Aging is associated with large-scale proteome remodelling and progressive accumulation of insoluble, aggregation-prone proteins. Identifying proteins that become enriched and insoluble with age can help prioritize molecular targets for interventions aimed at preserving proteostasis. The work summarized here applied a proteome-guided strategy in Caenorhabditis elegans to find proteins whose abundance increases substantially with age and to evaluate natural small molecules predicted to bind conserved aggregation-prone proteins.
The investigators identified proteins whose abundance rose more than four-fold in aged worms compared with young worms. Many of these age-enriched proteins also accumulated in the age-associated insoluble proteome, indicating they are prone to aggregation during aging. The study used these observations as a prioritization filter to focus on proteins with both increased abundance and biochemical behavior consistent with aggregation. Specific lists of proteins, quantitative measures, experimental protocols, and raw data are not reported in the source abstract and would be found in the full preprint.
To assess translational relevance, the team identified human orthologs for the set of age-enriched, aggregation-prone C. elegans proteins. Comparative analysis across species was used to prioritize proteins that are conserved structurally and biologically, reasoning that conserved aggregation-prone proteins may represent more broadly relevant targets for interventions that aim to preserve proteostasis in aging.
From the prioritized set, the enzyme glutamine-fructose-6-phosphate aminotransferase-2 (GFAT-2) in C. elegans was selected for molecular docking studies. Selection criteria cited in the abstract included biological relevance, structural conservation, and availability of high-confidence structural models. The corresponding human ortholog GFPT1 was included in comparative docking to identify molecules showing conserved interactions across species.
The authors screened a panel of fifteen phytochemicals by molecular docking against C. elegans GFAT-2 and human GFPT1. Among the compounds tested, quercetin was the strongest predicted binder and was reported to exhibit conserved interactions with both GFAT-2 and GFPT1 in the docking models. The abstract does not provide docking scores, binding poses, or specific interaction residues; these details would be available in the main manuscript or supplementary materials.
Following the in silico prioritization, the study tested quercetin in C. elegans to evaluate effects on protein insolubility during aging. According to the abstract, treatment with quercetin did not significantly alter global protein insolubility in aged worms. The authors suggest this observation may reflect a mechanism in which quercetin modulates inappropriate protein–protein interactions without substantially reducing the overall aggregation burden. The abstract does not report experimental protocols, concentrations, time courses, or statistical measures; those experimental details are not included in the source abstract.
The study highlights two principal messages. First, a proteome-guided approach can identify evolutionarily conserved, age-associated, aggregation-prone proteins suitable for target prioritization. Second, in silico docking predictions—even when showing conserved interactions across species—require experimental validation because a predicted binder (quercetin) did not produce a measurable decrease in global protein insolubility in aged worms.
The authors underscore the need for downstream experimental work to confirm whether predicted binding yields functional modulation of aggregation, proteostasis networks, or organismal phenotypes. They also note the possibility that some modulators might alter specific protein–protein interactions or functional activities without changing bulk measures of insolubility. The study, presented as a preprint, provides a framework for prioritizing aggregation-prone proteins as candidate therapeutic targets during aging and illustrates the gap that can exist between computational predictions and organismal-level outcomes.
Notes on reporting and source limitations
This summary is derived from the article abstract and metadata provided in the source. Specific experimental methods, quantitative results, lists of identified proteins, docking parameters, and statistical analyses were not reported in the abstract. The article is a preprint that has not been peer reviewed; readers should consult the full manuscript for complete data and methods.