Project Probacine: A Novel In Silico Framework for Engineering a Precision Synbiotic Guild to Target Alzheimer's Neuroinflammation

Overview: This repository contains the official conference abstract, live presentation videos, and photographs of Rocher Adeyeye presenting at the All-Ireland Conference of Undergraduate Research (AICUR) 2026.

Abstract: Alzheimer’s Disease (AD) is increasingly characterised by gut-brain axis dysbiosis, specifically the depletion of neuroprotective microbial metabolites like Indole-3-Propionic Acid (IPA) and S-Equol. While Network Pharmacology (NP) offers a route to drug discovery, current methods typically rely on qualitative binary presence/absence data, failing to account for metabolite production rates or bioavailability in the human gut. To address this gap, this exploratory research introduces Quantitative Synbiotic Fragility Analysis (QSFA), a novel computational framework designed to engineer Probacine, a 6-strain precision synbiotic guild including Akkermansia muciniphila and Adlercreutzia equolifaciens.

Currently in the in silico design phase, this project adapts quantitative algorithms (Liu et al., 2026) to integrate Network Topology - identifying hub genes in the AD neuroinflammatory network, Metabolic Flux - predicted microbial production rates, and Binding Affinity - molecular docking scores against receptors like PXR and ER\beta into a single "Fragility Score". This score aims to predict the precise dosage required to collapse the neuroinflammatory network driving AD pathology.
The project further outlines a future potential validation workflow using the INFOGEST Quant (2025) static digestion model. By establishing protocols to quantify bio accessible metabolites in digestion supernatants via LC-MS/MS, this research aims to calibrate the computational model against real-world bioprocess data. This work represents a paradigm shift from generalised probiotics to engineered, dose-responsive biotherapeutics, offering a rigorous new methodology for determining the prophylactic potential of functional foods.