In silico discovery and interaction analysis of a Datura stramonium defensin-like peptide targeting cancer-related receptors.

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

Findings highlight Withaferin A as a promising natural inhibitor of UBE2J1 and provide a foundation for future experimental validation aimed at developing targeted therapies against ovarian cancer.

Computational identification and evaluation of Adenium obesum phytochemicals as potential EGFR inhibitors for targeted therapy against non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) remains the leading cause of lung cancer–related mortality, largely driven by aberrant activation of the epidermal growth factor receptor (EGFR). Despite the clinical success of EGFR tyrosine kinase inhibitors (TKIs), intrinsic and acquired resistance, coupled with safety concerns, highlight the need for novel, safer inhibitors. Natural products represent an underexplored source of structurally diverse bioactive compounds with favorable biocompatibility. In this study, a comprehensive in silico approach is used to evaluate phytochemicals from Adenium obesum as potential candidate EGFR-targeting compound. Initially, sixteen phytochemicals were first assessed for predicted antineoplastic activity using PASS. High-scoring molecules were docked against the EGFR kinase domain (PDB ID: 1M17), besides performed detailed protein–ligand interaction analysis, drug-likeness and ADMET profiling, toxicity prediction and 100-ns molecular dynamics (MD) simulations. PASS-based bioactivity prediction revealed strong anticancer potential among the sixteen screened compounds, with consistently high antineoplastic and antiproliferative activity probabilities (Pa > 0.79) and low inactivity scores, supporting their selection for subsequent docking, ADMET, and molecular dynamics analyses. Next, several phytochemicals exhibited strong docking affinities, with Cardenolide achieving the highest binding score (–9.9 kcal/mol) and forming stable interactions with key catalytic residues. A 100-ns MD simulation confirmed the structural stability, persistent binding, and dynamic integrity of the EGFR–Cardenolide complex under physiological conditions. Importantly, interaction mapping revealed that Cardenolide engages conserved and functionally critical regions of the EGFR kinase domain associated with catalytic activity and structural stability, supporting its mechanistic relevance as an ATP-competitive scaffold. Additionally, predicted pharmacokinetic and toxicity profiles further supported Cardenolide’s suitability as a drug-like candidate. Collectively, these results identify Cardenolide as a computationally prioritized candidate with favorable predicted EGFR-binding characteristics, structural stability, and physicochemical and toxicity profiles. However, as the present study is based entirely on computational analyses, these findings should be considered hypothesis-generating and do not establish EGFR inhibitory activity or therapeutic efficacy. Experimental validation, including biochemical kinase inhibition and cellular assays, is therefore required to determine the actual EGFR inhibitory potential and anticancer activity of Cardenolide. Nevertheless, the findings provide a rational basis for prioritizing Cardenolide for further experimental investigation and illustrate the potential of Adenium obesum phytochemicals as a source of candidate EGFR-targeting compounds for future NSCLC drug discovery.

Exploring glycopentamides from Glycosmis pentaphylla as CDK4 inhibitors: a computational study

Integrated Computational and Experimental Discovery of Antitumoral Peptides Targeting Luminal A and Triple-Negative Breast Cancer

Breast cancer remains one of the leading causes of cancer-related mortality worldwide, highlighting the need for more selective and effective therapies. This study aimed to identify and validate novel anticancer peptides targeting Luminal A (MCF-7) and triple-negative (MDA-MB-231) breast cancer subtypes using an integrated in silico and in vitro approach. Overexpressed proteins in each cell line were identified through literature mining, followed by the construction of protein–protein interaction (PPI) networks using STRING. Conserved motifs within PPI components were identified via multiple sequence alignment using the MEME Suite. Immunogenicity and anticancer potential of the selected motifs were predicted using VaxiJen and AntiCP, respectively. Peptide–target interactions were assessed through molecular docking (PatchDock/FireDock) and refined using molecular dynamics simulations in GROMACS. Based on these analyses, two lead peptides per subtype were selected, synthesized, and experimentally evaluated for cytotoxicity and subcellular localization. Two lead peptides were identified for each breast cancer subtype. Notably, the peptides RVCGDRGFFF and WYLKMMWQW exhibited strong membrane-associated interactions and significantly reduced the viability of MDA-MB-231 cells by approximately 75% and 90%, respectively. The combined computational and experimental approach enabled the identification of peptides with selective cytotoxic effects and favorable predicted immunogenic profiles. These findings demonstrate that integrating computational screening with experimental validation is an effective strategy for accelerating the discovery of selective anticancer peptides. The identified candidates represent promising leads for the development of peptide-based therapeutics targeting specific breast cancer subtypes, with potential applications in oncology.

