Dioscorea bulbifera (DB) and Hemidesmus indicus (HI) are widely recognized ethnomedicinal plants in Ayurveda that are traditionally used for managing metabolic disorders, oxidative stress, and diabetes. The present study aimed to establish a reliable comparative phytochemical profile of methanolic extracts of DB (tuber) and HI (root) using integrated High-Performance Thin-Layer Chromatography (HPTLC) and High-Performance Liquid Chromatography (HPLC), using rutin and gallic acid as marker flavonoids and phenolic compounds, respectively. Preliminary qualitative phytochemical screening confirmed the presence of phenols and flavonoids in both extracts; alkaloids were detected exclusively in HI, and terpenoids were absent in both plants. HPLC based quantitative analysis revealed marked differences in flavonoid and phenolic contents between the two species. The HI extract exhibited a prominent rutin peak at a retention time of 2.810 min with a relative concentration of 97.14%, whereas DB showed a corresponding peak at 2.821 min with a significantly lower relative concentration of 50.71%, indicating nearly a two-fold higher flavonoid abundance in HI compared to DB. HPTLC fingerprinting further demonstrated distinct and reproducible chromatographic bands corresponding to the marker compounds in both plant extracts, confirming their characteristic phenolic and flavonoid compositions. Overall, the integrated HPTLC–HPLC analysis provides a robust and reproducible framework for the authentication, standardization, and comparative evaluation of DB and HI, while the observed quantitative differences underscore their differential therapeutic potential, particularly regarding antidiabetic and antioxidant applications.

Chikungunya virus (CHIKV) remains a major global health threat due to its rapid transmission, debilitating arthralgia, and absence of approved antiviral therapy. This study employed a structure-based drug repurposing strategy targeting key viral proteins (E1, E2, NSP2, and P62) and the host entry receptor MXRA8, which play essential roles in viral attachment, membrane fusion, replication, and virion maturation. Clinically approved antiviral and immunomodulatory compounds were systematically screened using molecular docking performed through AutoDock Vina, PyRx 0.8, Discovery Studio, and UCSF Chimera to identify potential inhibitors with favorable binding affinities and interaction profiles. Sixteen drugs were evaluated for their binding interactions, ADMET behavior, and toxicity characteristics. Paritaprevir exhibited the highest affinity toward the E1/E2 protease complex (–10.8 kcal/mol), while Ledipasvir demonstrated strong multi-target potential with notable affinity for E1/E2 (–10.7 kcal/mol) and NSP2 (–9.3 kcal/mol). Eptifibatide acetate showed the strongest binding to MXRA8 (–10.2 kcal/mol), forming extensive hydrogen bond networks, and Sorafenib displayed the best interaction with SQSTM1 (–8.8 kcal/mol) through unique halogen-mediated stabilization. ADMET profiling revealed that Rimantadine, Ruxolitinib, Naringenin, and silymarin derivatives possessed favorable bioavailability and safety margins, whereas Obatoclax exhibited the highest predicted toxicity. Collectively, these findings highlight Paritaprevir, Ledipasvir, and Eptifibatide acetate as potent multi-target antiviral candidates, while Rimantadine emerges as a low-risk repurposing option. This comprehensive target-centric screening provides mechanistic insights and establishes a strong foundation for further optimization, in vitro validation, and therapeutic development against CHIKV infections.

The present study evaluated the antiulcer potential of ethanolic extracts of the aerial parts of Tinospora cordifolia (EETC) and the stem bark of Psidium guajava (EEPG) using a pyloric ligation–induced gastric ulcer model in albino Wistar rats. Gastric ulcers were induced by pyloric ligation, a well-established method for assessing ulcerogenesis and gastric acid secretion. The extracts were administered orally as a 1:1 combination of EETC and EEPG at doses of 200 and 400 mg/kg, while ranitidine (150 mg/kg) served as the standard drug. Gastric volume, pH, free acidity, total acidity, bound acidity, ulcer index, gastric lesion length, ulcer severity score, and ulcer number were evaluated, along with percentage protection and percentage inhibition. Treatment with the combined extract produced a dose-dependent reduction in gastric volume and acidity, with a concomitant increase in gastric pH. The 400 mg/kg dose showed pronounced gastroprotective effects compared to the ligation control (P < 0.01). Both dose levels significantly reduced ulcer index, ulcer number, and gastric lesion length, showing comparable efficacy to ranitidine. These findings indicate that the combined ethanolic extracts of Tinospora cordifolia and Psidium guajava exert protective effects against pyloric ligation–induced gastric ulcers, supporting their potential use in ulcer management.

