A Comprehensive Computational Investigation of Novel Hydrazide–Hydrazone Derivatives as Potential EGFR Inhibitors for Gastric Cancer Treatment

QSAR, molecular dynamics, and biological evaluation of novel myeloperoxidase inhibitors via ligand-based pharmacophore modeling as potential anticancer agents

The findings from molecular docking, 500-ns molecular dynamics simulations, MM-GBSA calculations, and alanine scanning analyses collectively corroborate a stable binding mode of BTB11556 within the MPO active site, support further investigation of BTB11556 as a candidate compound associated with MPO-targeted therapeutic strategies.

Quinazolinone–hydroxamate derivatives as potential HDAC8 inhibitors: An integrated docking, ADME, DFT, and molecular dynamics study

Cancer remains a major global health challenge, highlighting the need for novel therapeutic agents with improved selectivity and efficacy. Histone deacetylase (HDAC) inhibition represents an important epigenetic strategy in anticancer drug discovery because it can influence gene expression, cell-cycle regulation, and tumor cell survival. In this computational study, fifteen 4-oxoquinazolin-3(4 H )-yl- N -hydroxybenzamide derivatives were evaluated as potential HDAC8-targeting compounds using an integrated in silico workflow. Molecular docking was performed against HDAC8 using the crystal structure deposited under Protein Data Bank (PDB) ID 1T69, with suberoylanilide hydroxamic acid (SAHA) used as the reference inhibitor. The investigated derivatives showed favorable accommodation within the HDAC8 catalytic pocket, with predicted interaction patterns involving zinc coordination, hydrogen bonding, and π-related interactions with key active-site residues. Several derivatives showed favorable predicted docking scores and interaction profiles relative to SAHA, suggesting that the designed quinazolinone–hydroxamate scaffold may be suitable for further prioritization. Prime molecular mechanics generalized Born surface area (MM-GBSA) analysis identified selected derivatives with comparatively favorable calculated binding free-energy contributions, particularly through van der Waals, electrostatic, and lipophilic interactions. In silico absorption, distribution, metabolism, and excretion (ADME) prediction indicated that most derivatives possessed acceptable drug-like and pharmacokinetic descriptors, including physicochemical properties, predicted oral absorption, and limited central nervous system (CNS) activity. Density functional theory (DFT) analysis provided supportive electronic-level information by identifying molecular regions that may contribute to hydrogen bonding and zinc coordination. A 100 ns molecular dynamics simulation of the HDAC8–derivative 15 complex suggested the short-timescale persistence of one representative predicted binding pose under the selected simulation conditions. Overall, this study identifies selected 4-oxoquinazoline hydroxamic acid derivatives as preliminary computational leads for further experimental validation as potential HDAC8-targeting compounds.

Tetrazole–imidazole hybrid derivatives as potential EGFR tyrosine kinase inhibitors: design, synthesis and in silico evaluation with preliminary antiproliferative assessment

Structure-based elucidation of thiazine inhibitors targeting estrogen receptors alpha: pharmacophore modeling, virtual screening, molecular docking, MD, and DFT approach.

This research developed a promising lead molecule (HIT1) as a therapeutic approach for ER-positive breast cancer through pharmacophore model-based drug design of thiazine derivative targeting ERα via pharmacophore model-based drug design.

In silico investigation of novel isatin derivatives as potential multi-target anticancer agents targeting VEGFR-2, EGFR, and caspase-6.

This study highlights the usefulness of computational approaches in the discovery of novel isatin-based multi-target lead candidates for cancer therapy and suggests that compound 4 represents a promising lead for further investigation.

QSAR of Novel Chrysin Benzimidazole Derivatives for Potential Anti-Cancer Agents

The current study focuses on developing a Quantitative Structure-Activity Relationship (QSAR) model for novel chrysin-benzimidazole derivatives as possible anti-cancer drugs for hepatocellular carcinoma (HepG2 cell line). The biological activity of 21 substances was measured using IC₅₀ values, which were then converted to pIC₅₀ for better statistical analysis. Molecular structures were optimized with the semi-empirical PM3 method, and ChemOffice software was used to calculate several physicochemical characteristics. Multiple linear regression analysis was used to find relationships between molecular characteristics and biological activity. The created QSAR models revealed a strong link between structural features and anticancer efficacy, emphasizing the significance of descriptors such as molar refractivity, partition coefficient, and related factors. The validated model demonstrated satisfactory prediction ability on both the training and test sets. This study sheds light on the structural prerequisites for anticancer action, which may aid in the rational development of more effective benzimidazole-based medicinal medicines.