Abstract
SummaryMetformin, the first drug chosen to be tested in a clinical trial aimed to target the biology of aging per se, has been clinically exploited for decades in the absence of a complete understanding of its therapeutic targets or chemical determinants. We here outline a systematic chemoinformatics approach to computationally predict biomolecular targets of metformin. Using several structure‐ and ligand‐based software tools and reference databases containing 1,300,000 chemical compounds and more than 9,000 binding sites protein cavities, we identified 41 putative metformin targets including several epigenetic modifiers such as the member of the H3K27me3‐specific demethylase subfamily, KDM6A/UTX. AlphaScreen and AlphaLISA assays confirmed the ability of metformin to inhibit the demethylation activity of purified KDM6A/UTX enzyme. Structural studies revealed that metformin might occupy the same set of residues involved in H3K27me3 binding and demethylation within the catalytic pocket of KDM6A/UTX. Millimolar metformin augmented global levels of H3K27me3 in cultured cells, including reversion of global loss of H3K27me3 occurring in premature aging syndromes, irrespective of mitochondrial complex I or AMPK. Pharmacological doses of metformin in drinking water or intraperitoneal injection significantly elevated the global levels of H3K27me3 in the hepatic tissue of low‐density lipoprotein receptor‐deficient mice and in the tumor tissues of highly aggressive breast cancer xenograft‐bearing mice. Moreover, nondiabetic breast cancer patients receiving oral metformin in addition to standard therapy presented an elevated level of circulating H3K27me3. Our biocomputational approach coupled to experimental validation reveals that metformin might directly regulate the biological machinery of aging by targeting core chromatin modifiers of the epigenome.
Highlights
The TAME (Targeting Aging with Metformin) clinical trial has been designed to evaluate the capacity of the antidiabetic biguanide metformin to delay the manifestation of age-associated disorders (Barzilai, Crandall, Kritchevsky & Espeland, 2016)
The evaluation of the binding mode of several metformin-related biguanides to the catalytic site of KDM6A/UTX revealed a differential but overlapping utilization of interacting residues shared with the crystallographic ligand NOG (K1137, T1143, S1154, and N1156) and other key interacting residues reported in the literature (H1146, E1148, W1166, and H1226) (Figure 4a). norMitoMet showed the largest number of contact residues and bound to the catalytic site of KDM6A/UTX with the highest energy value among all the biguanides tested (À54.4117 kcal/mol, Figure 4), which was notably higher than those binding energies found when using buformin, phenformin or cycloguanil, all of them lower than those initially observed with metformin (À26.1494 kcal/mol, Table S3)
We provide biocomputational evidence to suggest that the capacity of metformin to operate as a polytherapeutic anti-aging tool likely involves diverse mechanisms of action, such as substrate competition phenomena with metabolites or nutrients, metal-interactive regulation of protein functioning, genome stability, and epigenome marking and functioning (Figure 6d)
Summary
The TAME (Targeting Aging with Metformin) clinical trial has been designed to evaluate the capacity of the antidiabetic biguanide metformin to delay the manifestation of age-associated disorders (Barzilai, Crandall, Kritchevsky & Espeland, 2016). By enrolling patients aged 65–79 years diagnosed with one single age-associated condition and assessing the global impact of metformin on a composite outcome including cardiovascular events, cancer, dementia, mortality, and other functional and geriatric endpoints, this paradigm-shifting study aimed to target the aging process per se (Newman et al, 2016; Figure S1A). If the positive consequences of metformin extend beyond an isolated impact on each separate agerelated disease, the TAME study might pave the way for the development of new healthspan-promoting treatments aimed to promote reduction in age-associated multimorbidity. The ability of metformin to promote such metabolic fitness and operate as an antiaging tool is commonly perceived as the sum of the pleiotropic effects due to its primary action on a single master mechanism. Using a systematic chemoinformatics approach (Figure S1B) coupled to laboratory-based confirmatory testing, we sought to computationally predict and experimentally validate new biomolecular targets through which metformin might operate as a polytherapeutic tool capable of targeting the biological machinery of aging
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