ArticleScientific reports2024
QSAR, ADMET, molecular docking, and dynamics studies of 1,2,4-triazine-3(2H)-one derivatives as tubulin inhibitors for breast cancer therapy.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation.Molecular biomedicine · 2026Review
- In Silico Development of Novel Quinazoline-Based EGFR Inhibitors via 3D-QSAR, Docking, ADMET, and Molecular Dynamics.International journal of molecular sciences · 2026Article
- Structure-Guided Design of Novel Diarylpyrimidine-Based NNRTIs Through a Comprehensive In Silico Approach: 3D-QSAR, ADMET Evaluation, Molecular Docking, and Molecular Dynamics.Pharmaceuticals (Basel, Switzerland) · 2025Article
- FromACS omega · 2025Article
- Synthesis, antiproliferative activity targeting lung cancer and in silico studies of hydroxypiperidine substituted thiosemicarbazones.Scientific reports · 2025Article
- Multitarget Design of Steroidal Inhibitors Against Hormone-Dependent Breast Cancer: An Integrated In Silico Approach.International journal of molecular sciences · 2025Article
- An in-depth study of indolone derivatives as potential lung cancer treatment.Scientific reports · 2025Article
- Design, synthesis and antiproliferative activity of novel colchicine derivatives: selective inhibition of melanoma cell proliferation.Frontiers in pharmacology · 2025Article
- Article
- Paraherquamides - A new hope and great expectations of anthelmintic agents: Computational studies.PloS one · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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Abstract
Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development of more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors of Tubulin, a pivotal protein in cancer cell division, highlighting a targeted approach in cancer therapy. Using an integrated computational approach, we combined quantitative structure-activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and molecular dynamics simulations to evaluate and predict the efficacy and stability of these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such as absolute electronegativity and water solubility significantly influence inhibitory activity, achieving a predictive accuracy (R
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