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Colorectal cancer is the second leading cause of cancer-related deaths. In 2018, there were an estimated 1.8 million cases, and this number is expected to increase to 2.2 million by 2030. Despite its prevalence, the current therapeutic option has a lot of side effects and limitations. Therefore, this study was designed to employ a computational approach for the identification of anticancer inhibitors against colorectal cancer using Resveratrol derivatives. Initially, the pass prediction spectrum of 50 derivatives was conducted and selected top seven compounds based on the maximum pass prediction score. After that, a comprehensive analysis, including Lipinski Rule, pharmacokinetics, ADMET profile study, molecular orbitals analysis, molecular docking, molecular dynamic simulations, and MM-PBSA binding free energy calculations. The reported binding affinity ranges of Resveratrol derivatives from molecular docking were -6.1 kcal/mol to -7.9 kcal/mol against the targeted receptor of human armadillo repeats domain of adenomatous polyposis coli (APC) (PDB ID: 3NMW). Specifically, our findings reported that two compounds [(03) Resveratrol 3-beta-mono-D-glucoside, and (29) Resveratrol 3-Glucoside] displayed the highest level of effectiveness compared to all other derivatives (-7.7 kcal/mol and -7.9 kcal/mol), and favorable drug-likeness, and exceptional safety profiles. Importantly, almost all the molecules were reported as free from toxic effects. Subsequently, molecular dynamic simulations conducted over 100ns confirmed the stability of the top two ligand-protein complexes. These findings suggest that Resveratrol derivatives may be effective drug candidate to manage the colorectal cancer. However, further experimental research, such as in vitro/in vivo studies, is essential to validate these computational findings and confirm their practical value. [ABSTRACT FROM AUTHOR]

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori‐carcinogenic TNF‐alpha‐inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand–protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root‐mean‐square deviation (RMSD), root‐mean‐square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross‐correlation matrix (DCCM). The results has confirmed that the ligand–protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand–protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand–protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori. [ABSTRACT FROM AUTHOR]

The rise of pyrazinamide (PZA)‐resistant strains of Mycobacterium tuberculosis (MTB) poses a major challenge to conventional tuberculosis (TB) treatments. PZA, a cornerstone of TB therapy, must be activated by the mycobacterial enzyme pyrazinamidase (PZase) to convert its active form, pyrazinoic acid, which targets the ribosomal protein S1. Resistance, often associated with mutations in the RpsA protein, complicates treatment and highlights a critical gap in the understanding of structural dynamics and mechanisms of resistance, particularly in the context of the G97D mutation. This study utilizes a novel integration of computational techniques, including multiscale biomolecular and molecular dynamics simulations, physicochemical and medicinal chemistry predictions, quantum computations and virtual screening from the ZINC and Chembridge databases, to elucidate the resistance mechanism and identify lead compounds that have the potential to improve treatment outcomes for PZA‐resistant MTB, namely ZINC15913786, ZINC20735155, Chem10269711, Chem10279789 and Chem10295790. These computational methods offer a cost‐effective, rapid alternative to traditional drug trials by bypassing the need for organic subjects while providing highly accurate insight into the binding sites and efficacy of new drug candidates. The need for rapid and appropriate drug development emphasizes the need for robust computational analysis to justify further validation through in vitro and in vivo experiments. [ABSTRACT FROM AUTHOR]

Introduction: The research focuses on Rhododendron ferrugineum L., Nepal's national flower and Uttarakhand's state tree, thriving in high-altitude mountain ecosystems. Methodology and Result: A study conducted in Himachal Pradesh (Latitude: N 31° 6' 2.0088", Longitude: E 77° 10' 29.9136") identified leaf anomalies resembling rust-like manifestations in R. ferrugineum. These anomalies were traced back to the pathogenic fungus Curvularia tuberculata, marking the first documented case of its impact on R. ferrugineum in India. Discussion: This discovery emphasizes the need for vigilant monitoring, disease management research, and conservation efforts to protect the cultural and ecological significance of this iconic shrub. Beyond its immediate findings, the study introduces a novel dimension to Indian flora by associating C. tuberculata with R. ferrugineum, historically linked to monocotyledonous crops. The research methodology combines traditional microscopic examination with advanced genomic sequencing and phylogenetic analysis, enhancing pathogen identification accuracy. Future prospect: In a broader context, this research aligns with the United Nations Sustainable Development Goals (SDGs) by highlighting the importance of environmental preservation, conservation, and sustainable management. It underscores the intricate interplay between biodiversity, cultural heritage, and the need for holistic solutions. Overall, this study calls for proactive measures to protect R. ferrugineum's cultural and ecological heritage and emphasizes the significance of interdisciplinary approaches in addressing emerging ecological threats. [ABSTRACT FROM AUTHOR]