|SALEKEEN, RAHAGIR - Khulna Agricultural University|
|LUSTGARTEN, MICHAEL - Jean Mayer Human Nutrition Research Center On Aging At Tufts University|
|DIDARUL ISLAM, KAZI MOHAMMED - Khulna Agricultural University|
Submitted to: Journal of Biomolecular Structure and Dynamics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/13/2023
Publication Date: 3/27/2023
Citation: Salekeen, R., Lustgarten, M., Didarul Islam, K. 2023. Model organism life extending therapeutics modulate diverse nodes in the drug-gene-microbe tripartite human longevity interactome. Journal of Biomolecular Structure and Dynamics. https://doi.org/10.1080/07391102.2023.2192823.
Interpretive Summary: Although there are many food-derived compounds that have been linked to improved lifespan in animal studies, the potential impact of these substances on human longevity is mostly untested. To address this knowledge gap, using a predictive modeling approach, we used computer-simulation to test the effect of many of these anti-aging candidates on human metabolic pathways, and identified potential positive effects for food-derived substances that are found in berries, red wine, green tea, onions, and others. This study may be a first step for use of these substances in studies aimed at improving human health, and potentially, lifespan in older adults.
Technical 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.