Netaji Mahavidyalaya

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) is indispensable for viral replication and remains a validated antiviral drug target. Naturally occurring biflavonoids, particularly those with C-C and C-O-C interflavonoid linkages, have gained attention due to their structural diversity and reported antiviral potential. In this study, an integrated in silico approach was employed to investigate the inhibitory potential of representative biflavonoids against SARS-CoV-2 Mpro. A curated library of C-C- and C-O-C-linked biflavonoids was initially screened using molecular docking within the catalytic pocket of Mpro (PDB ID: 6LU7), followed by density functional theory (DFT) calculations to evaluate electronic properties and chemical reactivity. Molecular dynamics simulations (MDS) were performed to assess the structural stability of the ligand-Mpro complexes, while binding free energies were estimated using the MM/PBSA method. Principal component analysis (PCA) and free energy landscape (FEL) analyses were applied to characterize essential motions and conformational stability during the simulations. Key interactions with the catalytic dyad (His41 and Cys145) and surrounding residues, including Glu166, His163, and Gly143, were consistently observed. Comparative analyses revealed that C-C-linked biflavonoids, particularly amentoflavone and robustaflavone, exhibited more favourable binding affinities and dynamic stability than C-O-C-linked counterparts such as hinokiflavone and ochnaflavone, although both classes demonstrated inhibitory potential. Drug-likeness and pharmacokinetic properties were evaluated using ADMET predictions and Molinspiration analysis, while toxicity assessment via ProTox-3 indicated low predicted toxicity for the top-ranked compounds. Overall, these findings suggest that naturally occurring biflavonoids, C-C- and C-O-C-linked scaffolds, represent promising leads for SARS-CoV-2 Mpro inhibition and merit further experimental validation.

Fungal infection is an ongoing public health concern due to its severity and associated complications. Exploring putative targets is needed to overcome this to enhance the therapeutic design. Therefore, a systematic computational-assisted subtractive proteomics approach was implemented to find the putative drug target and its promising inhibitor, examining the 6 Candida species. Considering 6 species, a total of 501,366 sequences were curated from NCBI and UniProt. Furthermore, based on subsequent steps such as non-orthologous, paralogous, and non-homologous, a total of 352 targets were obtained. Of which, 118 were identified as putative based on essential and target screening. Moreover, the target revealed various similar metabolic pathways toward the host organism, of which 5 proteins were found to be unique based on the non-significant similarity. The subcellular localization demonstrated that out of 5 proteins, only histidine kinase was found to be suitable based on its localization in the cytoplasm. Subsequently, the target structures were enhanced and validated, and significant structural proteins were found. The docking analysis following the high-throughput virtual screening was performed which resulted hyaluronic acid (ID: DB08818) and gadopiclenol (ID: DB17084), with docking scores of − 11.975 kcal/mol and − 11.442 kcal/mol as the most promising based on computational hits and high docking score. Moreover, the stability of these complexes was analyzed over 100 ns and found significant stability of the docked complex, based on the analyzed trajectories such as RMSD, RMSF, and PCA, along with the MMPBSA analysis. Based on the implemented strategy, the overall findings suggest that the identified drug target, together with the selected inhibitors, may enable the treatment of candidiasis-causing fungi and their associated infections.

Gestational diabetes mellitus (GDM) is an increasingly prevalent metabolic disorder with profound implications for maternal and offspring health; however, it remains under-recognized compared with other forms of diabetes, particularly in low- and middle-income countries such as India. Once considered a transient pregnancy complication, GDM is now recognized as a manifestation of underlying insulin resistance, β-cell dysfunction, and metabolic vulnerability, conferring a markedly increased risk of future type 2 diabetes mellitus and the intergenerational transmission of metabolic disease. This narrative review critically examines the current understanding of the pathophysiology, diagnosis, and management of GDM, highlighting major gaps across the continuum of care. Persistent heterogeneity in diagnostic criteria, reliance on glucose-centric screening, inadequate community sensitization, and limited postpartum follow-up undermine effective detection and long-term prevention. Emerging insights into inflammatory pathways, adipokine imbalance, placental dysfunction, and epigenetic regulation highlight the importance of developing integrative mechanistic approaches. To address these challenges, a 360° hub-and-spoke translational framework is proposed, linking community engagement, standardized diagnosis, mechanistic research, and sustained postpartum care to reframe GDM as a life-course metabolic disorder.

