Structure-Based Design and Evaluation of Coumarin-Derived CDK4 Inhibitors for Non-Small Cell Lung Cancer: An Integrated Computational Study.

An Integrated Computational Workflow for Discovering Alkaloid-Derived Ligands of Cyclin-Dependent Kinase 2

Background/Objectives: Cyclin-dependent kinase 2 (CDK2) is a key regulator of cell-cycle progression and a potential anticancer target. This study aimed to identify alkaloid-derived CDK2 ligands using an integrated computational workflow and to obtain preliminary evidence of their effects on cancer-cell viability. Methods: Molecular docking with mVina and fast pulling of ligand (FPL) simulations were benchmarked using 20 experimentally characterized CDK2 inhibitors. A library of 2692 PubChem-derived alkaloids was screened, followed by ADMET evaluation, 100 ns molecular dynamics simulations, and FPL-based relative-affinity re-ranking. The three prioritized compounds were evaluated in HepG2 and HGC-27 cells using an MTT assay after 48 h of exposure. Results: Docking and FPL showed correlations with experimental affinity data of RDock = 0.549 ± 0.180 and RW = −0.676 ± 0.119, respectively. CID 636885, CID 46184320, and CID 101691758 were prioritized for detailed evaluation. All three compounds reduced cell viability, with lower IC50 values observed in HepG2 cells than in HGC-27 cells. CID 101691758 exhibited the highest growth-inhibitory activity among the tested compounds, with IC50 values of 15.37 ± 0.46 µg mL−1 in HepG2 cells and 52.64 ± 1.33 µg mL−1 in HGC-27 cells. Conclusions: The workflow identified three preliminary alkaloid hits, with CID 101691758 showing the most favorable combined computational and cell-viability profile. However, the MTT assay does not establish direct CDK2 inhibition or kinase selectivity. Biochemical CDK2 inhibition, target-engagement, and kinase-panel studies are therefore required.

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

Comparative Structure-Based Molecular Docking Analysis of Clinically Approved CDK4/6 Inhibitors Targeting CDK6

Cyclin-dependent kinases 4 and 6 (CDK4/6) are critical regulators of the G1–S phase transition of the cell cycle and represent major therapeutic targets in hormone receptor-positive breast cancer. Although several CDK4/6 inhibitors have been approved for clinical use, their comparative binding characteristics at the molecular level remain insufficiently understood. In this study, a structure-based molecular docking approach was employed to evaluate the binding affinities and interaction profiles of clinically approved and clinical-stage CDK4/6 inhibitors toward CDK6. The crystal structure of CDK6 in complex with palbociclib (PDB ID: 5L2I) was retrieved from the Protein Data Bank, and the docking protocol was validated by redocking the co-crystallized ligand. Molecular docking analyses of ribociclib, abemaciclib, trilaciclib, alvocidib, and dalpiciclib were carried out using AutoDock. The redocking procedure successfully reproduced the experimental binding mode with an RMSD value of 1.0 Å, confirming the reliability of the docking protocol. Among the investigated ligands, dalpiciclib exhibited the lowest binding energy (−11.68 kcal/mol), followed by trilaciclib (−11.09 kcal/mol), both showing stronger predicted binding affinity than the reference ligand palbociclib (−10.91 kcal/mol). Abemaciclib demonstrated comparable binding affinity, whereas ribociclib and alvocidib displayed relatively weaker binding energies. These findings indicate that dalpiciclib and trilaciclib may form more stable complexes with CDK6 compared to other clinically used inhibitors. This comparative in silico analysis provides structural insights into the binding behavior of clinical CDK4/6 inhibitors and may contribute to future optimization and development of CDK-targeted therapies.

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)

A multistage computational pipeline integrating ligand-based and structure-based screening with ADMET evaluation, molecular dynamic simulation and free energy calculations for the discovery of potential TNIK inhibitors.

Dysregulation of metabolic signalling pathways, such as Wnt/β-catenin, is a hallmark of various cancers including colorectal cancer, lung squamous cell carcinoma, papillary thyroid carcinoma, multiple myeloma etc. TRAF2 and NCK-interacting kinase (TNIK), a serine/threonine kinase, plays a critical role in this pathway by phosphorylating TCF4, thereby promoting transcription of oncogenic genes linked to cell proliferation, stemness, and therapeutic resistance. Owing to its central role across multiple tumor types, TNIK is a promising target for small-molecule drug development. This study utilized an integrated computer-aided drug design (CADD) strategy to identify novel TNIK inhibitors. Ligand-based virtual screening (LBVS) was initiated using a pharmacophore model based on known inhibitors to screen over 1 billion PubChem compounds. Filtering via cheminformatics protocols (PAINS, Lipinski's rules, and molecular descriptors) in KNIME narrowed the library to 25,082 candidates. These were subjected to structure-based virtual screening (SBVS) using molecular docking against TNIK (PDB ID: 6RA7). The top 100 hits were assessed for ADMET properties using DruMAP v2.0, identifying three lead compounds: PubChem-11590224, -9168610, and -121049323. These were further validated through 200-ns molecular dynamics (MD) simulations in triplicate using GROMACS, confirming stable binding interactions. MM/PBSA free energy calculations revealed favorable binding energies, comparable to clinical-phase TNIK inhibitor INS018_055. This LBVS-SBVS-ADMET-MD pipeline effectively identified three promising TNIK inhibitors, providing a solid foundation for future experimental validation and potential development of targeted therapies for Wnt-driven malignancies.

Exploration of Natural Anti-Hepatocellular Carcinoma Compounds Targeting XIAP-BIR3 Using Molecular Docking, Conventional, and PaCS Molecular Dynamics

Hepatocellular carcinoma (HCC) exhibits apoptosis resistance driven in part by overexpression of X-associated inhibitor of apoptosis protein (XIAP), whose baculovirus IAP repeat domain 3 (BIR3) suppresses caspase activation. This study employed a stepwise in silico workflow to identify plant-based natural compounds targeting XIAP-BIR3. A curated library of 534 compounds from 12 medicinal plants was screened using ensemble docking (AutoDock Vina), then filtered for drug-likeness, and their poses were generated with AutoDock4. Selected candidates were evaluated through conventional molecular dynamics (MD) simulations (50 and 500 ns) and Parallel Cascade Selection MD (PaCS-MD). As a result, mangostanol and 9-hydroxycalabaxanthone showed the best affinity and stability, comparable to the co-crystal ligand 7HU as a control, while neoandrographolide showed decreased stability in the 500 ns MD simulation. PaCS-MD confirmed that 9-hydroxycalabaxanthone has a stronger initial interaction energy than neoandrographolide, but eventually fully dissociates, consistent with a dynamic and reversible interaction. Overall, mangostanol and 9-hydroxycalabaxanthone will be prioritized for in vitro/in vivo testing, underscoring the importance of a stepwise, structure-based approach.