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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
Identification of Potent HDAC6 Inhibitors for Breast Cancer Through Multi-Stage In Silico Modeling
Vaishali Pankaj1, Inderjeet Bhogal1, Sudeep Roy1
1Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czech Republic.
Abstract:
Histone deacetylases (HDACs) are essential epigenetic regulators, with HDAC6 overexpression linked to estrogen receptor (ER) activity and breast cancer progression. While several HDAC6 inhibitors have been investigated, their clinical success remains limited due to toxicity and off-target effects, necessitating the discovery of novel, selective inhibitors. This study employs a multi-stage computational approach to identify potent HDAC6 inhibitors for breast cancer therapy. A large-scale virtual screening of 264 834 compounds was conducted, followed by molecular docking, molecular dynamics (MD) simulations (100 ns), molecular mechanics/generalized born surface area (MM/GBSA) binding free energy calculations, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions. The HDI-3 emerged as the most promising candidate among replicate simulations, exhibiting a substantially favorable MM/GBSA binding free energy of -130.67 kcal/mol-indicative of strong thermodynamic stability and stronger binding affinity compared to reference inhibitors Trichostatin A and Ricolinostat. Molecular dynamics simulations revealed that HDI-3 maintained structural stability, persistent key interactions with active site residues (ASP649, HIS651, ASP742), and low conformational fluctuations. The ADMET evaluation confirmed HDI-3's favorable pharmacokinetic properties, including optimal bioavailability, non-mutagenicity, and low hepatotoxicity. Essential dynamics and principal component analysis further validated its stable binding profile. While these findings highlight HDI-3 as a selective and pharmacologically viable HDAC6 inhibitor, it is important to acknowledge that the results are entirely computational. Therefore, experimental validation is essential to confirm the compound's efficacy and safety. This integrated computational pipeline provides an efficient strategy to accelerate targeted drug discovery, laying the groundwork for future experimental investigations.
Insights
Researchers identified HDI-3, a potent computational HDAC6 inhibitor for breast cancer therapy. This selective compound shows promise for drug discovery, though experimental validation is crucial.
Area of Science:
- Epigenetics and Molecular Biology
- Computational Chemistry and Drug Discovery
- Oncology
Background:
- Histone deacetylases (HDACs) are critical epigenetic regulators.
- HDAC6 overexpression is associated with estrogen receptor (ER) activity and breast cancer progression.
- Existing HDAC6 inhibitors face challenges with toxicity and off-target effects, driving the need for novel, selective agents.
Purpose of the Study:
- To identify potent and selective HDAC6 inhibitors for breast cancer therapy using a multi-stage computational approach.
- To evaluate the binding affinity, stability, and pharmacokinetic properties of potential drug candidates.
Main Methods:
- Large-scale virtual screening of over 264,000 compounds.
- Molecular docking, 100 ns molecular dynamics (MD) simulations, and MM/GBSA binding free energy calculations.
- Absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions and essential dynamics analysis.
Main Results:
- HDI-3 emerged as the most promising candidate, demonstrating strong binding affinity (-130.67 kcal/mol MM/GBSA) and thermodynamic stability.
- MD simulations confirmed HDI-3's stable interactions with key active site residues (ASP649, HIS651, ASP742) and low conformational fluctuations.
- ADMET predictions indicated favorable pharmacokinetic properties for HDI-3, including good bioavailability and low toxicity.
Conclusions:
- HDI-3 is a computationally identified selective and pharmacologically viable HDAC6 inhibitor with potential for breast cancer treatment.
- The integrated computational pipeline offers an efficient strategy for targeted drug discovery.
- Experimental validation is essential to confirm the efficacy and safety of HDI-3.

