Current Trends in Biotechnology and Pharmacy

Investigation of Phytoconstituents in Curcuma caesia Rhizomes: Understanding their Potential for treating Urolithiasis through the Molecular Docking Study

Sanjeeb Kumar Sahoo — 2026-10-21

Urolithiasis (kidney stone disease) affects millions of people globally and often requires costly surgical intervention. Conventional treatments carry risks of recurrence and side-effects. So, the medicinal plants with anti-urolithiatic properties are of great interest due to their safety, accessibility, and multi-target mechanisms. Curcuma caesia (black turmeric) is widely used in traditional medicine for its anti-inflammatory, antioxidant, diuretic, and litholytic properties. Several phytoconstituents present Curcuma caesia include curcuminoids, essential oils (e.g., ar-turmerone, β-caryophyllene), and phenolics that may act on biochemical pathways involved in stone formation. For this study, the rhizomes of Curcuma caesia were collected, dried, powered and extracted with ethanol using Soxhlet apparatus. The presence of phytoconstituents in Curcuma caesia were identified and characterized by phytochemical analysis and spectral studies respectively. Further molecular docking study was conducted to assess therapeutic potential of phytochemicals towards urolithiatic property in comparison to standard drug (Hydrocholrthiazide). Hydrochlorothiazide is a thiazide diuretic commonly used to treat hypertension and edema. Interestingly, it also has a role in reducing calcium excretion, which can help prevent calcium-based stone formation in the urinary tract.

GC-MS Profiling and In-vitro Antidiabetic Activity of Leaf Extracts of Ravenala madagascariensis Sonn.

Sofiya MK — 2026-10-21

This study aimed to document the GC-MS profile and in-vitro α-amylase “and α-glucosidase” inhibitory activity of Ravenala madagascariensis Sonn. The shade-dried and powdered plant material after successive Soxhlet extraction with n-hexane and ethyl acetate was subjected to gas chromatography- mass spectrometry (GC-MS) analysis, followed by α-amylase and α-glucosidase inhibition using standard acarbose. Various bioactive compounds, including phytol, tritetracontane, squalene, tetratriacontane, γ-tocopherol and its ester derivative, with peak area percentages of 5.05, 5.94, 4.15, 14.96, 11.41, 43.93%, respectively, were recorded in n-hexane extract. The ethyl acetate extract also showed compounds including 2-Pentanone, 4-hydroxy-4-methyl derivative, 7,9-Di-tert-butyl-1-oxaspiro(4,5) deca- 6,9-diene-2,8-dione, phytol, (+)-γ-Tocopherol, O-methyl derivative, Tetratriacontane and γ-Tocopherol with a peak area percentage of 53.25, 2.08, 2.20, 24.64, 4.77, 2.65% respectively. Moreover, in-vitro analysis indicated that the ethyl acetate extract exhibited stronger α-amylase inhibitory activity (IC₅₀ = 91.75 μg/ mL) compared to the n-hexane extract (IC₅₀ = 229.78 μg/mL), with potency approaching that of the standard drug acarbose (IC₅₀ = 78.72 μg/ mL). In the α-glucosidase inhibition assay, the n-hexane and ethyl acetate extracts showed IC₅₀ values of 59.40 μg/mL and 54.40 μg/mL, respectively, which were comparable to that of the standard metformin (IC₅₀ = 55.49 μg/mL). In summary, the ethyl acetate leaf extract of Ravenala madagascariensis Sonn. exhibited potent α-amylase inhibitory activity, indicating its potential to reduce postprandial glucose levels, while both extracts showed significant α-glucosidase inhibition, aiding in delayed carbohydrate digestion and glucose absorption. The presence of diverse volatile phytoconstituents further supports their biological activity, highlighting the plant’s promise for development into an effective antidiabetic formulation.

