Data Sheet 12_Identification and validation of γ-Linolenic acid as a natural FABP5 inhibitor in hepatocellular carcinoma through deep learning and experimental approaches.csv

BackgroundFatty acid binding protein 5 (FABP5) is implicated in hepatocellular carcinoma (HCC) progression and represents a potential therapeutic target.
MethodsWe integrated machine learning–based virtual screening, molecular docking and molecular dynamics simulations to identify natural compounds with high binding affinity to FABP5. Candidate compounds were further validated by in-vitro assays in HCC cell lines, including proliferation, migration/invasion, apoptosis/ferroptosis-related readouts, and mechanistic validation.
ResultsThe optimized models enabled efficient screening of natural products and prioritized γ-linolenic acid (GLA) as a top candidate FABP5 inhibitor. Docking and simulations supported stable binding and key residue interactions. Experimentally, GLA inhibited HCC cell proliferation and aggressiveness and promoted cell death–related pathways consistent with anti-tumor activity.
ConclusionOur deep learning–guided workflow identified γ-linolenic acid as a natural FABP5 inhibitor and supports its potential as a lead compound for HCC therapy.