Tabrez Faruqui

Plant-derived phytochemicals are increasingly investigated for their antioxidant and enzyme-inhibitory activities as potential sources of bioactive compounds. The present study evaluated the phytochemical composition, antioxidant activity, and in vitro α-amylase inhibitory activity of Madhuca longifolia leaf and bark extracts, followed by GC-MS profiling and exploratory computational analyses of the methanolic leaf fraction. Moreover, we elucidated the ADME properties of GC-MS-putatively identified compounds and their computational molecular interactions with α-amylase. The leaves and barks were sequentially extracted using n-hexane, DCM, EtOAc, MeOH, and water. The qualitative phytochemical analysis and antioxidant activity were determined via DPPH, ABTS, and FRAP assays. Furthermore, the MeOH fraction of M. longifolia leaves was subjected to GC-MS analysis to identify the secondary metabolites. The putatively identified compounds were further subjected to ADME analysis and computational molecular interaction studies with α-amylase. Phytochemical screening indicated the presence of several tested phytochemical classes in the MeOH and aqueous fractions of the leaf and bark extracts. The MeOH and aqueous fractions of the leaf extract showed IC₅₀ values of 8.67 and 10.51 µg/mL, respectively, against DPPH, whereas the corresponding bark fractions showed IC₅₀ values of 8.21 and 8.15 µg/mL, respectively. A similar trend was observed in the ABTS assay, where the MeOH and aqueous fractions of the leaf extract exhibited IC₅₀ values of 4.32 and 4.68 µg/mL, respectively, while the corresponding bark fractions showed IC₅₀ values of 4.44 and 5.40 µg/mL, respectively. The maximum α-amylase inhibitory potential was observed in the MeOH fraction of the leaf extract, and global nonlinear enzyme kinetic analysis showed a pattern consistent with competitive inhibition. The in silico molecular docking analysis predicted that 6-methylheptanoic acid from the MeOH fraction of the leaf extract may interact with the catalytic site of human α-amylase, with a Glide score of −6.132. In conclusion, the findings provide preliminary evidence of antioxidant and in vitro α-amylase inhibitory activities of the MeOH fraction of M. longifolia leaf extract and support its consideration as a preliminary lead for further investigation. Further studies involving quantitative chemical characterization, isolation and validation of individual constituents, cellular and pharmacodynamic evaluation, experimental toxicity assessment, and in vivo efficacy studies are required to establish their relevance to glucose metabolism and diabetes-related outcomes.

Advanced glycation end‐products (AGEs) arise from non‐enzymatic reactions between reducing sugars and proteins, contributing to oxidative stress and metabolic dysfunction. Excessive AGE accumulation is implicated in chronic diabetic complications and may also be relevant to acute metabolic disturbances encountered in emergency medicine. N ‐acetylcysteine (NAC), a naturally occurring antioxidant found in Allium species, has demonstrated potential to attenuate oxidative and glycation‐mediated damage. The effect of NAC on d ‐ribose‐induced glycation of bovine serum albumin (BSA) was investigated using multiple physicochemical and spectroscopic techniques. AGE formation was assessed by measuring hyperchromicity, early glycation products (ketoamines), carbonyl content, hydroxymethylfurfural (HMF) levels, and fluorescent AGEs. The protective effect of NAC was further evaluated by determining free lysine and arginine contents. Protein aggregation and conformational changes were analyzed using Congo Red binding and fluorescence assays including thioflavin‐T and 1‐anilinonaphthalene‐8‐sulfonic acid. NAC significantly inhibited d ‐ribose‐mediated glycation of BSA in a concentration‐dependent manner. Treatment with NAC resulted in reduced hyperchromicity, decreased ketoamine formation, and lower carbonyl, HMF, and fluorescent AGE levels. NAC preserved protein integrity by maintaining higher free lysine and arginine contents. In addition, NAC markedly attenuated glycation‐induced protein aggregation, as evidenced by reduced Congo Red binding and diminished thioflavin‐T and ANS fluorescence, with maximal protection observed at 300 μM. NAC exhibits pronounced anti‐glycation and anti‐aggregation effects by limiting oxidative stress and glycation‐mediated protein modification. These findings demonstrate that NAC effectively attenuates d ‐ribose‐induced glycation and protein aggregation in vitro and provide mechanistic insights into its anti‐glycation properties through multiple complementary biochemical mechanisms. Further studies are warranted to evaluate its biological relevance in more complex experimental models.