Background and objecive: Caralluma fimbriata Wall, a succulent medicinal plant of the Apocynaceae family, has been traditionally utilized in various therapeutic applications including metabolic disorders, appetite regulation, and diabetes management. Despite its ethnomedicinal importance, comprehensive analytical characterization of its bioactive constituents remains limited. This investigation aimed to conduct systematic phytochemical screening and chromatographic profiling of C. fimbriata extracts to identify and characterize the major secondary metabolites responsible for its therapeutic activities.
Methods: Fresh plant specimens were collected, authenticated, and processed for extraction using methanol and aqueous solvents. Qualitative phytochemical screening was performed using standard chemical tests. High-performance liquid chromatography (HPLC) analysis was conducted using a C18 column with acetonitrile-water mobile phase system and multi-wavelength detection at 210, 230, 254, and 280 nm.
Results: Phytochemical analysis revealed the presence of alkaloids, flavonoids, phenolic compounds, tannins, saponins, terpenoids, steroids, and glycosides with differential solvent-dependent extraction patterns. HPLC chromatographic analysis demonstrated distinct retention profiles with major peaks identified at 5.557, 7.923, 12.047, 15.047, 16.736, 20.802, 23.183, 24.731, 33.760, 38.118, and 43.925 minutes, indicating the presence of diverse bioactive compounds with varying polarities.
Conclusion: The comprehensive analytical profile confirms the chemical diversity of C. fimbriata, providing scientific validation for its traditional therapeutic applications. The identified secondary metabolites, particularly pregnane glycosides, flavonoids, and phenolic compounds, may contribute to the plant''''s reported anti-obesity, antidiabetic, and cardioprotective effects. These findings establish a foundation for standardization, quality control, and further pharmacological investigations of this medicinally important species.

Magnetic iron oxide nanocarriers (MIONs) have gained significant attention in drug delivery due to their unique magnetic responsiveness, biocompatibility, and ability to enable site-specific targeting. This review summarizes recent advances in the design and biomedical applications of MION-based drug delivery systems. Particular emphasis is placed on the structural characteristics of MIONs, including particle size, morphology, and surface chemistry, which critically influence magnetic behavior, biodistribution, and drug release performance. Common synthesis approaches such as co-precipitation, thermal decomposition, hydrothermal, and microemulsion methods are discussed, along with surface functionalization strategies using polymers, lipids, and targeting ligands to improve stability and targeting efficiency. Key mechanisms enabling targeted and controlled drug delivery, including magnetic guidance, magneto-thermal release, and stimuli-responsive systems (pH, temperature, and magnetic field), are also highlighted. The review further outlines major biomedical applications of MIONs in targeted chemotherapy, gene delivery, antimicrobial therapy, and theranostic platforms that combine diagnosis and treatment. Emerging applications in neurological and cardiovascular therapies are also discussed. Despite significant progress, challenges such as toxicity concerns, aggregation, and limited clinical translation remain. Future perspectives focus on the integration of artificial intelligence, magnetic biosensing technologies, hybrid nanoplatforms, and green synthesis approaches to develop safer and more efficient magnetic nanocarriers for next-generation targeted drug delivery.

