Cells undergo a controlled and systematic cycle of growth, replication and death. However, the integrity of this process gradually declines, leading to accumulation of senescent cells, a major hallmark of biological ageing. Dietary algae, particularly marine algae, have been long reported to exert anti-ageing benefits as cosmeceuticals and nutraceuticals with limited understanding of the molecular mechanisms underlying their activity. In this study, we have incorporated 1,202 previously reported bioactive small phycocompounds and subjected them to cheminformatic queries to assess these interactions. In-silico ADMET, 2-phase docking, metabolic pathway interaction and molecular dynamics simulations reveal multiple marine phycocompounds to have safe and effective senolytic potentials. We employed a novel deep convolutional neural network driven screening approach to identify (2R*, 3S*, 6R*, 7S*, 10R*, 13R*)-7,13-Dihydroxy-2,6-cyclo-1(9),14-xenicadiene-18,19-dial derived from Dilophus Fasciola, Laurendecumenyne A from Laurencia decumbens and 4-Bromo-3-ethyl-9-[(2E)-2-penten-4-yn-1-yl]-2,8-dioxabicyclo[5.2.1]decan-6-ol from Laurencia sp. to be potent inhibitors of multiple target senescent-cell anti-apoptotic pathway proteins. We simulated the best overall target inhibitors, specific protein inhibitors and molecular pathway regulators with each target protein and found stable interactions with minimum deviations (mean RMSD = 0.17 ± 0.01 nm) and gyrations (mean Rg = 1.64 ± 0.16 nm) of the simulated protein-compound complexes. Finally, molecular mechanics calculation suggests potent (mean ΔG = -69.56 ± 27.19 kCal/mol) and frequent hydrophobic interactions between the top performing marine phycocompounds and target proteins.
Keywords: Anti-ageing; cheminformatics; drug discovery; marine algae; senolytics.