What question did this study set out to answer?

This research aims to identify dual inhibitors for HDAC and VEGFR2 as potential anticancer drugs using computational methods.

April 28, 2026Open Access

Computational investigation of dual HDAC and VEGFR2 inhibitors using DFT, QSAR and molecular dynamics for rational anticancer drug design

Puntos clave

This research aims to identify dual inhibitors for HDAC and VEGFR2 as potential anticancer drugs using computational methods.
Screening 36 quinazoline analogues through molecular docking and molecular dynamics simulations (500 ns).
Utilization of density functional theory (DFT), MMGBSA, pharmacophore modeling, and robust 3D-QSAR techniques.
Predictions of ADME and toxicity to evaluate drug-likeness and safety profiles.
Compound 20 shows high binding affinities to HDAC and VEGFR2, outperforming reference drugs Panobinostat and Pazopanib.
Robust 3D-QSAR models demonstrate strong predictivity with maximum R2 = 0.981.
MMGBSA calculations indicate positive binding free energies and favorable electronic characteristics for dual inhibition.

Resumen

The development of dual inhibitors against histone deacetylases (HDACs) and vascular endothelial growth factor receptor 2 (VEGFR2) is a promising approach in the treatment of cancers. A detailed computational screening of 36 quinazoline analogues was conducted in the context of identifying any possible dual HDAC & VEGFR2 inhibitors in this study. A detailed in-silico workflow was used, comprising of molecular docking, molecular dynamics (500 ns), MMGBSA binding free energy, density functional theory (DFT), pharmacophore modelling and 3D-QSAR (PLS, MLR and GFA). The predications of ADME and toxicity were made to determine the drug-likeness and safety profiles. Compound 20 also exhibited high binding affinities to HDAC and VEGFR2, which are better than the reference drugs Panobinostat and Pazopanib. RMSD, RMSF and hydrogen-bond assays were used to ascertain stable protein and ligand complexes. Calculation of MMGBSA showed positive binding free energies. Strong predictivity has been demonstrated by robust 3D-QSAR models (maximum R2 = 0.981), whereas DFT analysis has revealed the presence of good electronic characteristics to facilitate dual inhibition. All the interaction analyses, dynamic stability, electronic properties and structure-activity relationships sustained the dual inhibitory nature of Compound 20. Its toxicity, limited penetration into BBB and good ADME characteristics further enhanced its therapeutic relevance. The present integrative computational research confirms that Compound 20 is an effective dual HDAC-VEGFR2 that has high anticancer potential. The results offer a logical basis on the continued experimental validation and development of dual-target anticancer therapeutics.

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