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Updated: Jan 16, 2026
Simultaneous Measurement of HDAC1 and HDAC6 Activity in HeLa Cells Using UHPLC-MS
Published on: August 10, 2017
Discovery of selective HDAC6 inhibitors driven by artificial intelligence and molecular dynamics simulation
Xingang Liu1,2, Hao Yang2, Xinyu Liu2
1Department of Pharmacology, Hebei Medical University, Shijiazhuang, 050017, China.
Abstract:
Increasing evidence showed that histone deacetylase 6 (HDAC6) dysfunction is directly associated with the onset and progression of various diseases, especially cancers, making the development of HDAC6-targeted anti-tumor agents a research hotspot. In this study, artificial intelligence (AI) technology and molecular simulation strategies were fully integrated to construct an efficient and precise drug screening pipeline, which combined Voting strategy based on compound-protein interaction (CPI) prediction models, cascade molecular docking, and molecular dynamic (MD) simulations. The biological potential of the screened compounds was further evaluated through enzymatic and cellular activity assays. Among the identified compounds, Cmpd.18 exhibited more potent HDAC6 enzyme inhibitory activity (IC50 = 5.41 nM) than that of tubastatin A (TubA) (IC50 = 15.11 nM), along with a favorable subtype selectivity profile (selectivity index ≈ 117.23 for HDAC1), which was further verified by the Western blot analysis. Additionally, Cmpd.18 induced G2/M phase arrest and promoted apoptosis in HCT-116 cells, exerting desirable antiproliferative activity (IC50 = 2.59 μM). Furthermore, based on long-term MD simulation trajectory, the key residues facilitating Cmpd.18's binding were identified by decomposition free energy analysis, thereby elucidating its binding mechanism. Moreover, the representative conformation analysis also indicated that Cmpd.18 could stably bind to the active pocket in an effective conformation, thus demonstrating the potential for in-depth research of the 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold.
Insights
Artificial intelligence and molecular simulations identified Cmpd.18 as a potent inhibitor of histone deacetylase 6 (HDAC6), showing anti-cancer effects in cells and potential for drug development.
Area of Science:
- Biochemistry
- Computational Chemistry
- Pharmacology
Background:
- Histone deacetylase 6 (HDAC6) dysfunction is linked to various diseases, particularly cancers.
- Targeting HDAC6 is a promising strategy for developing novel anti-cancer agents.
Purpose of the Study:
- To develop an efficient drug screening pipeline using AI and molecular simulations.
- To identify and characterize novel HDAC6 inhibitors with anti-tumor potential.
Main Methods:
- Integrated AI with molecular simulations, including compound-protein interaction prediction, molecular docking, and molecular dynamics (MD) simulations.
- Evaluated biological potential through enzymatic and cellular activity assays.
- Analyzed binding mechanisms using MD simulations and free energy decomposition.
Main Results:
- Cmpd.18 demonstrated potent HDAC6 inhibition (IC50 = 5.41 nM) and selectivity over HDAC1 (selectivity index ≈ 117.23).
- Cmpd.18 induced G2/M phase arrest and apoptosis in HCT-116 cells, exhibiting significant antiproliferative activity (IC50 = 2.59 μM).
- MD simulations elucidated Cmpd.18's stable binding to the HDAC6 active pocket via key residues.
Conclusions:
- The developed AI-driven pipeline efficiently identified Cmpd.18 as a promising HDAC6 inhibitor.
- Cmpd.18 exhibits significant anti-cancer properties and a favorable binding mechanism, warranting further research.
- The 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold shows potential for developing novel HDAC6-targeted therapies.
