PI: Thomas Girke

The Chemoinformatics core will identify longevity-associated drugs and target proteins for the genetic and molecular findings (here multi-omics hits, MOH) discovered by the other projects and cores of the Longevity Consortium (LC). These associations will make efficient use of the large body of drug-target interaction data available in the public domain including high-quality annotations of existing drugs, high-throughput bioassays and gene expression data involving drug treatments.

Aim 1 will systematically assess which proteins associated with longevity MOH sets are perturbable by drugs given the data currently available in public reference databases. Aim 2 will identify drugs inducing gene expression changes similar to those associated with healthy aging and longevity. Aim 3 will incorporate protein family information to compensate for the lack of bioassay information for certain proteins of interest using bioactivity information available for closely related proteins within and across organisms. Aim 4 will prioritize drug candidates by their level of experimental evidence, annotation and selectivity levels, as well as their potential to be useful for drug repurposing approaches or combinatorial strategies by modulating the activity of proteins in pathways of interest with several selective drugs or single drugs targeting multiple proteins. Aim 5 will validate the effects of the identified drug candidates on longevity and healthy aging using the experimental screening program of the Mice/Cells project. Candidate drugs passing these validation tests will be further evaluated for downstream translational studies with LC and external advisory committee members. Moreover, longevity drug-target networks will be computed and interrogated in close collaboration with the Disease Context, Proteomics, Metabolomics and Centenarian projects, and the Systems Biology core. Aim 6 will organize, integrate and share all analysis results and software developed by the LC with the public by developing the LC database (LCDB) portal.

Figure 1: Drug-target data mining strategy.

Figure 2: Drug-target network of the small-molecule assayed proteome (Backman et al, 2017).