Sudden cardiac events are the leading cause of death worldwide. Conventional risk stratification methods, which largely depend on clinical history, imaging, and electrocardiography, are usually inadequate for identifying high‐risk individuals, especially those without visible structural heart disease. Through genetic testing, personalized medicine has been revolutionized by enabling the identification of single‐gene variants, population‐specific polymorphisms, and polygenic risk factors that promote susceptibility to arrhythmia. Inherited channelopathies, such as long QT syndrome, Brugada syndrome, and catecholaminergic polymorphic ventricular tachycardia, as well as cardiomyopathies, are characterized by strong genotype–phenotype correlations, allowing more accurate prediction of arrhythmia risk. Single‐gene panels, whole‐exome sequencing (WES), whole‐genome sequencing (WGS), and polygenic risk scores (PRS) are not mutually exclusive; rather, they can be used together to enhance diagnostic yield and risk stratification. Screening of relatives of affected individuals enables the early identification of asymptomatic carriers. Moreover, the combination of clinical, imaging, and molecular data supports individualized risk assessment. The next steps emphasize the integration of multiomics, variant interpretation using artificial intelligence, and the creation of ancestry‐specific genetic repositories, which will facilitate predictive and preventive approaches to cardiology. This review describes current genetic testing approaches for sudden cardiac events, their use in personalized risk assessment, and the potential of personalized medicine to lower the risk of sudden cardiac death.

Terpenes are among the most diverse kinds of natural products because of their remarkable chemical variety. Numerous biological characteristics of terpenoids have been documented, including their antibacterial, antifungal, antiviral, antihyperglycemic, anti-inflammatory, and antiparasitic effects, as well as their cancer chemopreventive benefits. Additionally, terpenes are utilized in the manufacturing of organic solvents, varnishes, inks, adhesives, synthetic polymers, natural rubbers, cleaning supplies, biofuels, insecticides, and food and beverage items. Terpenes are therefore highly valued in modern medicine, pharmacy, nutraceuticals, cosmetics, and other fields. Plant oils, including terpenes, have been used to treat a variety of diseases without a full understanding of the roles or modes of action of particular bioactive substances. Many of these compounds are only present in nature in extremely small amounts; thus, methods such as metabolic engineering and synthetic biology are used to harvest them in large quantities in order to produce enough medicine. This comprehensive review aims to elucidate the biochemistry, phytochemical properties, and pharmacological activities of terpenes in metabolic disorders.

Background COVID-19 manifestations range from asymptomatic to severe, and are influenced by host genetic factors. This study examined the association between vitamin D receptor (VDR) polymorphisms (TaqI and FokI) and transmembrane serine protease 2 (TMPRSS2) gene polymorphisms (rs12329760) and COVID-19 severity. Methods and results 242 COVID-19 patients underwent genotyping using PCR-RFLP. Statistical analysis were conducted using SPSS v.21 and SHesis software, and validated by Sanger sequencing. The association of the VDR TaqI, FokI, and TMPRSS2 rs12329760 polymorphisms with COVID-19 severity was investigated. Computational analysis of TMPRSS2 was used to determine the pathogenicity and structural effects of these SNPs. For VDR TaqI, the ‘TC’ genotype showed higher prevalence in severe cases (50.5%) compared to mild cases (41.4%); however, no statistically significant association was observed [OR: 1.545 (0.893–2.675), p > 0.05]. Similar patterns were noted for the ‘CC’ genotype and ‘C’ allele, without statistical significance. For VDR FokI, the ‘Ff’ genotype showed higher prevalence in severe cases (25.8%) compared to mild cases (20.0%) [OR: 0.766 (0.199–2.951), p = 0.69], with no significant association. In haplotype analysis, elevated frequencies of ‘Tf’ and ‘ft’ haplotypes were observed in severe cases, but without statistical significance. For TMPRSS2 rs12329760, the ‘CT’ genotype showed a marginally higher prevalence in severe cases (50.5%) than in mild cases (49.7%) [OR: 0.805 (0.276–2.345), p > 0.05], without significant association. Computational analysis indicated that the variant does not demonstrate pathogenic effects but may influence protein stability. Conclusion This study revealed no statistically significant association between VDR (TaqI and FokI) and TMPRSS2 (rs12329760) polymorphisms and COVID-19 severity. Large-scale investigations and functional analysis are required to delineate the impact of these genetic variations on COVID-19 susceptibility and severity.