Molecular Docking of Cyclic Peptides Against the Quorum-Sensing LasR Protein of Pseudomonas aeruginosa

A. Sowmiya — 2026-10-21

The emerging resistance of microorganisms to commonly used antibiotics and the emergence of P. aeruginosa as one of the ESKAPE pathogens necessitate the search for and development of newer drugs. So far, only a limited number of synthetic compounds have been reported to disrupt quorum sensing (QS). Therefore, the identification and development of novel compounds targeting quorum sensing may provide an effective strategy for controlling P. aeruginosa infections. Hence, in this study, peptide-protein docking was used to target the LasR protein with a small peptide library, and the resulting peptides’ pharmacokinetic properties were evaluated. Out of the 101 peptides, Gramicidin C (-101.5 ± 4.4), Epilancin (-99.8 ± 9.1), Cathelicidin-DM (-91.4 ± 6.3), Gassericin A (-86.4 ± 17.6), PO4 (-83.9 ± 5.7), Gramicidin B (-81.1 ± 1.0), and Salivaricin P (-79.7 ± 3.6) exhibited the highest Haddock score by extending the hydrogen bond interaction with the key Tyr 56 and Ser 129 amino acid residues of the Las R protein. These in silico findings suggest that the identified peptides exhibited high binding affinity toward the LasR protein of P. aeruginosa and may interfere with LasR-mediated quorum sensing, warranting further in vitro and in vivo studies to validate their effects on biofilm formation. A few identified peptides exhibited potential pharmacokinetic challenges; therefore, further formulation strategies would be required to overcome these limitations.

Optimization, purification, and characterization of L-asparaginase from Aspergillus quadrilineatus

Rupa Acharya — 2026-10-21

One remedy used to treat lymphoblastic cancer is L-asparaginase. The ability of a new strain to produce extracellular L-asparaginase was investigated in this work. The study examined the production of L-asparaginase utilising MCDB, which exhibited the highest level of L-asparaginase activity. The optimisation, synthesis, purification, and characterisation of the Aspergillus quadrilineatus derived L-Asparaginase enzyme are the main objectives of this investigation. After the crude enzyme was removed, it was precipitated with ammonium sulphate, filtered using a Sephadex column, and then further purified using ion exchange chromatography to create L-asparaginase. The enzyme’s reaction to different temperatures, pH values, substrate concentrations, incubation times, and SDS-PAGE analyses was evaluated in order to characterise it. To improve the synthesis of L-asparaginase, physical parameters like pH and nutritional parameters like carbon, nitrogen, ionic salts, amino acids, phosphate groups, surfactants, plant oil, and vitamins, as well as their corresponding concentrations, were optimised. The results of the study showed that 37°C and a pH of 8.0 were the most conducive to the synthesis of enzymes. The most effective sources of carbon and nitrogen were L-asparagine (0.5%) and maltose (0.5%), respectively. Vitamins (1%), sodium acetate (1%), citric acid (1%), tryptophan (1%), and sodium dihydrogen phosphate (1%), were found abundant in the yield. With the medium composition described in the paper, continuous fermentation can produce L-asparaginase on a large scale. Protein profiling was conducted using SDS-PAGE on the partly purified enzyme, resulting in a predicted molecular weight of the protein as 47KDa.

Evaluation of Bioorganic Compound from Vitex negundo Linn and its Inhibitory Effect on Biofilm Forming Urinary Tract Infectious agent Enterococcus faecium HAUTI19

