingredients in CR, primarily alkaloids and phytosterols, with favorable pharmacokinetics, including the ability to cross the blood-brain barrier and low toxicity at lower doses. These ingredients were associated with 125 genes and five key therapeutic targets- AKT1, CASP3, ESR1, BCL2, and MAPK3-integral to synaptic signaling and neurotransmitter activity. The molecular docking analysis revealed significant interactions, with CASP3 and tetrahydrocorysamine demonstrating the highest binding affinity at -9.6 kcal/mol, suggesting their potential for neuroprotection, antidepressant effects, and pain relief. MD simulations confirmed the strong binding affinity predicted by docking, particularly for the CASP3- THC complex. This study highlights the therapeutic potential of CR's active components in treating MDD/NP through a comprehensive framework of network pharmacology, molecular docking, and MD simulations. While the findings are promising, further preclinical research is necessary to validate the safety, efficacy, and mechanisms of action of these compounds.

Colorectal cancer (CRC), the world's third leading cause of death, can be caused by a variety of reasons, one of which is a valine-to-glutamate mutation at position 600 in the BRAF gene. Nonetheless, the prognosis of patients with BRAF mutations remains poor, necessitating additional research in this field. This work aims to recognize and validate innovative and effective BRAF inhibitors. A merged-featured ligand-based pharmacophore model was validated and screened against various external databases. The pharmacokinetic and toxicological characteristics of the 102 hits were analyzed, and the appropriate ligands were docked against BRAF protein. The top four protein-ligand complexes with the lowest binding energies were chosen, and their molecular dynamic (MD) simulation studies were accomplished. The finest complex selected has a Root Mean Square Deviation (RMSD) value of 2.229A0 and a Radius of gyration (RoG) value of 25.770A0. The LC50 of the best ligand was experimentally calculated to be 102.83 μg/ml. The ligand was found to destroy CRC cells, but it did not affect normal non-cancerous cells much. This work thus proposes 3-(6,7-dimethoxy-3,4-dihydroisoquinoline-2-carbonyl)-N- (2-methoxyphenyl)benzenesulphonamide as a potential BRAF V600E inhibitor for the CRC treatment.

Jieyu Fuwei Powder (JFP) is a modified prescription of Chinese medicine used to treat functional dyspepsia (FD). However, its components and how it works are still unknown. Identifying the active ingredients of JFP and understanding its therapeutic mechanism for FD were the objectives of the study. The compounds present in JFP were analyzed using the UPLC-Q-TOF-MS/MS technique. Potential targets for compounds and diseases were obtained from Swiss Target Prediction and GeneCards databases. A PPI network was created using the STRING database to identify key targets. The Metascape database was utilized for conducting GO and KEGG pathway enrichment analyses. Molecular docking identified active compound-target interactions, validated by FD zebrafish models. In total, 65 compounds were identified from JFP and the key active ingredients were Tangeretin, Obovatol, Magnolignan C, Magnolol, Randaiol, Magnolignan A, Luteolin, and Naringenin. The PPI network was constructed, identifying five core targets: SRC, STAT3, PIK3R1, PIK3CA, and MAPK3. JFP primarily regulates anti-depression, promotes gastrointestinal peristalsis, and influences inflammation, according to the enrichment analysis of GO and KEGG pathways. The molecular docking results indicated a strong binding affinity between these five targets and their corresponding compounds. Therefore, the MAPK and PI3K-Akt signaling pathways are important in JFP's effects on FD pathology. Experiments using the zebrafish model confirmed that JFP and its main components could enhance gastrointestinal motility, thus demonstrating the effectiveness of the network pharmacology screening strategy. The study revealed the active ingredients and mechanisms of JFP in treating FD, supporting its clinical application.

Cancer and neurological diseases are among the major causes of mortality and disabilities around the world. Neurological diseases are accounting for 12% of all fatalities. The major challenge in treating these diseases is the effective drug delivery to the disease site, where traditional approaches fail to give satisfactory results. As nanoparticles have many major benefits over conventional drug delivery, they have become the preferred method for drug delivery. The main objective of this review is to discuss the recent advancements and the role of nanoparticles in the effective treatment of cancer and neurodegenerative diseases. Properties of nanoparticles, such as size, shape, and surface, utilized in medical therapy showed a promising impact on the efficacy of nano-drug transportation and, as a result, therapeutic efficiency. Many potentially helpful drugs for neurological disorders cannot enter the brain in therapeutic concentrations because of the blood-brain barrier, while nanoparticles can pass through it because of their size-specific properties. Besides contributing to bioavailability and half-life, nanoparticle surface properties are also important. The use of nanotechnology in medicine has demonstrated its importance in the field of medicine and led to the development of novel therapeutic alternatives for neurological disorders and cancer. The various types of nanoparticles, like liposomes, polymeric micelle, solid nanoparticles, quantum dots, and nanogels, have shown promising results in in-vitro models and clinical investigations. This review provides a concise description of the recent implications of various nanoparticles for the treatment of cancer and neurodegenerative disorders. It also helps in concise discussion of future opportunities of applications and challenges related to the production, efficacy, and safety of nanoparticles.

The field of drug design has evolved from conventional approaches relying on empirical evidence to advanced approaches such as Computer-Aided Drug Design (CADD). It aids in intricate phases of drug discovery, such as target discovery, lead optimization, and clinical trials, establishing a safe, rapid, and cost-effective system. Structure based drug design (SBDD), Ligand based drug design (LBDD), and Pharmacophore modelling, being the most utilized techniques of CADD, play a major role in establishing the road map necessary for the discovery. Artificial intelligence (AI) and Machine learning (ML) have improved the field with the incorporation of big data and, thereby, enhancing the efficacy and accuracy of the CADD. Deep Learning (DL), a part of AI helps in processing complex and non-linear data and thereby decreases complexity, increases resource utilization and enhances drug-target interaction prediction. These approaches have revolutionized healthcare by enhancing diagnostic precision and predicting the behavior of drugs. Currently, AI/ML approach has become crucial for rapidly discovering novel insights and transforming healthcare areas lie diagnostics, clinical research, and critical care. In the case of the drug development area, techniques like PBPK modeling and advanced nano-QSAR enhance drug behavior understanding and predict nano material toxicity if any, leading to safe and effective therapeutic predictions and interventions. The advancement of AI/ML techniques will bring accuracy, efficacy, and more patient-tailored responses to the drug development field.