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

Structure-Based In Silico Screening of PubChem Compounds for Potential Anti-Inflammatory and Anticancer Targets

Multi-target treatment methods are essential because inflammation and cancer involve intricate, interrelated pathways. To screen thirty different small compounds from PubChem for potential multi-target activity, this study employed a structure-based drug design approach. Their binding affinities for key inflammatory, analgesic and carcinogenic protein targets were evaluated using molecular docking, yielding promising candidates for further experimental validation. A total of eight pharmacologically significant receptors were selected: COX-1 (3KK6), COX-2 (3LN1), MOR (4DKL), EGFR (4HJO), ERα (3ERT), AR (1E3G), HER2 (3PP0) and CDK8 (5F19) targets. Protein structures were prepared using Discovery Studio and molecular docking was performed with AutoDock Vina in PyRx. Standard drugs such as aspirin, tramadol, erlotinib, tamoxifen, bicalutamide, lapatinib and raltitrexed were used for comparative evaluation of docking scores and interaction patterns. Post-docking analysis primarily focused on key amino acid interactions, hydrophobic contacts and hydrogen bonding. Among all tested compounds, C25, was identified as the most potent and effective compound. It exhibited strong binding affinities toward 3LN1 (-10.0 kcal/mol), 3PP0 (-9.6 kcal/mol), 5F19 (-11.9 kcal/mol), 3ERT (-8.6 kcal/mol), 1E3G (-8.8 kcal/mol), 4HJO (-8.9 kcal/mol), surpassing their respective standards. Moreover, Verimol K with 3KK6 (-7.8 kcal/mol) and 8-Deoxylactucin with 4DKL (-7.5kcal/mol) showed notable activity. Overall, the pyrazolin derivative represents a novel multi-target ligand with potential applications as an anti-inflammatory, analgesic, and anti-neoplastic agent. Its strong binding affinity across multiple therapeutic targets highlights its promise as a lead scaffold for future drug development.  Bangladesh Pharmaceutical Journal 29(2): 172-192, 2026 (July)

Computational identification of potential VEGFR2 inhibitors using integrated pharmacophore modeling, QSAR analysis, molecular docking, dynamics simulation, and virtual screening followed by in vitro bioassays

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

Identification of novel EGFR inhibitors for glioblastoma through pharmacophore-guided virtual screening and molecular dynamics

Glioblastoma (GB) is an aggressive and lethal brain tumor characterized by high mortality and poor prognosis. Amplification and mutation of the epidermal growth factor receptor (EGFR) gene are key drivers of GB progression, highlighting EGFR as a promising therapeutic target. This study aimed to identify novel small-molecule EGFR inhibitors through a pharmacophore-guided computational screening approach. A pharmacophore model was generated using the co-crystal ligand (PDB: HYZ) as a template. This model was employed to screen the Specs database comprising approximately 280,000 compounds. Ligand-based virtual screening yielded 323 hits that matched the pharmacophore query. These compounds were subjected to molecular docking against the EGFR active site using the Glide standard precision protocol, applying a binding affinity threshold of -9 kcal/mol. Eleven compounds with favorable docking scores were further evaluated through ADMET (adsorption, distribution, metabolism, excretion, toxicity) profiling, and eight top candidates were subjected to molecular dynamics simulations to assess binding stability. The pharmacophore-based screening and docking analysis identified eleven promising EGFR-binding compounds, of which eight demonstrated optimal ADMET characteristics and stable interactions within the active site during molecular dynamics simulations. The selected molecules exhibited strong binding affinities and favorable conformational stability, suggesting their potential efficacy as EGFR inhibitors. This study identified and characterized novel small molecules with high potential for EGFR inhibition in glioblastoma. These findings provide a foundation for further experimental validation and may contribute to the development of targeted therapies for GB.

MOLECULAR DOCKING STUDY OF INDONESIAN PLANT-DERIVED BIOACTIVE COMPOUND TARGETING ESTROGEN RECEPTOR ALPHA (1L2J) IN CERVICAL CANCER

Cervical cancer remains a leading cause of cancer-related mortality among women worldwide, with estrogen receptor alpha (ER-?) playing a key role in carcinogenesis. Although tamoxifen is an established ER-? antagonist, its clinical use is limited by drug resistance and tissue-specific adverse effects. Indonesian medicinal plants contain diverse phytochemicals with potential as alternative ER-? inhibitors. This study evaluated the binding affinities and molecular interaction profiles of six Indonesian plant-derived bioactive compounds against the ER-? ligand-binding domain (PDB ID: 1L2J) using molecular docking in MOE 2015.10, with tamoxifen as the reference ligand. Docking validation by re-docking the native ligand produced an RMSD of 1.5487 Å, confirming the reliability of the protocol. Among the tested compounds, carissanol exhibited the strongest binding affinity (S-score: ?14.7293 kcal/mol), surpassing tamoxifen (?12.7112 kcal/mol), and formed a key hydrogen bond with Gln305, along with extensive hydrophobic interactions. Quercetin also demonstrated strong binding (?13.5099 kcal/mol), whereas piperidine showed the weakest affinity (?5.5143 kcal/mol). These findings suggest that carissanol from Carissa spinarum L. is a promising natural lead compound targeting ER-? and merits further in vitro and in vivo investigations. Keywords: Cervical cancer, Estrogen Receptor Alpha, Molecular Docking, Carissanol, 1L2J

In-silico Molecular Docking and ADME/Pharmacokinetic Prediction Studies of Some Novel Benzothiazole Derivatives as Anticancer Agents for the Treatment of Breast Cancer

Molecular docking simulation of 3 molecules of N-(1H-benzo[d]imidazol-2-yl)-7-chloro-6-fluorobenzo[d]thiazol2-amine with the target receptor aromatase was carried out so as to evaluate their theoretical binding affinities. The chemical structure of the molecules was accurately drawn using ChemDraw Ultra software, then optimized at density functional theory (DFT) using Becke’s three-parameter Lee–Yang–Parr hybrid functional (B3LYP/6-311**) basis set in a vacuum of Spartan 14 software. Subsequently, the docking operation was carried out using PyRx virtual screening software. Three compounds were developed by fusion of a benzothiazole and benzimidazole ring system targeting the treatment of breast cancer. The marketed drug Exemestane which is also an aromatase inhibitor was used as a reference molecule for docking. The highest docking score from all three molecules was -8.6 kcal/mol which is very near to the standard drug score -9.5 kcal/mol which suggests that the compound exhibited favorable protein–ligand interactions, indicating its potential as a lead candidate for further investigation. In-silico ADME and drug-likeness prediction of the molecules showed good pharmacokinetic properties having high gastrointestinal absorption, orally bioavailable, and less toxic. The outcome of the present research strengthens the relevance of these compounds as promising lead candidates for the treatment of breast cancer which could help the medicinal chemists and pharmaceutical professionals in further designing and synthesis of more potent drug candidates. Moreover, the research also encouraged the in vivo and in vitro evaluation study for the proposed designed compounds to validate the computational findings.