The electronic structure and singlet–triplet characteristics of a series of divalent silicon species, SiR₂ (R = H, F, Cl, Br, Me, Et, iPr, tBu, Ph), were systematically investigated using density functional theory (DFT). Geometry optimizations and frequency analyses confirmed all stationary points as true minima. The effects of substituents on structural parameters, energetics, charge distribution, polarizability, and spectroscopic signatures were analyzed in both singlet and triplet states. Singlet–triplet energy gaps corrected for zero-point energy reveal a pronounced preference for the singlet state across the entire series, with strong substituent dependence. Frontier molecular orbital analysis and global reactivity descriptors highlight substantial variations in electrophilicity and chemical softness induced by both substituent identity and spin state. Molecular electrostatic potential (MEP) maps clearly demonstrate the ambiphilic nature of singlet silylenes, characterized by well-separated electrophilic and nucleophilic regions, in contrast to the more diffuse electronic distribution of triplet species. Furthermore, calculated ²⁹Si NMR parameters and NBO analyses provide direct spectroscopic and orbital-level fingerprints distinguishing the two spin states. Overall, this study offers a comprehensive substituent-controlled framework for understanding singlet–triplet electronic signatures in silylenes, providing valuable insights for their reactivity and experimental identification.

Luteolin-7-rutinoside (L7R), a glycosylated luteolin derivative, has shown promising anticancer activity against oral cancer, particularly oral squamous cell carcinoma (OSCC). Its multifaceted mechanism targets key signaling pathways, such as PI3K/AKT, MAPK, and TNF, causing apoptosis, inhibiting metastasis, and reducing inflammation. L7R also has the potential to synergize with conventional therapies, increasing the efficacy of drugs, such as cisplatin. Despite bioavailability issues, advances in nanotechnology may overcome these obstacles. L7R is a promising candidate for future clinical trials, providing a comprehensive approach to treating oral cancer by modulating multiple oncogenic targets.

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, is characterized by amyloid-beta (Aβ) plaques, neurofibrillary tangles (NFTs), oxidative stress, and neuroinflammation. Current therapies offer only symptomatic relief, necessitating novel multi-target approaches. Chalcones, a class of bioactive flavonoids with an α,β-unsaturated ketone backbone, exhibit potent anti-amyloidogenic, anti-tau, antioxidant, and anti-inflammatory properties, positioning them as promising neuroprotective agents. This review comprehensively examines chalcones’ mechanisms in AD, including: (1) inhibition of Aβ aggregation and destabilization of fibrils through direct binding and metal chelation; (2) suppression of tau hyperphosphorylation via modulation of GSK-3β and PP2A; (3) scavenging of reactive oxygen species (ROS) and activation of the Nrf2 antioxidant pathway; (4) attenuation of neuroinflammation by blocking NF-κB and NLRP3 inflammasome signaling; and (5) enhancement of autophagy to clear pathogenic proteins. Key chalcones such as xanthohumol, isoliquiritigenin, and butein demonstrate efficacy in preclinical models, improving cognitive function and reducing pathology. However, challenges such as poor bioavailability, limited blood-brain barrier penetration, and insufficient clinical data hinder translation. Strategies to overcome these limitations—including structural optimization, nanoparticle delivery, and prodrug design—are discussed. By integrating traditional knowledge with modern pharmacology, chalcones may offer a viable multi-target strategy to modify AD progression. Future research should prioritize pharmacokinetic refinement, biomarker development, and rigorous clinical trials to validate their therapeutic potential.

Oral squamous cell carcinoma (OSCC), a prevalent and aggressive malignancy, presents significant challenges owing to the poor prognosis, limited treatment efficacy, and adverse effects of conventional therapies. This review highlights rutin, a natural flavonoid abundant in Ruta graveolens and various plant sources, and has recently emerged as a promising anticancer agent against OSCC. Owing to its potent antioxidant, anti-inflammatory, and pro-apoptotic properties, rutin mitigates oxidative stress, a key factor in OSCC progression, and modulates crucial signaling pathways involved in cancer cell proliferation and survival. In vitro and in vivo studies have shown that rutin inhibits OSCC cell lines, such as CA9-22 and KB-1 through autophagy induction, suppression of NF-κB and TNF-α, and downregulation of TGF-β/SMAD2 signaling. Moreover, the ability of rutin to enhance enzymatic antioxidants and reduce tumor marker levels underscores its therapeutic potential. Nanoformulations of rutin further improved its bioavailability and anticancer efficacy. Given its multi-targeted actions, minimal toxicity, and cost-effectiveness, rutin is a compelling natural compound with the potential to complement or replace conventional therapies for OSCC management.

