Network-integrated Virtual Screening Identifies HIF-1α Targeting Phytochemicals from Ajuga decumbens

Abstract

Background: Tumour hypoxia is a critical hallmark of cancer progression, contributing to metastasis, therapeutic resistance, and poor clinical outcomes. Hypoxia-inducible factor-1 alpha (HIF-1α) regulates cellular adaptation to hypoxia by modulating angiogenesis, metabolism, and survival. Targeting HIF-1α represents a potential therapeutic strategy, while natural compounds provide a valuable source of bioactive molecules. Aim: To identify and evaluate phytochemicals derived from Ajuga decumbens as potential HIF-1α-targeting compounds using an integrated computational approach. Methods: Twelve phytochemicals were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and evaluated against HIF-1α (PDB ID: 3KCX). Molecular docking was performed using AutoDock Vina. Protein–protein interaction analysis was conducted using STRING. Drug-likeness and pharmacokinetic properties were assessed using Lipinski’s rule of five and SwissADME, respectively. The stability of the top-ranked protein–ligand complex was further evaluated using 50-ns molecular dynamics simulation based on RMSD, RMSF, hydrogen bonding, and radius of gyration. Results: All selected compounds demonstrated favourable predicted binding affinities toward HIF-1α, ranging from −6.5 to −10.3 kcal/mol. Ajugalactone exhibited the strongest predicted binding affinity (−10.3 kcal/mol), followed by ecdysterone (−9.1 kcal/mol) and ajugacumbin F (−9.0 kcal/mol). Recurrent interactions involved Gln203, Asp201, Arg238, and Trp296. Ajugalactone showed no Lipinski violations, high predicted gastrointestinal absorption, and no predicted blood–brain barrier permeability. Molecular dynamics simulation demonstrated stable behaviour of the HIF-1α–ajugalactone complex over 50 ns, with RMSD of 0.22–0.30 nm, 2–4 hydrogen bonds, and Rg of 2.15–2.25 nm. Conclusion: A. decumbens phytochemicals, particularly ajugalactone, represent promising computationally predicted HIF-1α-targeting candidates. Further biochemical and experimental validation is required to establish their HIF-1α inhibitory and anticancer activity. Major Findings: Ajugalactone showed the strongest predicted binding toward HIF-1α (−10.3 kcal/mol) and maintained a stable protein–ligand complex during the 50-ns Molecular Dynamics (MD) simulation. The integrated computational findings identify ajugalactone as a promising lead for subsequent experimental validation.