Fig 1.
Overview of the methods used in this study to prioritise compounds likely to ameliorate ageing in humans.
A) STITCH chemicals were mapped into DrugBank drugs using the UniChem resource programmatically. B) The significance of the drug-ageing inference was calculated using a Fisher’s exact test, which calculates the probability that the overlap between two samples (ageing-related genes and drug targets) drawn from the same universe is due to chance. This comparison was made at different biological levels. C) Diagram of the procedure to expand the “gene” information into multiple biological levels. Ageing-related genes were mapped to other levels using an enrichment analysis, while the drugs’ targets were cross-referenced with the list of genes defining each annotation.
Table 1.
Drugs significantly enriched for ageing-related targets.
The names of the drugs previously shown to extend lifespan in animal models are in bold and genotoxic molecules are in italic. The columns k(l) and m(n) are consistent with the diagram in Fig 1B. OR stands for odd-ratios and adj.p-value is the p-value adjusted for multiple testing.
Fig 2.
Comparison between the results using different data sources.
A) Correlation between the ranked list of compounds. Boxes are coloured by the Kendall’s correlation coefficient. Enrichment curves for B) pro-longevity drugs and C) anti-longevity drugs. The results of each data source are displayed in lines with different colours. The enrichment expected by chance is shown as a diagonal line with AUC = 0.5.
Table 2.
Top-ranked compounds using multiple levels of biological action.
The names of the drugs previously shown to extend lifespan in animal models are in bold. The numeric values represent the ranking of the drugs when different sources of data (columns) are used. The last column is the ranking average (Avg.) for each drug in the 7 ranked lists.
Fig 3.
Pro-longevity effect of tanespimycin in C. elegans.
A) Representative fluorescent images of day 6 adult, hsp-16.2p::mCherry transcriptional reporter worms, grown on plates containing 0.1% DMSO (vehicle) or different concentrations of tanespimycin (17-AAG) continuously from the first larval stage, or exclusively from the first day of adulthood onward. B) The relative fluorescent intensity of hsp-16.2p::mCherry worms grown on plates containing 0, 1, 10, 25, 50, or 100 μM tanespimycin (17-AAG) continuously from the first larval stage or exclusively from the first day of adulthood onward. Values plotted are the mean of at least 5 animals, and error bars represent the standard deviation from the mean. Statistical significance relative to the DMSO control group was calculated by ONE-WAY ANOVA with Tukey post analysis pairwise comparison of groups. * = p < 0.05, ** = p < 0.01, *** = p < 0.001. C) Lifespan at 20°C of N2 worms grown on plates containing 0.1% DMSO or 100 μM Tanespimycin (17-AAG) from the first day of adulthood onward in the presence of empty vector control or hsp-90(RNAi). Statistical significance was calculated by Log-rank (Mantel-Cox) text. *** = p < 0.001. Treatment groups: 0.1% DMSO (n = 102, 14 censored, median lifespan = 17 days), 100 μM tanespimycin (n = 107, 9 censored, median lifespan 21 days), 0.1% DMSO + hsp-90(RNAi) (n = 69, 30 censored, median lifespan = 15 days), 100 μM tanespimycin + hsp-90(RNAi) (n = 92, 22 censored, median lifespan = 15 days). D) Relative hsp-90 mRNA levels 48 hours following exposure to empty vector control or hsp-90(RNAi). Levels of hsp-90 mRNA were normalized to the geometric mean of three house-keeping genes (cdc-42, rpb-2, and pmp-3). Values plotted are the mean of 3 biological replicates and error bars represent standard deviation. Significance levels were calculated as in Fig 3B.