ArticleMolecules (Basel, Switzerland)2022
Docking, Binding Free Energy Calculations and In Vitro Characterization of Pyrazine Linked 2-Aminobenzamides as Novel Class I Histone Deacetylase (HDAC) Inhibitors.
Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- An AI-Assisted Workflow for Rapid Prioritization of FDA-Approved Drugs as HDAC3 Inhibitor Candidates for Drug Repurposing.Biology · 2026Article
- MINERVA: a public XAI-powered platform advancing multi-target discovery in Alzheimer's disease.Journal of cheminformatics · 2026Article
- Next-Generation HDAC Inhibitors: Advancing Zinc-Binding Group Design for Enhanced Cancer Therapy.Cells · 2025Review
- Potential Antidiabetic Inhibitors and Antimicrobials from the FungusJournal of microbiology and biotechnology · 2025Article
- New potent N-hydroxycinnamamide-based histone deacetylase inhibitors suppress proliferation and trigger apoptosis in THP-1 leukaemia cells.Archiv der Pharmazie · 2025Article
- A Review on Molecular Docking on HDAC Isoforms: Novel Tool for Designing Selective Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Statistical Improvement of rGILCC 1 and rPOXA 1B Laccases Activity Assay Conditions Supported by Molecular Dynamics.Molecules (Basel, Switzerland) · 2023Article
- Application of Ligand- and Structure-Based Prediction Models for the Design of Alkylhydrazide-Based HDAC3 Inhibitors as Novel Anti-Cancer Compounds.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Elucidation of bioinformatic-guided high-prospect drug repositioning candidates for DMD via Swanson linking of target-focused latent knowledge from text-mined categorical metadata.Frontiers in cell and developmental biology · 2023Article
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Authors and funding
9 authors.
Funding
Abstract
Class I histone deacetylases, HDAC1, HDAC2, and HDAC3, represent potential targets for cancer treatment. However, the development of isoform-selective drugs for these enzymes remains challenging due to their high sequence and structural similarity. In the current study, we applied a computational approach to predict the selectivity profile of developed inhibitors. Molecular docking followed by MD simulation and calculation of binding free energy was performed for a dataset of 2-aminobenzamides comprising 30 previously developed inhibitors. For each HDAC isoform, a significant correlation was found between the binding free energy values and in vitro inhibitory activities. The predictive accuracy and reliability of the best preforming models were assessed on an external test set of newly designed and synthesized inhibitors. The developed binding free-energy models are cost-effective methods and help to reduce the time required to prioritize compounds for further studies.
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Registered trials
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