Molecular Docking and Pharmacological In Silico Evaluation of Genistein and Hematoxylin as Promising Ribonucleotide Reductase-targeted Therapies for Cancer.

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

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.

In silico evaluation of Syzygium cumini phytochemicals as BCL-2 inhibitors: molecular docking and molecular dynamics simulations for gastric cancer therapy

Design and Evaluation of Naphthoxy and Phenoxy amide as Potential PARP 1 inhibitors: Molecular Docking and In Vitro Analysis.

INTRODUCTION The objective was to design, synthesize, and evaluate novel naphthoxy and phenoxy amide derivatives as potential poly(ADP-ribose) polymerase-1 (PARP1) inhibitors, aiming to identify compounds with improved binding affinity, favorable pharmacokinetic properties, and enhanced anticancer activity compared with existing PARP1 inhibitors. METHODS A series of naphthoxy and phenoxy amide derivatives (A1-A9 and B1-B9) were evaluated using combined computational and experimental approaches. Molecular docking against PARP1 (PDB ID: 4ZZZ) was performed using Glide to assess binding affinity. ADMET and drug-likeness properties were predicted via SWISS-ADME, and binding free energies were refined using Prime MM-GB/SA. The lead compound B2 underwent a 50-ns molecular dynamics simulation using Desmond. In vitro cytotoxicity was assessed against MCF-7 human breast cancer cell lines. RESULTS Compounds B2 and B3 exhibited strong docking scores comparable to the reference PARP1 inhibitor and demonstrated favourable ADMET profiles. MM-GB/SA analysis supported their high binding affinity toward PARP1. Molecular dynamics simulations revealed that compound B2 formed a stable complex within the PARP1 active site. In vitro assays showed enhanced cytotoxic activity of B2 against MCF-7 cells. DISCUSSION The findings highlight the effectiveness of combining computational and biological approaches to identify promising PARP1 inhibitors, with B2 showing strong binding, stability, and cytotoxicity, despite lacking in vivo validation. CONCLUSION Overall, compound B2 emerged as a promising PARP1 inhibitor with strong binding affinity, structural stability, and significant in vitro anticancer activity, warranting further optimization and preclinical investigation.

Computational Investigation of Cinnamon Phytochemicals Targeting Key Cancer Signaling Pathways: Molecular Docking, ADMET and Molecular Dynamics Simulations Analysis

Cancer remains one of the leading causes of morbidity and mortality worldwide, highlighting the need for safe and effective therapeutic strategies targeting multiple oncogenic pathways. Cinnamon (Cinnamomum spp.) contains several bioactive phytochemicals with reported antioxidant and anticancer properties; however, their potential interactions with key cancer-associated signaling proteins have not been comprehensively investigated. In this study, an integrated computational and preliminary experimental approach was employed to evaluate four major cinnamon phytochemicals, namely e-cinnamaldehyde, eugenol, p-cymene, and cinnamic acid. Consensus molecular docking was performed using AutoDock Vina (v1.2.7), Smina (v2020.12.10), and GNINA (v1.3.3) against phosphoinositide 3-kinase (PI3K), nuclear factor kappa B (NF-κB), and mammalian target of rapamycin (mTOR). Docking analyses were complemented by protein-ligand interaction profiling, pharmacokinetic and toxicity prediction (ADMET), and a 100 ns molecular dynamics simulation with MM/GBSA binding free-energy analysis of the selected mTOR-p-cymene complex. In addition, the antioxidant activity and cytotoxic effects of a crude methanolic cinnamon bark extract were evaluated using in vitro antioxidant assays and MTT assays against HCT-116 and HT-29 colorectal cancer cell lines. Consensus docking predicted that all four phytochemicals were capable of interacting with the selected protein targets, although the predicted binding profiles varied among the compounds. Eugenol showed comparatively more favorable predicted interactions with PI3K, p-cymene produced the lowest predicted docking score for NF-κB, and cinnamic acid displayed a comparatively consistent predicted multitarget binding profile across PI3K, NF-κB, and mTOR. ADMET analysis suggested that all compounds satisfied major drug-likeness criteria and exhibited predicted oral bioavailability, although potential cytochrome P450 interactions and hepatotoxicity were predicted for some compounds. Molecular dynamics simulation indicated that the selected mTOR-p-cymene complex maintained a stable binding pose throughout the simulation, while MM/GBSA analysis yielded a modest binding free-energy estimate (ΔG_bind = −4.70 ± 8.20 kcal/mol), which should be interpreted cautiously because of the observed energetic variability. The crude methanolic cinnamon bark extract exhibited antioxidant activity and reduced the viability of HCT-116 and HT-29 colorectal cancer cells in a concentration-dependent manner. Collectively, these findings provide computational predictions of potential interactions between selected cinnamon-derived phytochemicals and cancer-associated signaling proteins and are consistent with the preliminary observation that the crude cinnamon extract exhibits antioxidant activity and cytotoxic effects in colorectal cancer cell lines. However, the computational analyses do not establish direct inhibition of the PI3K/NF-κB/mTOR signaling pathway, and the biological assays were performed using a crude extract rather than isolated phytochemicals. Therefore, further studies using purified compounds, biochemical target validation, pathway-specific cellular analyses, and in vivo models are required to determine whether the predicted protein-ligand interactions contribute to the observed biological activity.

Molecular and metabolic dysregulation of lung cancer in developing anti-tumor activity by gambogic acid mediated mTOR signaling: in vitro and computational study