The use of computational technology has greatly sped up the development of drug delivery systems, allowing for more accurate, effective, and targeted therapeutic treatments. This study provides an extensive summary of the latest developments in computational methodologies that have transformed nanoscale and targeted medication delivery. The article starts with basic methods such as molecular dynamics simulations, quantum mechanical methods, and machine learning algorithms. It then goes into detail about how important these methods are for modeling molecular interactions, predicting pharmacokinetic profiles, and improving nanocarrier architectures. The design and in silico assessment of diverse nanocarriers, encompassing lipid-based, polymeric, inorganic, and hybrid systems, as well as their behaviour in biological contexts, are of particular focus. The paper also looks at cutting-edge computational methods for targeted administration, such as ligand-receptor simulations, smart nanocarriers that respond to physiological signals, and AI-driven prediction models. Combining pharmacokinetic/pharmacodynamic modeling, ADMET profiling, and virtual human simulations gives us a better idea of how well and safely drugs work in the body. Computational medication delivery has the potential to change the game, but there are still significant problems to solve, such as how to understand models, the quality of the data, and how to address ethical considerations. Additionally, the present study discusses about new developments in next-generation drug delivery research, such as personalized medicine, digital twin models, and the blending of AI and bioinformatics. This synthesis seeks to function as a significant resource for researchers and practitioners aiming to utilize computational techniques in the systematic design of efficient and secure drug delivery systems.

Evodiamine and Camptothecin are promising therapeutic agents, with distinct pharmacological profiles. Evodiamine, a bioactive alkaloid, exhibits anti-inflammatory, anticancer, and anti-obesity properties, whereas camptothecin, a topoisomerase I inhibitor, is widely recognized for its potent anticancer activity, particularly in the treatment of solid tumors. Their diverse mechanisms of action render them valuable candidates for drug development. Therefore, we investigated these two promising candidates as potential Cyclin-dependent Kinase (CDK) inhibitors to identify novel targets for cancer treatment. In this study, molecular docking was performed using the crystal structure of CDK (PDB ID: 2QKR) to validate its binding potential. Here, we explored compounds for ADMET property calculations and molecular docking analysis. Both compounds exhibited potent binding interactions with CDK. Evodiamine and Camptothecin displayed docking score of -10.8 and -10.4 kcal/mol, respectively, whereas camptothecin formed three conventional hydrogen bonds with the target, claiming its potential power to cause conformational changes in receptor activity. We concluded that these compounds have enough potential to be claimed as potent CDK inhibitors, which can be explored using more in vitro and in vivo models.

Cryptolepine and tryptanthrin are bioactive alkaloids derived from medicinal plants and are widely recognized for their antimalarial, antimicrobial, anti-inflammatory, and anticancer properties. Given the therapeutic need for safer and more effective α-glucosidase inhibitors for Type II diabetes management, the antidiabetic potential of these compounds was explored using a comprehensive computational framework. The present study integrated ADMET screening, molecular docking, and structural interaction analysis to systematically evaluate their drug-likeness, pharmacokinetic behavior, and binding affinity toward α-glucosidase. ADMET profiling revealed that both cryptolepine and tryptanthrin possess favorable physicochemical and pharmacokinetic characteristics, including acceptable lipophilicity, high gastrointestinal absorption, and good bioavailability. Molecular docking demonstrated strong binding affinities, with cryptolepine and tryptanthrin exhibiting binding free energies of −8.1 kcal/mol and −8.3 kcal/mol, respectively, both exceeding the native ligand. Cryptolepine formed multiple hydrophobic and carbon–hydrogen interactions, whereas tryptanthrin showed extensive aromatic interactions, indicating stable accommodation within the enzyme’s active cavity. These results suggest that their structural features and interaction patterns significantly contribute to α-glucosidase inhibition. This study highlighted the novelty of using an integrated computational approach to rapidly assess natural compounds as viable therapeutic candidates. By combining ADMET prediction with a detailed docking evaluation, the workflow provides a robust preclinical assessment platform that minimizes the experimental burden while maximizing predictive accuracy. Based on their strong in silico performance, cryptolepine and tryptanthrin have emerged as promising lead molecules for antidiabetic development. Future investigations will include in vitro α-glucosidase inhibition assays and biological evaluations to experimentally validate their predicted therapeutic potential and advance their translational relevance.

