Integrative in silico analysis identifies multitarget mechanisms of Pterostilbene in neurodegenerative diseases, suggesting future experimental studies.
Background: Neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS), differ in etiology but share several convergent pathological mechanisms. Pterostilbene (PTR) is a natural stilbene with reported antioxidant, anti-inflammatory, and neuroprotective properties. This study aimed to prioritize putative PTR-associated targets and biological processes potentially relevant to shared neurodegenerative mechanisms. Methods: An integrative in silico workflow combining network pharmacology, protein–protein interaction (PPI) analysis, GO Biological Process (GO BP) enrichment, molecular docking, and molecular dynamics (MD) simulations was applied. GO BP terms were filtered, focused on neurodegeneration- and neuroprotection-related processes, and subjected to REVIGO-based redundancy reduction. Selected targets were further evaluated by docking and 500 ns MD simulations. Results: A total of 181, 165, 128, and 109 shared PTR–disease targets were identified for AD, PD, HD, and ALS, respectively. Redundancy-reduced GO BP analysis indicated associations with neuroinflammation, oxidative stress and reactive oxygen species-related responses, programmed cell death, MAPK/ERK- and PI3K/AKT-related signaling, ion and calcium transport, and lipid-, steroid-, or hormone-associated regulation. PPI topology prioritized SRC, ESR1, and HSP90AA1 as recurrent hub–bottleneck proteins, whereas MD-based structural interpretation focused on ESR1 and HSP90AA1. MD analyses indicated stable PTR interactions with both proteins, with ESR1 showing the most favorable predicted interaction profile. Conclusions: These findings suggest that PTR may interact with shared neurodegeneration-relevant molecular systems, particularly through ESR1- and HSP90AA1-associated mechanisms. However, the results are exclusively computational and should be interpreted as hypothesis-generating, requiring further experimental validation.
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Rosiak et al. (2026) studied this question.
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