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Updated: Aug 5, 2025
A Suppressor Screen for the Characterization of Genetic Links Regulating Chronological Lifespan in Saccharomyces cerevisiae
Published on: September 17, 2020
Model organism life extending therapeutics modulate diverse nodes in the drug-gene-microbe tripartite human longevity
Rahagir Salekeen1, Michael S Lustgarten2, Umama Khan1
1Biotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
Abstract:
Advances in antiaging drug/lead discovery in animal models constitute a large body of literature on novel senotherapeutics and geroprotectives. However, with little direct evidence or mechanism of action in humans-these drugs are utilized as nutraceuticals or repurposed supplements without proper testing directions, appropriate biomarkers, or consistent in-vivo models. In this study, we take previously identified drug candidates that have significant evidence of prolonging lifespan and promoting healthy aging in model organisms, and simulate them in human metabolic interactome networks. Screening for drug-likeness, toxicity, and KEGG network correlation scores, we generated a library of 285 safe and bioavailable compounds. We interrogated this library to present computational modeling-derived estimations of a tripartite interaction map of animal geroprotective compounds in the human molecular interactome extracted from longevity, senescence, and dietary restriction-associated genes. Our findings reflect previous studies in aging-associated metabolic disorders, and predict 25 best-connected drug interactors including Resveratrol, EGCG, Metformin, Trichostatin A, Caffeic Acid and Quercetin as direct modulators of lifespan and healthspan-associated pathways. We further clustered these compounds and the functionally enriched subnetworks therewith to identify longevity-exclusive, senescence-exclusive, pseudo-omniregulators and omniregulators within the set of interactome hub genes. Additionally, serum markers for drug-interactions, and interactions with potentially geroprotective gut microbial species distinguish the current study and present a holistic depiction of optimum gut microbial alteration by candidate drugs. These findings provide a systems level model of animal life-extending therapeutics in human systems, and act as precursors for expediting the ongoing global effort to find effective antiaging pharmacological interventions.Communicated by Ramaswamy H. Sarma.
Insights
This study simulates animal anti-aging drugs in human networks, identifying 25 key compounds like Resveratrol and Metformin that may extend human lifespan and healthspan.
Area of Science:
- Computational biology
- Pharmacology
- Gerontology
Background:
- Numerous anti-aging drugs show promise in animal models but lack human validation.
- Current use as supplements lacks clear directions, biomarkers, and consistent models for human application.
Purpose of the Study:
- To computationally model and predict the efficacy of animal geroprotective compounds in human metabolic networks.
- To identify safe, bioavailable drug candidates with potential to modulate human longevity and healthspan pathways.
Main Methods:
- Simulated 285 pre-identified drug candidates in human metabolic interactome networks.
- Screened compounds for drug-likeness, toxicity, and KEGG network correlation.
- Developed a tripartite interaction map using longevity, senescence, and dietary restriction genes.
Main Results:
- Generated a library of 285 safe and bioavailable compounds.
- Predicted 25 best-connected drug interactors, including Resveratrol, EGCG, Metformin, and Quercetin.
- Identified compound clusters regulating longevity and senescence pathways, and analyzed serum/microbial interactions.
Conclusions:
- Provides a systems-level model for translating animal anti-aging therapeutics to human systems.
- Identifies key compounds and pathways for future pharmacological intervention development.
- Highlights the role of gut microbial interactions in optimizing anti-aging drug effects.
