Abstract
The growing availability of 'omics' data and high-quality in silico genome-scale metabolic models (GSMMs) provide a golden opportunity for the systematic identification of new metabolic drug targets. Extant GSMM-based methods aim at identifying drug targets that would kill the target cell, focusing on antibiotics or cancer treatments. However, normal human metabolism is altered in many diseases and the therapeutic goal is fundamentally different - to retrieve the healthy state. Here we present a generic metabolic transformation algorithm (MTA) addressing this issue. First, the prediction accuracy of MTA is comprehensively validated using data sets of known perturbations. Second, two predicted yeast lifespan-extending genes, GRE3 and ADH2, are experimentally validated, together with their associated hormetic effect. Third, we show that MTA predicts new drug targets for human ageing that are enriched with orthologs of known lifespan-extending genes and with genes downregulated following caloric restriction mimetic treatments. MTA offers a promising new approach for the identification of drug targets in metabolically related disorders.
| Original language | English |
|---|---|
| Article number | 2632 |
| Journal | Nature Communications |
| Volume | 4 |
| DOIs | |
| State | Published - 2013 |
Bibliographical note
Funding Information:We thank Matthew Oberhardt, Tuvik Beker, Gideon Y. Stein, Shiri Stempler, Allon Wagner and Yoav Teboulle for their helpful comments on the manuscript. K.Y. is partially supported by a fellowship from the Edmond J. Safra Bioinformatics center at Tel-Aviv University and is grateful to the Azrieli Foundation for the award of an Azrieli Fellowship; E.R. acknowledges the generous support of grants from the Israeli Science Foundation (ISF) and the Israeli Cancer Research Fund (ICRF) for this research; H.C. acknowledges the generous support of grants from the Israeli Ministry of Health and the ERC; E.R. and H.C. acknowledge the I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation (Grant number 41/11).