M. Mohamed Mahroop Raja — 2026-10-21

Enterococci are the main pathogen to cause human urinary tract infection is rapidly enhancing the antimicrobial resistant leads to develop biofilm associated infections throughout the globe. The present work aimed to evaluate the inhibition activity carried out by traditional plant of Vitex negundo Linn. A clinical sign of 25 urine samples was collected and processed to identify the biofilm bacteria and their antibiofilm activity against Vitex negundo. The drug sensitivity pattern was determined among the four selected enterococci strains by disc diffusion method. Among the four enterococci isolates, the biofilm forming strain was identified as Enterococcus faecium HAUTI19 by 16S rRNA gene sequence with the accession number MG002173. The biofilm isolates used for further studies against medicinal plant extract of Vitex negundo Linn by disc diffusion method, well diffusion method and minimal inhibitory concentration for biofilm inhibition. The application of ethyl acetate leaves extract of Vitex negundo showed antibacterial and biofilm inhibition activity compared to amikacin as standard antibiotics. The structural compound was analyzed by FT-IR and NMR detected as 1-( 3-anilino-5-(2H-1,3- benzodioxol-5-yl)-4,5-dihydro-1H-pyrazol-1-yl ) ethan-1-one. This finding concludes that the confirming the critical need to achieve novel antimicrobial metabolite derived from well- known traditional plant in india Vitex negundo Linn is a promising source and its implementation in medical field used to eradicate all common types infection raised from multidrug resistant and biofilm producing bacterial pathogens.

Development and Validation of a Stability-Indicating RP-UPLC Method for the Simultaneous Determination of Glimepiride and Lobeglitazone Sulfate in Pharmaceutical Dosage Forms

Bangaraiah Pagala — 2026-10-21

A simple and rapid RP-UPLC method was developed and validated for the simultaneous analysis of Glimepiride (GLM) and Lobeglitazone sulfate (LBZ) in pharmaceutical formulations. Chromatographic separation was performed on a Phenyl column using a mobile phase of 0.1% formic acid and acetonitrile (70:30, v/v) at 0.5 mL min⁻¹, with detection at 266 nm. Retention times were 1.267 min for GLM and 1.876 min for LBZ. Linearity was achieved over 25–150 μg/mL for GLM and 12.5–75 μg/ mL for LBZ (R² = 0.99956 and 0.99980, respectively). Recoveries ranged from 99.8–100.3% (GLM) and 99.3–100.1% (LBZ), with method precision (%RSD) below 0.64% and LOD/LOQ values of 0.6/2.0 μg/mL (GLM) and 0.3/1.0 μg/ mL (LBZ). Stress degradation studies established its stability-indicating capability, with peroxide treatment producing the highest degradation (15.9% for GLM and 16.5% for LBZ). Peak purity analysis demonstrated that analyte peaks remained free from interference by degradation products, indicating the validated method is reliable for routine quality assessment and stability evaluation of Glimepiride and Lobeglitazone sulfate in formulations.

Petasiphenol and Spathulenol as Promising Natural DPP-4 Inhibitors: An In Silico Multiple Ligand-Based Study Against Type 2 Diabetes Mellitus

Nazmun Nahar — 2026-10-21

Type 2 Diabetes Mellitus (T2DM) is a prevalent metabolic disorder with significant global morbidity and mortality. Dipeptidyl peptidase- 4 (DPP-4) is a key enzyme regulating glucose metabolism, and its inhibition represents a promising therapeutic strategy. This study evaluated the binding affinity and interaction mechanisms of natural compounds from Impatiens balsamina and Acmella oleracea against DPP-4 (PDB ID: 2RGU) using molecular docking, with Linagliptin as a reference inhibitor. Docking results revealed that Linagliptin exhibited the strongest interactions, forming multiple hydrogen bonds, π–π interactions, and hydrophobic contacts with catalytic residues. Among the phytochemicals, Petasiphenol demonstrated the highest affinity, stabilized by hydrogen bonds and aromatic interactions, while Spathulenol showed favorable binding through a combination of polar and hydrophobic contacts. Apigenin exhibited moderate interactions, whereas sesquiterpenoids Cedrenol and Salvia-1(14)-en-1-one showed limited binding due to their predominantly hydrophobic nature. These findings indicate that natural compounds containing hydroxyl groups and aromatic scaffolds are more effective DPP-4 binders. Petasiphenol and Spathulenol emerge as promising lead compounds for further molecular dynamics, pharmacokinetic studies, and experimental validation, supporting their potential development as plant-derived antidiabetic agents.

