Computational blueprint and stereochemical validation of a small peptide derived from Lacticaseibacillus casei VITCM05 targeting estrogen receptor alpha and human epidermal growth factor receptor 2

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

BACKGROUND Ribonucleotide Reductase (RR) is a pivotal enzyme in DNA synthesis and repair, making it a vital target in cancer therapy. While synthetic RR inhibitors such as gemcitabine and hydroxyurea are used clinically, their long-term efficacy is hampered by drug resistance and systemic toxicity. This has prompted growing interest in natural compounds with potential anticancer properties and reduced toxicity. This study aims to evaluate the molecular interactions and pharmacokinetic profiles of two naturally derived compounds traditionally used, genistein (Chinese name: , derived from Glycine max) and hematoxylin (Chinese name: , extracted from Caesalpinia sappan), against human RR using molecular docking and in silico pharmacological analyses. METHODS The three-dimensional structure of human RR (PDB ID: 6L7L) was retrieved and subjected to docking simulations using AutoDock Vina and Chimera. Genistein and hematoxylin were docked into the RR active site, and their interactions were analyzed in comparison to gemcitabine. Molecular dynamics simulations over 100 ns further confirmed the structural stability and binding persistence of both compounds within the RR active site. Pharmacokinetic and drug-likeness properties were evaluated via SwissADME and Molinspiration platforms. RESULTS Both genistein and hematoxylin exhibited strong binding affinities (-8.2 kcal/mol, -8.8 kcal/mol), respectively, to the RR active site, interacting with key catalytic residues in a manner comparable to the standard drug gemcitabine (-7.3 kcal/mol). Molecular dynamics simulations over 100 ns further confirmed the structural stability and binding persistence of both compounds within the RR active site. In silico pharmacokinetic predictions indicated good oral bioavailability, compliance with drug-likeness criteria, and low predicted toxicity. DISCUSSION Genistein emerges as a good candidate owing to its strong RRM1 binding, favorable physicochemical attributes, clean medicinal chemistry profile, and low predicted toxicity. Hematoxylin offers superior binding affinity but requires refinement to address solubility and PAINS-related concerns. Gemcitabine, while efficacious clinically, suffers from limited oral bioavailability and potential toxicities. CONCLUSION Genistein and hematoxylin demonstrate promising molecular interactions and pharmacological profiles as potential natural RR inhibitors. Their dual role in traditional healing and modern molecular pharmacology supports further preclinical development as anticancer agents.

Molegro Virtual Docker-Based Prediction of Rhodomyrtus tomentosa Metabolites Targeting Ribonucleotide Reductase as Potential Anticancer Agents

The increasing number of cancer cases has prompted the search for new drug candidates from natural ingredients, particularly plant-derived compounds considered safer and more effective. Rhodomyrtus tomentosa (Aiton) Hassk. contains various metabolites responsible for various biological activities. This study aimed to predict the anticancer potential of R. tomentosa metabolites against the Ribonucleotide Reductase (RNR) enzyme using an in silico approach. The RNR protein structure (PDB ID: 2WGH) was obtained from the RCSB Protein Data Bank. Molecular docking was performed on 25 compounds previously reported in the literature as metabolites of R. tomentosa using Molegro Virtual Docker (MVD) version 7.0 to evaluate ligand-receptor binding affinity based on MolDock Score values using a validated docking protocol (RMSD≤2.0 Å), followed by interaction analysis and pharmacokinetic evaluation using ADMET parameters. The results indicated that most compounds exhibited favorable binding affinities toward RNR, as reflected by negative MolDock Score values. Rhodomyrtosone B (−137.144 kcal/ mol) showed the best binding affinity, followed by Malvidin-3-glucoside (−135.173 kcal/ mol), Delphinidin-3-galactoside (-132.359 kcal/mol), Rhodomyrtosone I (−130.004 kcal/ mol), and Cyanidin-3-galactoside (-127.741 kcal/mol). Interaction analysis revealed stable interactions with key amino acid residues (Arg256, Asp226, and Ser269) through hydrogen bonding, hydrophobic, and electrostatic interactions. ADMET analysis indicated variability in pharmacokinetic properties, including absorption, distribution, metabolism, and toxicity. In conclusion, Rhodomyrtosone B has potential as a natural product-based anticancer agent targeting RNR, providing a basis for further in vitro and in vivo studies.Keywords: anticancer, Rhodomyrtus tomentosa, molecular docking, Ribonucleotide Reductase; in silico.

