# Targeting epigenetic regulators: In-silico discovery of natural inhibitors against histone demethylase KDM4C

## TL;DR

This study uses computer modeling to find natural compounds that can inhibit the KDM4C enzyme, a target for cancer treatment.

## Contribution

The study identifies pectolinarin and compound 202 as novel natural inhibitors of KDM4C through in-silico methods.

## Key findings

- Pectolinarin and compound 202 showed better docking scores and stable interactions with KDM4C than the reference ligand.
- MD simulations confirmed the stability of the KDM4C-inhibitor complexes over 200 ns with low RMSD and RMSF values.
- ADMET predictions indicated favorable drug-like properties, including oral bioavailability and low toxicity for both compounds.

## Abstract

Cancer is a multifaceted disease driven by genetic mutations and epigenetic dysregulation. Among epigenetic modifiers, histone demethylases like KDM4C (lysine demethylase 4C) play a pivotal role in tumor progression by removing repressive methylation mark at Histone H3K9/H3K36 and altering chromatin structure and gene expression. Overexpression of KDM4C has been implicated in various malignancies, including breast, prostate, colorectal, and hepatocellular carcinomas, hence it is promising drug target. This study employs a structure-based drug discovery strategy to identify natural polyphenolic inhibitors of KDM4C. High-throughput virtual screening, followed by molecular docking, molecular dynamics (MD) simulations, and MM-GBSA free energy calculations, used to assess binding potential. Pectolinarin and compound 202 emerged as top candidates, outperforming the reference ligand (6X9) used from PDBID: 5KR7, in docking scores, and exhibiting robust hydrogen bonding and hydrophobic interactions within the active site. MD simulations over 200 ns confirmed complex stability, indicated by consistently low RMSD and RMSF values. MM-GBSA analysis revealed strong binding affinities with free energy values of −68.4 kcal/mol and −65.7 kcal/mol for Pectolinarin and compound 202, respectively. ADMET predictions supported their drug-likeness, suggesting favorable pharmacokinetic profiles, oral bioavailability, and low toxicity. These findings highlight pectolinarin and compound 202 as promising leads for KDM4C-targeted cancer therapy. Further experimental validation is required to confirm their efficacy and specificity. Overall, this work demonstrates the potential of computational approaches in advancing the discovery of nature-derived epigenetic therapeutics.