RP-HPLC Method Development and Validation for Simultaneous Quantitation of Sitagliptin Phosphate and Empagliflozin: QbD Driven

Sapna Rathod — 2026-10-21

The recently approved combination of Sitagliptin Phosphate and Empagliflozin (September 2024) is widely used to improve glycemic control in adults with type 2 diabetes mellitus. Reported HPLC method for the quantification of Sitagliptin Phosphate and Empagliflozin lack the required robustness for regulatory approval and ignore interaction effects between method parameters. Also there is a lack of structured, risk-based methodology in the literature to optimize the separation of both drugs. Till date, no robust Quality by Design (QbD) -based RPHPLC method has been systematically developed for their simultaneous estimation, creating a gap in reliable and optimized analytical procedures for routine quality control. This study aims to develop and validate a simple, robust, and efficient RP-HPLC method using a QbD approach for the simultaneous quantification of these drugs in a laboratory-prepared blend. Critical method parameters like percentage of acetonitrile (ACN), percentage of o-phosphoric acid (OPA), and flow rate were initially screened using a Plackett–Burman design and further optimized using a Box–Behnken design with response surface methodology. Key analytical responses, including retention time, theoretical plates, and tailing factor, were evaluated and optimized. Chromatographic separation was achieved on an XR ODS II C18 column (150 × 3 mm, 5 μm) at 25 °C, using a mobile phase of ACN and 0.1% OPA in water (70:30, v/v), at a flow rate of 1.0 mL/min, with detection at 254 nm. The retention times were 2.626 min for Sitagliptin Phosphate and 4.041 min for Empagliflozin. In AQbD multiple factors can be varied simultaneously to optimise it as well as enables regulatory flexibility in comparison to traditional HPLC methods where one factor is varied at a time. Validation results complied with ICH Q2(R2) guidelines. Its robustness and efficiency make it particularly valuable for simultaneous estimation of this newly approved drug combination in bulk and formulation studies.

Non-Coding RNA Regulators of the Immunosuppressive Tumour Microenvironment in Glioma: a Cross-Cohort TCGA Analysis Identifying Delivery-Aware Therapeutic Targets

Mahmoud Almutadares — 2026-10-21

Gliomas are the most common malignant primary brain tumours, and their dismal prognosis is driven in large part by an immunosuppressive tumour microenvironment (TME) dominated by tumour-associated macrophages and microglia, hypoxia and mesenchymal transition. The non-coding RNA (ncRNA) circuitry that couples these programmes remains incompletely defined, and few candidate regulators have been evaluated for therapeutic tractability given the blood-brain barrier (BBB). Here we integrated transcriptomic and clinical data from TCGA-GBM and TCGA-LGG to map ncRNA regulators of the glioma TME and to prioritise delivery-aware targets. Tumours were scored along four TME axes (hypoxia, myeloid/TAM, mesenchymal and lymphoid), and long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) were tested for differential expression, axis correlation, survival association and competing- endogenous-RNA (ceRNA) connectivity. Across 304 GBM and 533 LGG scored tumours, the myeloid, mesenchymal and hypoxia axes were strongly co-activated, defining a TME-high state. A replicated module of lncRNAs (including LINC02381, PRKAR1B-AS1 and LBX2- AS1) and the miRNAs miR-155 and miR-23a was up-regulated in TME-high tumours, with Spearman correlations reaching rho = 0.70 and concordant effects between cohorts. High expression of these ncRNAs was associated with shorter overall survival (median hazard ratios 1.5-2.2; best P < 1e-20). Expression-supported ceRNA reconstruction placed LINC02381 as a hub linking miR-155 and miR-23a and de-repressing target genes enriched for Notch signalling (DLL1). Integrating replication, effect size, survival and network evidence yielded a 50-target, BBB-aware, delivery-aware shortlist mapped to the TAM/microglia and hypoxic-necrotic compartments. These candidates provide a prioritised, experimentally testable basis for antisense, RNA-interference and antagomir strategies against the glioma TME.

