# Identification and validation of γ-Linolenic acid as a natural FABP5 inhibitor in hepatocellular carcinoma through deep learning and experimental approaches

## TL;DR

This study identifies γ-linolenic acid as a natural inhibitor of FABP5, a protein linked to liver cancer, using deep learning and experiments.

## Contribution

The study introduces a deep learning workflow to discover γ-linolenic acid as a novel FABP5 inhibitor for hepatocellular carcinoma.

## Key findings

- γ-linolenic acid showed high binding affinity to FABP5 through virtual screening and simulations.
- GLA inhibited HCC cell proliferation and aggressiveness in vitro.
- GLA promoted cell death pathways, indicating anti-tumor potential.

## Abstract

Fatty acid binding protein 5 (FABP5) is implicated in hepatocellular carcinoma (HCC) progression and represents a potential therapeutic target.

We 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.

The 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.

Our deep learning–guided workflow identified γ-linolenic acid as a natural FABP5 inhibitor and supports its potential as a lead compound for HCC therapy.