Chemosensitization and Molecular Docking Assessment of Dio-NPs on Resistant Breast Cancer Cells to Tamoxifen

Pharmaceuticals, Journal Year: 2025, Volume and Issue: 18(4), P. 452 - 452

Published: March 23, 2025

Background: Diosgenin, a powerful compound found in fenugreek and Dioscorea villosa, has diverse pharmacological effects. This study examines the anticancer potential of diosgenin nanoparticles (Dio-NPs) against DMBA-induced breast cancer mice combination with tamoxifen. Methods: In current investigation, characterization Dio-NPs was performed, including their size, shape, zeta potential, UV-vis, FT-IR spectra. (120 mg/kg) tamoxifen (2 were given to cancer, either alone or combination, over 4 weeks. We measured inflammatory oxidative stress markers, as well gene expressions related apoptosis, using ELISA qRT-PCR. Additionally, molecular docking studies conducted assess binding affinity specific proteins. Molecular dynamics simulations on CDK4, AKT, CDK6 proteins GROMACS. The systems solved, neutralized, equilibrated under NVT NPT ensembles. Simulations ran for 100 ns, trajectories analyzed RMSD, RMSF, RG, SASA, hydrogen bonds. Results: IC50 MCF-7 cells 47.96 ± 1.48 µg/mL. had −21.8 0.6 mV size 56.85 3.19 nm uniform spherical. LD50 2400 mg/kg. DMBA exposure increased WBCs, stress, expression CDK2, CDK6, Akt, while reducing Hb%, RBCs, PLTs, GSH, superoxide dismutase, catalase levels. tamoxifen, both combined, significantly reduced these treatment more effective than individual treatments. Histological analyses supported findings. showed stronger target compared revealed that effectively binds maintaining stability structural integrity. consistent SASA values, moderate flexibility stable bonding patterns, suggesting therapeutic targets. Conclusions: Combining inhibits progression DMBA-treated mice. is primarily due reduction Akt proteins, which enhances sensitivity resistant

Language: Английский

NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction

Chemical Biology & Drug Design, Journal Year: 2025, Volume and Issue: 105(4)

Published: April 1, 2025

Sirtuins, a class of NAD+ -dependent deacetylases, play key role in aging, metabolism, and longevity. Their interaction with at the catalytic site is crucial for function, but experimental methods to map binding sites are time consuming. To address this, we developed computational method integrating pretrained protein language models multiwindow convolutional neural networks (CNNs). This captures sequence information diverse local patterns, achieving state-of-the-art performance, AUC 0.9733 human sirtuin proteins 0.9701 other NAD-dependent deacylation enzymes. These findings offer insights into sirtuins aging their broader biological functions while providing new path identifying therapeutic targets aging-related diseases.

Language: Английский