Proctological disorders, including hemorrhoids, anal fissures, and proctitis, are common anorectal conditions marked by inflammation, bleeding, and mucosal damage that significantly impact patients'' quality of life. Conventional treatments often present challenges such as poor mucosal retention, frequent dosing, irritation, and systemic side effects. Herbal emulgels—hybrid drug delivery systems combining emulsions and gels—offer a promising alternative by enabling localized, non-invasive, and sustained delivery of herbal bioactives. These formulations enhance drug penetration and retention, improving therapeutic efficacy.”. This review highlights the phytotherapeutic potential of key herbal ingredients like Hamamelis virginiana (witch hazel), Calendula officinalis, Aloe vera, Curcuma longa (turmeric), Melaleuca alternifolia (tea tree oil), Matricaria chamomilla (chamomile), and Azadirachta indica (neem), known for their anti-inflammatory, antimicrobial, analgesic, and wound-healing properties. The manuscript further discusses formulation strategies, including emulsification techniques, selection of gelling agents, penetration enhancers, and preservatives. Critical evaluation parameters—such as pH, viscosity, spreadability, drug content uniformity, in vitro release, antimicrobial activity, and skin compatibility—are outlined. Advances in nanoemulgels, phytosome-based formulations, and patient-centric attributes (e.g., non-irritant, odorless designs) are addressed alongside regulatory considerations and standardization challenges. While preclinical studies support the efficacy of herbal emulgels in managing anorectal conditions, robust clinical trials and regulatory validation are essential to ensure their safety, efficacy, and broader therapeutic adoption. The integration of modern drug delivery technologies with traditional herbal medicine offers a patient-friendly, effective solution for chronic proctological therapy.

Pyrazoline derivatives are a promising pharmacophore, as demonstrated by various biological applications. This work relies on computational and spectroscopic methods to synthesize, structurally characterize, and biologically evaluate novel pyrazoline derivatives, synthesizing novel pyrazoline derivatives and evaluating their anti-inflammatory and antioxidant activities using both in vitro and in silico methods. Pyrazoline derivatives (4a–4e) have been produced by cyclizing chalcones with acetylhydrazine hydrate. The compounds have been analyzed using FTIR, ¹H-NMR, ¹³C-NMR, and mass spectrometry. The hydrogen peroxide scavenging assay has been employed to measure antioxidant activity, while the egg albumin denaturation method has been utilized to assess anti-inflammatory activity. Pharmacokinetic profiling was conducted using Swiss ADME, and PyRx and Discovery Studio were used for molecular docking studies against human transthyretin (1DVX) and LsfA (6POW). Compound 4e showed the highest anti-inflammatory activity (54.12%, IC₅₀ = 40.68 µg/ml), while compound 4a exhibited the best antioxidant effect (IC₅₀ = 29.86 µg/ml). With docking scores ranging from -6.4 to -7.6 kcal/mol, compound 4b possessed the highest binding affinity (-7.6 kcal/mol). Oral bioavailability increased, in accordance with the Swiss ADME study. These findings suggest that the derived pyrazoline derivatives, especially 4a, 4b, and 4e, possess potent anti-inflammatory and antioxidant properties, making them potential candidates for further therapeutic research.

