Today, Alzheimer’s disease (AD)—the most common neurodegenerative disorder, which affects 50 million people—remains incurable. Several studies suggest that one of the main pathological hallmarks of AD is the accumulation of abnormal amyloid beta (Aβ) aggregates; therefore, many therapeutic approaches focus on anti-Aβ aggregation inhibitors. Taking into consideration that plant-derived secondary metabolites seem to have neuroprotective effects, we attempted to assess the effects of two flavones—eupatorin and scutellarein—on the amyloidogenesis of Aβ peptides. Biophysical experimental methods were employed to inspect the aggregation process of Aβ after its incubation with each natural product, while we monitored their interactions with the oligomerized Aβ through molecular dynamics simulations. More importantly, we validated our in vitro and in silico results in a multicellular organismal model—namely, Caenorhabditis elegans—and we concluded that eupatorin is indeed able to delay the amyloidogenesis of Aβ peptides in a concentration-dependent manner. Finally, we propose that further investigation could lead to the exploitation of eupatorin or its analogues as potential drug candidates.

Alzheimer’s disease (AD) is the most common form of dementia. Given the link between oxidative stress and AD, many studies focus on the identification of natural antioxidants against AD. Although their antioxidant capacity is important, increasing data suggest that additional activities are related to their beneficial effects, including properties against amyloid beta (Aβ) aggregation. Sideritis spp. (mountain tea) extracts possess not only antioxidant activity but also other bioactivities that confer neuroprotection. Although various Sideritis spp. extracts have been extensively studied, there are scarce data on S. clandestina subsp. peloponnesiaca (SCP) phytochemical composition and neuroprotective potential, while nothing is known of the responsible compounds. Given that SCP is a weaker antioxidant compared to other Sideritis spp., here, we investigated its potential beneficial properties against Aβ aggregation. We characterized different SCP extracts and revealed their anti-aggregation activity by taking advantage of established C. elegans AD models. Importantly, we identified two pure compounds, namely, sideridiol and verbascoside, being responsible for the beneficial effects. Furthermore, we have revealed a potential anti-Aβ aggregation mechanism for sideridiol. Our results support the use of mountain tea in the elderly against dementia and demonstrate the activity of sideridiol against Aβ aggregation that could be exploited for drug development.

The vast majority of microbial diversity remains unculturable, limiting access to novel biotechnological resources. Advances in metagenomics have expanded the understanding of microbial communities, yet targeted protein discovery remains challenging. This study introduces ProteoSeeker, a command‐line tool for streamlined metagenomic protein identification and annotation. ProteoSeeker operates in two primary modes: i) Seek mode, which screens the proteins according to user‐defined protein families, and ii) Taxonomy mode, which uncovers the taxonomy of the host organisms. By automating key steps, ProteoSeeker reduces computational complexity, enabling time‐efficient and comprehensive metagenomic analysis for both specialized and nonspecialized users. The efficiency of ProteoSeeker to achieve targeted enzyme discovery is demonstrated by identifying extremophilic enzymes with desired biochemical features, such as amylases for starch hydrolysis and carbonic anhydrases for CO₂ capture applications. By democratizing functional metagenomics, ProteoSeeker is anticipated to accelerate biotechnology, synthetic biology, and biomedical research and innovation.

Metagenomics have served as a key driver of biotechnology advancements through, among others, the identification of novel proteins. The lack of standardized guidelines and benchmarks in the field, however, complicates the selection of appropriate bioinformatics tool ensembles and hinders faster progress. This study introduces ProteoSeeker , an automated pipeline designed for accessible and comprehensive metagenomic exploration of whole-genome sequencing data. ProteoSeeker identifies proteins within user-defined protein families and uncovers the taxonomy of the host organisms. It is implemented as a command-line tool to facilitate metagenomic dataset analysis for non-expert users, thus enabling facilitated and streamlined protein discovery.

Enzymatic depolymerization of polyethylene terephthalate (PET) has advanced rapidly, alongside a growing volume of publicly available metagenomic data from microbial communities under sustained selective pressure from plastic exposure. Reasoning that such environments may harbor underexplored polyester-active enzymes, we developed a targeted mining workflow that screens exclusively plastic-associated datasets through multi-step bioinformatic filtering—integrating catalytic-motif screening, disulfide-topology validation, structural-similarity scoring, and phylogenetic profiling—to recover high-confidence PETase candidates. Applied to 277 plastic-associated metagenomes, the pipeline yielded 21 non-redundant candidates, several of which combine the Type I catalytic motif (GHSMGGGG) with Type II-like extended loops and secondary disulfide bonds. Two candidates were experimentally confirmed as PET hydrolases; the more active, PET-KR1, is a thermostable enzyme ( Tm = 66.5 °C) that depolymerizes PET across a broad temperature range, with markedly higher productivity on powdered than on film substrate. PET-KR1 achieved optimal depolymerization at 50 °C, yet at 60–65 °C, where total yields declined, the product pool was more strongly enriched in the terminal monomer TPA, suggesting that thermostability and substrate accessibility are the primary targets for further engineering. Molecular dynamics simulations revealed a conserved hydrophobic binding network around the catalytic serine, consistent with established PETase substrate-recognition modes, and rational disulfide engineering raised the melting temperature by 3.5 °C, confirming amenability to further optimization. Overall, PET-KR1 expands the scaffold space available for PETase engineering, while the discovery workflow, built entirely on publicly available tools and open-access data, provides a reproducible strategy for metagenomic mining of novel PET-degrading enzymes toward biocatalytic PET recycling.