Computational Insights into 1,4-Naphthoquinones as Allosteric MEK1 Inhibitors for Cancer Therapy.

INTRODUCTION MEK1 plays a critical role in cellular survival and proliferation. Its activity is tightly regulated, and its dysregulation may lead to various cancers. It is frequently targeted for therapeutic intervention. 1,4-Naphthoquinones, a natural compound class, have garnered increasing interest for their anticancer potential. METHODS A comprehensive library of 1,4-naphthoquinones was obtained from the PubChem database. This library was subjected to virtual screening using molecular docking against the allosteric site of MEK1 kinase. Selection was based on DOCK scores and pose similarity to the native inhibitor BBM. Ten compounds were selected and analyzed in detail for binding affinity, binding poses, and molecular interactions. Molecular dynamics (MD) simulation was performed for the top candidate. RESULTS The ten shortlisted compounds exhibited strong binding affinities for MEK1. Key residues involved in binding, including Asp-190, Asp-208, Phe-209, Met-219, and Lys-97, were consistently engaged by the shortlisted compounds and the native inhibitor. MD simulation of the top compound confirmed its stable binding. Pose overlay revealed that similar scaffolds showed comparable binding energies and interactions. ADMET predictions were considered in hit prioritization. DISCUSSION Early enrichment of true positives over decoys strongly supports the screening protocol. The common key residues shared between the naphthoquinones and the native inhibitor suggest a similar inhibitory mechanism. ADMET-based predictions led to the identification of the five most promising candidates. CONCLUSION This study proposed ten 1,4-naphthoquinones as potential allosteric inhibitors of MEK1. After integrating DOCK scores, binding energy, and ADMET risk, five compounds emerged as the most promising. These results provide a computational foundation for further testing.

Therapeutic Potential of Icariin in Breast Cancer: An Integrated Network Pharmacology and Molecular Simulations Approach

Breast cancer is a prevalent and aggressive tumor affecting women, known for its molecular diversity and treatment resistance. This study investigates the anticancer potential of Icariin (ICA), a flavonol glycoside derived from Herba epimedii, against breast cancer using network pharmacology and molecular simulation. Using the SwissTargetPrediction database and GeneCards, the researchers identified 98 common targets shared by ICA and breast cancer. Gene ontology (GO) and KEGG enrichment analyses highlighted the targets' roles in the regulation of apoptosis, inflammatory signaling, receptor tyrosine kinase activity, chemokine signaling, sphingolipid metabolism, and VEGF pathways. Molecular docking revealed ICA's strong binding affinity for key oncogenic proteins, with binding energies ranging from −12 to −7.5 kcal/mol, particularly to SER783, THR862, ASP863, LYS753, and ARG849. Molecular dynamics (MD) simulations demonstrated the structural stability of the ICA‐HER2 complex, which maintained strong hydrogen bonds and exhibited minimal conformational changes over a 1000 ns trajectory, with average RMSD values of 1.7 Å for the protein and 1.0 Å for the protein‐ligand complex. Furthermore, ICA exhibited favorable pharmacokinetic properties, including moderate solubility and negligible inhibition of cytochrome P450. These findings support the hypothesis that ICA may serve as a valuable natural compound for treating HER2‐driven breast cancer; it requires further experimental validation.