This study focuses on the development and optimization of a mucoadhesive buccal film incorporating chlorhexidine gluconate to enhance oral health outcomes. Recognizing the limitations of conventional oral drug delivery systems, this research explores mucosal drug delivery as an alternative, ensuring localized and sustained antimicrobial activity. The work includes an in-depth analysis of mucoadhesive mechanisms, pharmaceutical formulation strategies, and key evaluation parameters. The experimental framework assesses film properties, covering aspects such as swelling index, drug content, antimicrobial activity, and surface morphology using scanning electron microscopy. This study aims to contribute to effective oral healthcare solutions, emphasizing bio-adhesive drug delivery for improved therapeutic benefits.

Gout is a painful inflammatory condition caused by the accumulation of urate crystals in joints, typically resulting from elevated blood uric acid levels. Allopurinol is commonly used for long-term treatment and prevention of gout. However, its clinical efficacy is limited by poor solubility and bioavailability. This study aimed to develop and characterize solid lipid nanoparticles (SLNs) containing allopurinol (ALP-SLNs) to overcome these limitations. ALP-SLNs were prepared using the emulsification and low-temperature solidification method, employing Glycerol Monostearate (GMS) as the lipid matrix and Poloxamer 188 as the surfactant. Formulation and process parameters were optimized using Design Expert software. The physicochemical properties of the nanoparticles were evaluated, including particle size (PS), polydispersity index (PDI), zeta potential, and drug encapsulation efficiency (EE). The optimized formulation exhibited a particle size of 145.1 nm, a PDI of 0.212, a zeta potential of –21.70 mV, and an encapsulation efficiency of 97.33%. These results indicate successful fabrication of ALP-SLNs with desirable characteristics for enhancing allopurinol delivery.

Structure-Based Drug Design (SBDD) has emerged as a pivotal strategy in modern drug discovery, enabling the rational design of therapeutics through detailed understanding of biomolecular structures. This review presents a comprehensive overview of the fundamental principles, methodologies, and computational tools that underpin SBDD. The process begins with the determination of protein structures using techniques such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy, followed by molecular modeling and visualization using tools like PyMOL and Chimera. Molecular docking approaches, both rigid and flexible, are employed to predict ligand binding modes and affinities, while molecular dynamics (MD) simulations offer insights into the dynamic behavior of protein-ligand complexes. Advanced techniques such as quantum mechanics (QM) and hybrid QM/MM methods further enhance the accuracy of active site analysis and energy calculations. Pharmacophore modeling and virtual screening facilitate the identification of novel hits, whereas ADMET predictions support the optimization of drug-like properties early in the design process. The integration of artificial intelligence (AI) and machine learning (ML) has significantly accelerated and refined SBDD workflows, allowing for data-driven predictions and enhanced screening efficiency. Despite remarkable progress, challenges such as limited accuracy in scoring functions and computational cost persist. Future directions point toward leveraging quantum computing and next-generation AI models to overcome these limitations. This review underscores the synergistic role of computational chemistry and emerging technologies in shaping the future of rational drug design.

The integration of artificial intelligence (AI), particularly machine learning (ML), into medicine marks a significant breakthrough in drug discovery. AI acts as a powerful tool that bridges the gap between understanding diseases and identifying potential treatments. Traditional drug development is often costly, time-consuming, and prone to high failure rates. In recent years, however, AI has emerged as a transformative approach in the pharmaceutical industry, offering innovative solutions to these challenges. This review highlights the diverse roles of AI in drug discovery, including AI-assisted drug design, the identification of new drug candidates, and the advancement of novel AI methodologies. It examines the different stages of the drug discovery process—from disease identification and diagnosis to target selection, screening, and lead discovery. AI’s capacity to analyze vast datasets and detect hidden patterns plays a vital role in these stages, enhancing accuracy and efficiency in disease identification, drug development, and clinical trial management. AI is particularly important in accelerating drug development by significantly reducing both time and cost. Machine learning algorithms aid in experimental design, predicting drug metabolism and toxicity, and prioritizing lead compounds. This reduces the reliance on extensive and costly animal testing. Moreover, AI supports personalized medicine by analysing real-world patient data, enabling more effective treatments and improving patient adherence. Overall, this review provides a comprehensive overview of recent advancements in AI and its growing impact on drug discovery.