Development and Validation of an Ultra High-Performance Liquid Chromatographic Method with Ultraviolet Detection for Simultaneous Quantification of Filgrastim and Motixafortide in Human Plasma

Lurdhu Mary. K — 2026-10-21

Multiple myeloma is a hematologic malignancy characterized by the uncontrolled proliferation of malignant plasma cells in the bone marrow. Filgrastim and motixafortide are used in combination to mobilize hematopoietic stem cells for collection prior to autologous stem cell transplantation, an important component of therapy for eligible patients with multiple myeloma. Accurate quantification of these agents in plasma is essential for therapeutic drug monitoring and bioequivalence studies. The objective of current work is to develop and validate a simple, accurate, and cost-effective ultra-high-performance liquid chromatographic method for the simultaneous estimation of filgrastim and motixafortide in human plasma. Protein precipitation was used for sample preparation. Chromatographic separation was achieved on a CHS C18 column with a mobile phase of 0.01 M ammonium acetate buffer pH 4.8 and acetonitrile (40:60, v/v) at a flow rate of 0.3 mL/min. Metformin was employed as the internal standard, and UV detection was performed at 220 nm. The retention times of filgrastim, motixafortide were 1.638 and 2.031 min,, respectively. The method was linear in the range of 5–200 ng/mL for filgrastim and 100–4000 ng/mL for motixafortide, with regression coefficients of 0.9993 and 0.9996, respectively. The lower limit of quantification was 5 ng/mL for filgrastim and 100 ng/mL for motixafortide. Accuracy values were within the range of 98.2% to 101.8%, and precision, evaluated as the percentage coefficient of variation, was below 2.0%. Mean recovery exceeded 95% for both analytes and the internal standard. The developed method is suitable for the simultaneous quantification of filgrastim and motixafortide in human plasm.

Phytofabrication of Selenium Nanoparticles Using Hibiscus rosa-sinensis and Evaluation of Their Antioxidant and Antidiabetic Activities

Sudhakar Goda — 2026-10-21

The present study aimed to synthesize selenium nanoparticles (SeNPs) using Hibiscus rosa-sinensis leaf extract through a green and eco-friendly approach and to evaluate their antioxidant and antidiabetic potential. The biosynthesis of SeNPs was confirmed by the appearance of characteristic brick red coloration and UV–Visible spectroscopy showing an absorption peak at 363 nm. Dynamic light scattering (DLS) analysis revealed an average hydrodynamic particle size of approximately 118 d. nm, while zeta potential analysis demonstrated a surface charge of −21 mV, indicating good colloidal stability. Fourier Transform Infrared (FTIR) analysis confirmed the involvement of phytochemical functional groups in the reduction and stabilization of SeNPs. Scanning electron microscopy (SEM) analysis revealed predominantly spherical to quasi-spherical aggregated nanoparticles. The antioxidant activity of the synthesized SeNPs was evaluated using DPPH and ABTS free radical scavenging assays. The SeNPs exhibited strong concentration- dependent antioxidant activity with IC₅₀ values of 34 μg/mL and 37 μg/mL for DPPH and ABTS assays, respectively. In addition, the antidiabetic activity of SeNPs was assessed using α-amylase and α-glucosidase inhibitory assays. The synthesized SeNPs demonstrated significant enzyme inhibitory activity with IC_₅₀ values of 480 μg/mL for α-amylase and 390 μg/mL for α-glucosidase inhibition. The enhanced biological activities may be attributed to the synergistic interaction between selenium and phytochemicals present in the plant extract. Overall, the present findings suggest that green synthesized selenium nanoparticles using Hibiscus rosa-sinensis leaf extract possess promising antioxidant and antidiabetic properties and may serve as potential nanotherapeutic agents for biomedical and pharmaceutical applications.

