Cathepsin L (CTSL) expression is dysregulated in a variety of cancers. Extensive empirical evidence indicates their direct participation in cancer growth, angiogenic processes, metastatic dissemination, and the development of treatment resistance. Currently, no natural CTSL inhibitors are approved for clinical use. Consequently, the development of novel CTSL inhibition strategies is an urgent necessity. In this study, a combined machine learning (ML) and structure-based virtual screening strategy was employed to identify potential natural CTSL inhibitors. The random forest ML model was trained on IC₅₀ values. The accuracy of the trained model was over 90%. Furthermore, we used this ML model to screen the Biopurify and Targetmol natural compound libraries, yielding 149 hits with prediction scores >0.6. These hits were subsequently selected for virtual screening using a structure-based approach, yielding 13 hits with higher binding affinity compared to the positive control (AZ12878478). Two of these hits, ZINC4097985 and ZINC4098355, have been shown to strongly bind CTSL proteins. In addition to drug-like properties, both compounds demonstrated high affinity, ligand efficiency, and specificity for the CTSL binding pocket. Furthermore, in molecular dynamics simulations spanning 200 ns, these compounds formed stable protein-ligand complexes. ZINC4097985 and ZINC4098355 can be considered promising candidates for CTSL inhibition after experimental validation, with the potential to provide therapeutic benefits in cancer management.

A critical factor in the cause and progression of Alzheimer’s disease (AD) is the growth of β‐amyloid peptide (Aβ) in the brain. The mechanism of this effect is still unknown, although the effect of osthol on Aβ‐induced inflammation is neuroprotective in AD and supplementation with zinc might prevent or delay the onset of dementia. In the current study, by inducing APP vector in human BE (2)‐M17 cells, we established a cellular model of AD and investigated the protective effect of osthol (7‐methoxy‐8‐3‐methyl‐2‐butenyl‐2H‐1‐benzopyran‐2‐one)‐zinc oxide nanoparticles. The osthol‐conjugated zinc oxide nanoparticles could significantly increase cell viability by inhibiting cell apoptosis. Osthol treatment has also prevented synaptic proteins such as postsynaptic density‐95 (PSD‐95), synaptophysin (SYP), and synapsin‐1 from decreasing in APP‐induced BE (2)‐M17 cells. In addition, the expression of miR‐132 was significantly upregulated by osthol by triggering the Wnt/β‐catenin signaling pathway. We conclude from our observations that osthol is a potential drug for the treatment of a neurodegenerative disease, Alzheimer’s. The key reason was that by upregulating miR‐132, osthol could inhibit APP expression to prevent AD from occurring.

Considering that freshwater is a necessity for human life, sewage treatment has been a serious concern for an increasing number of scientists and academics in recent years. To clean industrial effluents, innovative catalysts with good adsorption, chemical stability, and physicochemical properties have been constructed. Here, a prospective microbial consortium was extracted from the wastewater and used as a low-cost catalyst that was functionalized with silver and silver-doped hydroxyapatite (Ag@HAp) nanostructures made using a sonochemical approach. The structural, optical, and crystal phases of Ag and Ag-doped hydroxyapatite (Ag@HAp) nanostructures were studied using ultraviolet-visible (UV-Vis), Fourier transfer infrared spectroscopy (FTIR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and high-resolution transmission electron microscopy (HRTEM) techniques. The degradation action of functionalized microbial consortia was examined against reactive orange 84 (RO84) organic discharge. Excellent efficiency for the removal of industrial effluents was found for the Ag NPs and Ag-doped hydroxyapatite (Ag@HAp) loaded with microbial consortia. A maximum of 95% of the decolorization properties of the RO84 dye were obtained in the case of microbial consortia with Ag and Ag@HAp, which was better than the consortia alone (80.32% for 5 ppm and 69.54% for 20 ppm). The consortia/Ag showed 93.34% for 5 ppm and 85.43% for 20 ppm, while was higher for consortia/Ag@HAp (95.34 and 88.43%). The use of these surface-modified nanocatalysts for wastewater treatment and waste effluents discharged from laboratories, the chemical industry, and other sources could be expanded.