Blocking the enzyme alpha-amylase is a promising approach for treating Type 2 diabetes. Although they have been employed as blood-sugar reducers, medicinal phytocompounds have limited ability to inhibit α-amylase. The bamboo plant Chamaedorea seifrizii is mostly used for its esthetic qualities and air-purifying capabilities. Further study is necessary because there are not many studies on this plant's phytochemical composition and anti-α-amylase capability. Therefore, this study's goal was chemical profiling, followed by an in vitro experiment to assess the anti-α-amylase capability of C. seifrizii's flowers and fruits, and an in silico docking of important bioactive chemicals against α-amylase. The bioactive ingredients in C. seifrizii auxiliary inflorescence acetone extract (CIAE) and C. seifrizii fruit acetone extract (CFAE) were identified using GC-FID. The web program Cb-dock2 was utilized for docking. Additionally, two-dimensional interactions between ligands and the target enzyme were examined. After molecular docking, molecular dynamics (MD) simulations, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) computations were performed. The PASS prediction of every ligand and the in silico ADMET pharmacoinformatic perspective were evaluated. The α-amylase inhibition assay was used for wet lab validation. A total of 17 (in CIAE) and 21 (in CFAE) phytocomponents were identified by GC-FID. Major phytocompounds were phenethyl cinnamate (45%) in CIAE and nezukol in (10%) CFAE along with other minor components, such as resveratrol, hinokione, butylated hydroxyanisole, sandaracopimarinol (CFAE), larixol, taxodione, methyl pentanoate, and cedrene epoxide (CIAE). Docking analysis showed that every ligand from CIAE and CFAE effectively bound to the enzyme but with varied affinity. Sandaracopimarinol from CIAE and taxodione from CFAE were detected as best docked compounds with vina score ranging from 8.9 to 8.3, respectively. The stability of docked complexes was further confirmed by the post-MD analysis of the best docked structure, as seen by the root mean square deviation (RMSD) and radius of gyration (Rg) values. MM-PBSA analysis revealed best docked structure with binding energy -72.2 kJ mol-1. According to the results of the in silico ADMET analysis, all the ligand molecules showed good absorption and did not cause any harmful effects. In a kinetic study, CIAE and CFAE were found to inhibit α-amylase in a noncompetitive way. To best of our knowledge, this is first time study reporting bioactive chemicals from C. seifrizii extracts exhibiting anti-α-amylase potential. To validate these results, more studies utilizing clinical trials and animal models are required. This study claimed that due to richness of phytocompounds, C. seifrizii extracts may help to block the enzyme α-amylase, which leads to the creation of new drugs for diabetes.

Fusarium species are major phytopathogens responsible for economically significant diseases such as vascular wilt, root rot, and necrosis in diverse crops. The increasing incidence of mancozeb-resistant strains has complicated disease management, underscoring the need for sustainable alternative or complementary strategies. In this study, phytochemicals from Aegle marmelos were evaluated against Fusarium spp. using an integrated computational approach combining molecular docking and molecular dynamics (MD) simulations. The ergosterol biosynthesis ERG4/ERG24 family enzyme (ERG) and serine protease (SEP) were selected for the first time as molecular targets to assess antifungal potential. Lupeol, not previously investigated in this context, was subjected to a 100 ns MD simulation to evaluate the stability and dynamic behaviour of the protein–ligand complexes. The simulation results revealed a good stability in the formation of complexes with lupeol, a finding that was further validated through Principal Component Analysis (PCA) and MMPBSA calculations. The ΔG binding values calculated by MMPBSA for the lupeol-ERG and lupeol-SEP interactions were found to be − 33.06 ± 3.10 and − 19.60 ± 3.43 kcal/mol, respectively. Complementary in vitro assays revealed that the combined application of A. marmelos leaf extract and mancozeb produced the highest inhibition of mycelial growth of Fusarium sp. strain AA1, accompanied by pronounced morphological deformities, including distorted and collapsed conidia. Collectively, this multi-level validation establishes a novel framework for developing plant-based antifungal strategies to combat mancozeb-resistant Fusarium. Moreover, the synergistic use of plant extract with reduced fungicide dosage offers a sustainable approach that may lower chemical inputs while advancing the development of eco-friendly antifungal strategies for agricultural applications.