Affiliations 

  • 1 Department of Food Science and Technology, Faculty of Agricultural Technology, Brawijaya University, Malang, Indonesia
  • 2 Drug Discovery and Synthetic Chemistry Research Group, Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan, Pahang, Malaysia
  • 3 Atta-ur-Rahman Institute for Natural Products Discovery (AuRIns), Universiti Teknologi MARA, Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia
  • 4 Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
  • 5 Faculty of Industrial Sciences & Technology, Universiti Malaysia Pahang, Gambang, Pahang, Malaysia
  • 6 Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
  • 7 Academic of Pharmacy and Food Analysis of Putra Indonesia Malang, East Java, Indonesia
  • 8 Faculty of Pharmacy and Health Sciences, Universitas Abdurrab, Pekanbaru, Riau, Indonesia
  • 9 Centre for Bio-Aromatic Research, Universiti Malaysia Pahang, Gambang, Pahang, Malaysia
  • 10 Department of Pharmaceutical Technology, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan, Pahang, Malaysia
J Biomol Struct Dyn, 2024 Dec 05.
PMID: 39633610 DOI: 10.1080/07391102.2024.2436553

Abstract

Monoamine oxidase (MAO) is crucial for the breakdown of monoamine neurotransmitters, making it a promising target for treating neurodegenerative disorders, such as depression, Alzheimer's disease, and Parkinson's disease. In this study, we investigated the selective inhibitory activity of chromone-based compounds against MAO-A and MAO-B for neurodegenerative disease treatment. In literary sources, thirty chromone derivatives have been identified as potential ligands for MAO-A and MAO-B inhibitors. We utilized molecular docking to evaluate how the most active compound interacted with the targeted MAO-A and MAO-B. Compound 2 g, the most active for MAO-A, demonstrated a lower CDOCKER energy compared to the co-crystallized ligand. Meanwhile, compound 2f, the most active for MAO-B, showed a CDOCKER energy similar to the co-crystallized ligand and exhibited similar binding patterns. Furthermore, we constructed a quantitative structure-activity relationship (QSAR) model to predict the properties and estimate IC50 values for 30 chromone derivatives functioning as MAO-A and MAO-B inhibitors. The model predictions were validated against experimental measurements. Our 2D QSAR model demonstrated robustness, with a statistically significant non-cross-validated coefficient (r2 < 0.9), cross-validated correlation coefficient (q2 < 0.6), and predictive squared correlation coefficient (r2pred < 0.8). Additionally, MD simulations confirmed the stable binding of compounds 2 g and 2f with MAO-A and MAO-B, respectively, displaying substantial binding energy. The most effective pharmacophore model identified key features, such as hydrogen bond acceptors and hydrophobic interactions, that contribute significantly to inhibitory potency. This study offers valuable insight into the selection of compounds with improved selectivity for MAO inhibition.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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