Geroprotectors.org: a new, structured and curated database of current therapeutic interventions in aging and age-related disease

Moskalev, Alexey; Chernyagina, Elizaveta; Magalhães, João Pedro de; Barardo, Diogo; Thoppil, Harikrishnan; Shaposhnikov, Mikhail; Budovsky, Arie; Fraifeld, Vadim E.; Garazha, Andrew; Tsvetkov, Vasily O.; Bronovitsky, E. V.; Bogomolov, В Р; Scerbacov, Alexei; Kuryan, Oleg; Gurinovich, Roman; Jellen, Leslie C.; Kennedy, Brian; Mamoshina, Polina; Dobrovolskaya, Evgeniya; Aliper, Alex; Kaminsky, Dmitry; Zhavoronkov, Alex

doi:10.18632/aging.100799

Cited by 100 publications

(68 citation statements)

References 60 publications

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“…Whereas most studies have focussed on model organisms, one study used the known prolongevity drugs from the Geroprotectors database (Moskalev et al, 2015) and asked whether these could be functional in humans (Aliper et al, 2016). Using young and old human stem cell expression profiles, they calculate a geroprotective score based on the GeroScope algorithm, which scores drugs based on the drug targets and age‐associated expression changes in related pathways (Zhavoronkov, Buzdin, Garazha, Borisov, & Moskalev, 2014).…”

Section: Introductionmentioning

confidence: 99%

Gene expression‐based drug repurposing to target aging

et al. 2018

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Aging is the largest risk factor for a variety of noncommunicable diseases. Model organism studies have shown that genetic and chemical perturbations can extend both lifespan and healthspan. Aging is a complex process, with parallel and interacting mechanisms contributing to its aetiology, posing a challenge for the discovery of new pharmacological candidates to ameliorate its effects. In this study, instead of a target‐centric approach, we adopt a systems level drug repurposing methodology to discover drugs that could combat aging in human brain. Using multiple gene expression data sets from brain tissue, taken from patients of different ages, we first identified the expression changes that characterize aging. Then, we compared these changes in gene expression with drug‐perturbed expression profiles in the Connectivity Map. We thus identified 24 drugs with significantly associated changes. Some of these drugs may function as antiaging drugs by reversing the detrimental changes that occur during aging, others by mimicking the cellular defence mechanisms. The drugs that we identified included significant number of already identified prolongevity drugs, indicating that the method can discover de novo drugs that meliorate aging. The approach has the advantages that using data from human brain aging data, it focuses on processes relevant in human aging and that it is unbiased, making it possible to discover new targets for aging studies.

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Section: Introductionmentioning

confidence: 99%

Gene expression‐based drug repurposing to target aging

et al. 2018

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“…HAGR focuses mostly on genes, and thus there is a need for a curated database of drugs and compounds that can extend lifespan in model organisms. Existing databases with lifespan‐extending drugs include AgeFactDB (http://agefactdb.jenage.de/) (Huhne et al ., 2014), in turn based on data from HAGR and SAGEWEB (http://sageweb.org/), and Geroprotectors.org (http://geroprotectors.org/) (Moskalev et al ., 2015). DrugAge incorporates data from all these resources and improves on them by providing a more extensive and systematic repertoire of lifespan‐extending drugs, compounds and substances.…”

Section: Discussionmentioning

confidence: 99%

The DrugAge database of aging-related drugs

et al. 2017

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SummaryAging is a major worldwide medical challenge. Not surprisingly, identifying drugs and compounds that extend lifespan in model organisms is a growing research area. Here, we present DrugAge (http://genomics.senescence.info/drugs/), a curated database of lifespan‐extending drugs and compounds. At the time of writing, DrugAge contains 1316 entries featuring 418 different compounds from studies across 27 model organisms, including worms, flies, yeast and mice. Data were manually curated from 324 publications. Using drug–gene interaction data, we also performed a functional enrichment analysis of targets of lifespan‐extending drugs. Enriched terms include various functional categories related to glutathione and antioxidant activity, ion transport and metabolic processes. In addition, we found a modest but significant overlap between targets of lifespan‐extending drugs and known aging‐related genes, suggesting that some but not most aging‐related pathways have been targeted pharmacologically in longevity studies. DrugAge is freely available online for the scientific community and will be an important resource for biogerontologists.

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“…Identification of potential geroprotectors will be even more effective with the development of geroprotector criteria, which involves the building of appropriate databases (Moskalev et al ., 2015). A number of additional requirements related to the storage, data format, access control, request processing, etc., in these databases should be met.…”

Section: Identification Of Candidatesmentioning

confidence: 99%

“…(2009) listed 24 geroprotectors known at that time. Today, more than 200 substances belong to this group, each reported to slow aging and/or increase lifespan in a variety of organisms, including yeasts, nematodes, fruit flies, and rodents, according to the Geroprotectors.org database (http://geroprotectors.org/) (Moskalev et al ., 2015). …”

Section: Introductionmentioning

confidence: 99%

Developing criteria for evaluation of geroprotectors as a key stage toward translation to the clinic

et al. 2016

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SummaryIn the coming decades, a massive shift in the aging segment of the population will have major social and economic consequences around the world. One way to offset this increase is to expedite the development of geroprotectors, substances that slow aging, repair age‐associated damage and extend healthy lifespan, or healthspan. While over 200 geroprotectors are now reported in model organisms and some are in human use for specific disease indications, the path toward determining whether they affect aging in humans remains obscure. Translation to the clinic is hampered by multiple issues including absence of a common set of criteria to define, select, and classify these substances, given the complexity of the aging process and their enormous diversity in mechanism of action. Translational research efforts would benefit from the formation of a scientific consensus on the following: the definition of ‘geroprotector’, the selection criteria for geroprotectors, a comprehensive classification system, and an analytical model. Here, we review current approaches to selection and put forth our own suggested selection criteria. Standardizing selection of geroprotectors will streamline discovery and analysis of new candidates, saving time and cost involved in translation to clinic.

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Geroprotectors.org: a new, structured and curated database of current therapeutic interventions in aging and age-related disease

Cited by 100 publications

References 60 publications

Gene expression‐based drug repurposing to target aging

Gene expression‐based drug repurposing to target aging

The DrugAge database of aging-related drugs

Developing criteria for evaluation of geroprotectors as a key stage toward translation to the clinic

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