This study focuses on an in silico comparative and descriptive analysis of the phytochemical compounds in Rubus fruticosus (blackberry) using the computational tool SwissADME, with an emphasis on their potential applicability to neurodegenerative diseases such as Alzheimer’s disease (AD). SwissADME enables the prediction of comprehensive pharmacokinetic profiles, including gastrointestinal absorption (HIA), blood–brain barrier (BBB) permeability via the BOILED-Egg model, and drug likeness. Moreover, this study evaluates the probability of these compounds being actively effluxed by P-gp (PGP+), which is crucial for assessing their bioavailability and potential therapeutic effectiveness in the central nervous system. The interaction of phytochemicals with P-gp can significantly influence their ability to penetrate the BBB, with higher efflux probabilities indicating reduced central nervous system accessibility. Additionally, similarities and differences between these compounds are highlighted to assess their therapeutic potential.

Using SwissTargetPrediction and SwissDock, this study further evaluates the interaction of these phytochemicals with crucial enzymes and molecular targets involved in neurodegeneration, such as β-secretase and acetylcholinesterase (implicated in amyloid plaque formation and cholinergic signaling); kinases like GSK3β, CDK5, and ERK2 (involved in tau protein hyperphosphorylation and neurodegeneration); β-amyloid protein; and microtubule-associated protein tau (amyloid plaques and NFTs—critical in AD pathology).

Key bioactive compounds from Rubus fruticosus—noted for their antioxidant, anti-inflammatory, and neuroprotective effects—are compared against established AD treatments, including galantamine and rivastigmine.

This comparative analysis underscores the potential of Rubus fruticosus phytochemicals as viable candidates for developing treatments for neurodegenerative diseases, with the potential to enhance cognitive function and delay or slow disease progression in conditions like AD. By integrating computational methods into our analysis, this research seeks to facilitate the discovery and development of new drugs from natural sources, like Rubus fruticosus, while emphasizing the necessity of experimental validation to confirm bioinformatic predictions.