Computational modeling of selected phytochemicals from Reevesia formosana: mechanistic insights into their potential against lung cancer

Background: Lung cancer remains a dominant cause of cancer mortality, and impaired apoptosis mediated by anti-apoptotic Bcl-2 family proteins contributes to persistence and treatment resistance. Phytochemicals from Reevesia formosana display reported anti-NSCLC (Non-Small Cell Lung Cancer) activity, yet target-level mechanisms remain incompletely defined. Objectives: To prioritize Reevesia formosana phytochemicals as putative Bcl-2 (PDB ID: 6GL8) inhibitors and to derive mechanistic insight through multiscale computation. Materials and methods: Six phytochemicals and the reference Tivantinib were docked to 6GL8, and the top candidate (CPD1) was evaluated by 100 ns molecular dynamics simulations alongside Tivantinib. MMGBSA binding free energies were computed from 125 snapshots spanning 20-100 ns. ADMET properties were predicted using pkCSM. Frontier-orbital and global reactivity descriptors were obtained by DFT. Results: Docking ranked CPD1 highest (-10.15 kcal/mol) relative to Tivantinib (-8.83 kcal/mol), with hydrogen bonding to Tyr108 and Arg129 and extensive pocket complementarity. MD trajectories indicated a more confined CPD1-6GL8 complex (RMSD mainly 0.18–0.22 nm) than Tivantinib-6GL8 (0.21–0.26 nm, occasional 0.27-0.28 nm), with comparable compactness (Rg of 1.44 nm) and bounded SASA. Hydrogen-bond counts supported intermittent polar anchoring for CPD1 (0-3) and higher early sampling for Tivantinib. MMGBSA favored CPD1 (ΔTOTAL -32.87 ± 4.28 kcal/mol) over Tivantinib (-17.27 ± 2.81 kcal/mol), supported by stronger ΔVDWAALS (-40.76 vs -31.34 kcal/mol) and a smaller ΔG_SOLV (20.28 vs 24.14 kcal/mol). ADMET prediction indicated high intestinal absorption with limited solubility, restricted BBB/CNS permeability, fewer CYP inhibition flags, and no hepatotoxicity alert for CPD1, while hERG II inhibition was flagged for both ligands. DFT showed similar EHOMO (eV) but a narrower ΔE (eV) and higher ω (eV) for CPD1 than for Tivantinib. Conclusions: Integrated modeling prioritizes CPD1 as a Bcl-2-targeting scaffold for lung cancer-relevant studies, supporting structure-guided optimization and experimental verification.

Computational identification of natural phytochemicals as potential inhibitors of UBE2J1 causing ovarian cancer

Synthesis, characterization, and in silico studies of new benzohydrazide derivatives targeting EGFR kinase

Targeted therapy has improved the management of non-small cell lung cancer (NSCLC); however, resistance and suboptimal responses persist, requiring the development of new epidermal growth factor receptor (EGFR)-directed chemotypes. A series of benzohydrazide derivatives (3a–f) was synthesized and characterized using FT-IR, 1 H NMR, and 13 C NMR. In silico ADME profiling predicted high oral absorption for the series and acceptable MW/HBD/HBA ranges; however, the elevated predicted lipophilicity (QPlogPo/w > 5) suggested potential solubility and nonspecific binding risks. Compound 3e had the most balanced size and polarity profile, and compound 3f had the highest predicted permeability. Binding was evaluated against two EGFR kinase conformations (PDB: 1M17, active-like; 4HJO, inactive-like) using /native-ligand redocking, docking/induced-fit docking, Prime MM-GBSA, and 200 ns molecular dynamics simulations, together with three EGFR reference inhibitors and five DUD-E decoys. The docking/MM-GBSA results suggested conformation-dependent binding, with 3d favored in 1M17 and 3f in 4HJO, with recurrent ATP-site contacts. Overall, these compounds represent computationally prioritized EGFR-directed scaffolds for experimental validation rather than confirmed EGFR inhibitors.

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

Breast cancer (BC) is considered a highly prevalent cancer among women, with estrogen receptor alpha (ERα) playing a pivotal role in tumor growth and development. Even with existing medications such as tamoxifen, the rising resistance underscores the vital demand for novel ER-positive inhibitors. The present work focuses on identifying a thiazine derivative targeting ERα via pharmacophore model-based drug design. A ligand database of 62 bioactive thiazine derivatives in the MCF-7 cell line was generated and validated using the pharmacophore model (AHRRR_1). An additional 95,296 thiazine derivatives were downloaded and screened against the developed pharmacophore model. 10 HITs were identified via high-throughput virtual screening, standard precision, and extra precision molecular docking with the ERα protein (Protein Data Bank ID: 4XI3). Hence, HIT1 was selected as a potential lead candidate following analysis of the pharmacokinetic profile and binding free energies, as it meets the criteria and has a higher docking score than the reference drug tamoxifen. Beyond this, the stability and structural compactness of the HIT1 were confirmed by a 200 ns molecular dynamics simulation. Subsequently, a Density Functional Theory assessment highlighted the drug-likeness and reactivity of the HIT relative to tamoxifen. Collectively, this research developed a promising lead molecule (HIT1) as a therapeutic approach for ER-positive breast cancer.