'Nothing of chemistry disappears in biology': the Top 30 damage-prone endogenous metabolites. (9th June 2016) - Lerma-Ortiz, Claudia; Jeffryes, James G.; Cooper, Arthur J.L.; Niehaus, Thomas D.; Thamm, Antje M.K.; Frelin, Océane; Aunins, Thomas; Fiehn, Oliver; de Crécy-Lagard, Valérie; Henry, Christopher S.; Hanson, Andrew D.
Abstract : Many common metabolites are intrinsically unstable and reactive, and hence prone to chemical (i.e. non-enzymatic) damage in vivo . Although this fact is widely recognized, the purely chemical side-reactions of metabolic intermediates can be surprisingly hard to track down in the literature and are often treated in an unprioritized case-by-case way. Moreover, spontaneous chemical side-reactions tend to be overshadowed today by side-reactions mediated by promiscuous ('sloppy') enzymes even though chemical damage to metabolites may be even more prevalent than damage from enzyme sloppiness, has similar outcomes, and is held in check by similar biochemical repair or pre-emption mechanisms. To address these limitations and imbalances, here we draw together and systematically integrate information from the (bio)chemical literature, from cheminformatics, and from genome-scale metabolic models to objectively define a 'Top 30' list of damage-prone metabolites. A foundational part of this process was to derive general reaction rules for the damage chemistries involved. The criteria for a 'Top 30' metabolite included predicted chemical reactivity, essentiality, and occurrence in diverse organisms. We also explain how the damage chemistry reaction rules ('operators') are implemented in the Chemical-Damage-MINE (CD-MINE) database (minedatabase.mcs.anl.gov/#/top30) to provide a predictive tool for many additional potential metabolite damage products. Lastly, we illustrate how defining a 'Top 30' list can drive genomics-enabled discovery of the enzymes of previously unrecognized damage-control systems, and how applying chemical damage reaction rules can help identify previously unknown peaks in metabolomics profiles.