1. Academic Validation
  2. In silico discovery of natural compound-derived multi-target inhibitor for Huntington's disease therapy

In silico discovery of natural compound-derived multi-target inhibitor for Huntington's disease therapy

  • Sci Rep. 2026 Feb 7;16(1):7716. doi: 10.1038/s41598-026-38430-w.
Bo Zheng 1 Mehrukh Banday 2 Shalesh Gangwar 2 Mohamed Abbas 3 4 Khalid Raza 5 6
Affiliations

Affiliations

  • 1 College of Basic Medical Sciences, China Three Gorges University, Yichang, Hubei, China.
  • 2 Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi, India.
  • 3 Electrical Engineering Department, College of Engineering, King Khalid University, 61421, Abha, Saudi Arabia.
  • 4 Central Labs, King Khalid University, AlQuraa, Abha,, P.O. Box 960, 61421, Saudi Arabia.
  • 5 Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi, India. kraza@jmi.ac.in.
  • 6 Faculty of Pharmaceutical Sciences, UCSI University, 56000, Kuala Lumpur, Malaysia. kraza@jmi.ac.in.
Abstract

Huntington’s disease (HD) is a progressive, autosomal dominant neurodegenerative disorder characterized by cognitive decline, psychiatric disturbances, and motor dysfunction. HD eventually leads to severe dementia, speech loss, and complete motor incapacitation. Despite extensive research, no curative therapy exists; current treatments are limited to symptomatic relief. The molecular pathology of HD involves mitochondrial dysfunction, protein aggregation, and excitotoxicity, indicating that a multitargeted therapeutic approach may be more effective. This study aimed to identify a novel multi-target inhibitor with potential efficacy against key proteins implicated in HD pathogenesis. An in silico strategy was employed to identify a multi-target inhibitor targeting three proteins critical to HD: Kynurenine 3-Monooxygenase (KMO), Caspase-6, and Glycogen Synthase Kinase 3 Beta (GSK-3β). Structure-based drug design and virtual screening were conducted, followed by pharmacokinetic profiling, molecular docking, and molecular dynamics simulations. Further, MM/GBSA free energy calculations and WaterMap analysis were performed to evaluate binding energetics and solvent interactions. DTB-acid emerged as the most promising candidate, exhibiting favourable docking and binding energetics across all three proteins. IFD docking produced scores of − 9.03 kcal/mol (Caspase-6), − 7.33 kcal/mol (KMO), and − 7.96 kcal/mol (GSK-3β). MM/GBSA binding free energies confirmed a stable and energetically favourable association, with dG values of − 31.03, − 36.58, and − 27.15 kcal/mol for Caspase-6, KMO, and GSK-3β, respectively. WaterMap analysis further supported thermodynamic feasibility, revealing favourable hydration contributions, particularly for GSK-3β (dG = − 33.99 kcal/mol). MD simulations demonstrated stable protein–ligand complexes over 100 ns. The study underscores the potential of multitarget computational approaches in tackling complex diseases like HD. DTB-acid emerges as a promising lead molecule, meriting further experimental validation through in vitro and in vivo studies for its therapeutic potential in HD.

Supplementary Information: The online version contains supplementary material available at 10.1038/s41598-026-38430-w.

Keywords

Huntington’s disease; Molecular docking; Molecular dynamics simulation; Multitargeted inhibitor.

Figures
Products