The insulin‐like growth factor 1 receptor (IGF1R) is a crucial receptor tyrosine kinase involved in cellular growth, survival, and metabolism. Abnormal overexpression and activation are common in various cancers and contribute to tumor development and resistance to treatment. The STRING database was used to analyze the protein–protein interaction network of IGF1R and was visualized using Cytoscape to identify the key associated proteins. We assessed IGF1R and its associated protein expression levels across pan‐cancer types and compared them to healthy controls using a TNMplot and cBioPortal. The objective of this study was to identify novel, low‐toxicity inhibitors targeting the IGF1R and its associated proteins (e.g., AKT1 and EGFR) with better pharmacokinetic profiles for effective cancer treatment, including brain cancer. We screened 693 million drug‐like compounds and selected the top 400 for toxicity analysis using ProTox‐II, which identified 83 nontoxic candidates. These were categorized as either blood–brain barrier (BBB) permeant or impermeant. Molecular docking studies with AutoDock Vina 4.1 were performed on 17 target proteins, including IGF1R, with the top three compounds. Subsequently, molecular dynamics simulations using Desmond were conducted on the two most promising candidates: two BBB permeants and two impermeants. Our study identified six nontoxic IGF1R inhibitors and 16 other target protein inhibitors. Docking and MD simulations confirmed the potential of these compounds in targeted therapies. Notably, both BBB‐permeant and ‐impermeant compounds in complex with the target proteins showed stability over 50 and 400 ns molecular simulation experiments, highlighting their potential in cancer therapy and suggesting the need for further in vitro and in vivo validation.

Despite recent breakthroughs in diagnosis and treatment, cancer remains a worldwide health challenge with high mortality. Autophagy plays a major role in the progression and development. Starving cancer cells obtain nutrients through the upregulation of autophagy. Several compounds derived from natural sources, including animals, plants, and microorganisms, have been identified as potential novel anticancer drugs. Spices play an important role in human health and possess many medicinal properties. Our study aimed to identify potential autophagy modulators from panch phoron spices (P5S) through in silico approaches. Herein, we report a structure-based virtual screening of compounds isolated from P5S (i.e., cumin, fenugreek, fennel, black mustard, and black cumin) against the molecular targets of autophagy. Using various computational tools, we attempted to identify potential modulators of autophagy. Among all the screening results (such as binding energy, hydrogen bonding, drug-likeness, bioactivity, ADME properties, and toxicity), P5S, stigmasterol, and tigogenin showed the best drug-like properties and binding affinity toward the selected targets of autophagy. Furthermore, the stability of both complexes was evaluated by performing a 100 ns molecular dynamics simulation (MDS) using Schrodinger's Desmond Module. Our results provide insight into the efficacy of P5S components against cancer. Therefore, targeting autophagy using these molecules may be an effective and potential drug candidate for cancer treatment. In conclusion, stigmasterol and tigogenin may act as potential candidates for anticancer drugs by targeting autophagy.