A Hybrid Graph Attention Network Integrating Coagulation Cascade Biology Developed for Transductive Prediction of Bleeding Disorders

Lakshmi J V N — 2026-10-21

Disorders of blood coagulation arise due to the complex, nonlinear interactions among multiple clotting factors and regulatory proteins. These disorders can be caused within the intrinsic, extrinsic, and common pathways. Traditional mathematical and machine learning approaches study these disorder pathways independently though models can analyze the coagulation cascade due to the existing system level architecture. In this study, a biologically constrained, graph-based learning framework is proposed for predicting coagulation disorders. The coagulation cascade is modeled as a directed network integrating patient’s individual factor activities with established biochemical interactions. A Graph Attention Network (GAT) is applied to understand the significant relation of coagulation factors and their interactions. Thereby GAT network enables interpretable disorder classification. The proposed model supports transudative interpretation of unseen patient data into the trained graph without retraining. The framework is evaluated using synthesized clinical datasets representing 6 types of blood disorders. Coagulation disorder is caused due to the deficiency of Factor VIII causing Hemophilia A, Factor IX causing hemophilia B, Factor XI causing hemophilia C, Factors IX, II, X, and VII causes vitamin K deficiency, Factor VIII causing von Willebrand disease, and normal coagulation profiles are the types of blood disorders considered for the study. Results demonstrate that the proposed approach effectively captures pathway level dependencies and accurately distinguishes the coagulation disorder. The proposed approach predicts the type of disorder with Macro F1 – Score of 0.013 and accuracy of 0.2915. The future scope is to implement the model on real world patient records and further improve the model.

Multi-Omic Integration Reveals a Lung Adenocarcinoma-Specific Tumour-Suppressor Survival Axis Where High-Dimensional Prediction Fails

Thoraia Shinawi — 2026-10-21

Multi-omic profiling is widely expected to improve cancer survival prediction, yet rigorous, transparent comparisons against simple clinical baselines remain scarce. We assembled a seven-modality matrix (gene expression, DNA methylation, somatic mutation, copy-number variation, reverse-phase protein array, clinical variables and protein-interaction context) for 628 patients with lung adenocarcinoma (LUAD) and 497 patients with lung squamous cell carcinoma (LUSC) from The Cancer Genome Atlas. A multimodal variational-autoencoder survival network and a panel of classical machine-learning models were trained and compared for overall- survival discrimination. Deep multimodal survival learning achieved a mean cross-validated concordance index (C-index) of 0.555, whereas a clinical-only random forest attained 0.633; adding high-dimensional omics consistently reduced performance, with the all-feature configuration falling to 0.593. Modality-ablation and nested cross-validation confirmed that this gap reflects the sample-to-feature regime (628 samples versus 1,902 features) rather than model choice. We therefore repurposed the omic data for biological discovery. A six-gene tumour-suppressor panel (KEAP1, STK11, TP53, SMARCA4, NF1 and CDKN2A) added independent prognostic information in LUAD (panel-plus-clinical C-index 0.602; panel hazard ratio 1.16, p = 0.025) but did not validate in LUSC (hazard ratio 0.94, p = 0.48), indicating histology-specific biology. STK11 mutation was the strongest single-gene signal (log-rank p = 0.044). Highrisk LUAD tumours showed coordinated up-regulation of cancer-testis antigens (MAGEA family, PRAME; p < 10^-14), enrichment of lipid and steroid metabolism (p = 0.011) and extracellular- matrix degradation (p = 0.032), together with reduced KEAP1 protein (p = 0.001). Panel-gene recurrence was confirmed across seven independent cBioPortal lung cohorts. These results demonstrate that multi-omic data can yield coherent, mechanistically interpretable biology even when they fail to improve prediction, and define a LUAD-specific metabolic-aggressive survival axis with therapeutic implications.