Computational and network-based strategies for neuroprotection against oxidative stress in neurodegenerative disorders

Neurodegenerative disorders are defined by progressive neuronal dysfunction and death, in which oxidative stress is recognized as a central contributor to disease pathology. While experimental studies have established the critical role of oxidative stress in these conditions, the discovery of effective neuroprotective interventions remains a major challenge. This complexity arises from the intricate architecture of redox signaling networks, multi-target interactions, and the limited translational success inherent to single-target approaches. Recent advances in molecular docking, density functional theory calculations, and network pharmacology now provide systematic tools for interrogating compound-target interactions along with pathway-level effects relevant to neuronal survival. The integration of these computational strategies with experimental validation in neuronal model systems offers a scalable framework for discovering and prioritizing neuroprotective strategies with enhanced translational potential. However, a significant gap persists between computational capability and therapeutic impact due to a lack of cross-validation between predictions and mechanistic or functional neurobiology.This Research Topic aims to highlight computationally driven discovery pipelines that address oxidative stress-mediated neurodegeneration through the integration of in-silico predictions and experimental neurobiology. Specifically, it seeks to bridge the disconnect that often exists where computational or experimental work occurs in isolation, by encouraging the submission of studies that incorporate both computational predictions and their experimental validation. The goal is to identify, prioritize, and validate neuroprotective compounds and mechanisms with realistic translational trajectories. Research questions include how network-level insights can reveal therapeutic opportunities missed by single-target approaches, what system-level mechanisms underlie successful neuroprotection, and how experimental outcomes inform the refinement of computational models.To gather further insights in this interdisciplinary and translational field, we welcome articles that combine rigorous computational methods with functional neurobiology, and that demonstrate integration between both approaches. Purely computational or isolated experimental studies will not be considered unless they present genuinely novel methodologies. The scope includes, but is not limited to, the following themes:• Structure-based computational approaches, including molecular docking, binding affinity prediction, density functional theory calculations, and multi-target screening targeting oxidative stress pathways and neuronal survival• Network pharmacology and systems biology: construction and analysis of compound-target-pathway networks and protein-protein interaction maps using neurodegeneration and oxidative stress datasets• Experimental validation in neuronal models, including SH-SY5Y cells, primary neurons, or human iPSC-derived neurons, or animal models subjected to oxidative or metabolic stress relevant to disease conditions• Integrative translational studies that connect computational findings with transcriptomic, proteomic, metabolomic, or clinical data, including biomarker identification and validation in patient-derived samples or mechanism-based clinical hypotheses• Methodological innovations that enable the integration of computational and experimental strategies for neuroprotective discovery Topic editors: Dr. Supriyo Saha, Nawab John Dar, Shahnawaz Ali Bhat Source: https://www.frontiersin.org/research-topics/77165/computational-and-network-based-strategies-for-neuroprotection-against-oxidative-stress-in-neurodegenerative-disorders