ArticleJournal of computer-aided molecular design2025
Computational study on QSAR modeling, molecular docking, and ADMET profiling of pyrazole-modified catalpol derivatives as prospective dual inhibitors of VEGFR-2/BRAF V600E.
Article in Journal of computer-aided molecular design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Component Analysis and Mechanism Exploration of Fangji Dihuang Decoction in Treating Ischemic Stroke With Homotherapy for Heteropathy Based on Molecular Networking and Network Pharmacology.Biomedical chromatography : BMC · 2026Article
- In-silico study of active phytochemicals and molecular mechanism of Hydrocotyle javanica Thunb.in treating MDR enterobacterial infection.Bioresources and bioprocessing · 2026Article
- Integrated AI-Driven Discovery of MAPK3 Inhibitors for Oral Inflammatory and Proliferative Diseases.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Biodesulfurization and activation of a thionated levofloxacin derivative: antimicrobial evaluation and LC-MS-based metabolic profiling.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
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Authors and funding
5 authors.
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Abstract
Pancreatic and Esophageal cancers are highly aggressive with high mortality and limited treatment, causing over 466,000 and 544,100 deaths worldwide in 2020 respectively. This highlights the urgent need for safer,and effective anticancer agents. Catalpol, a natural iridoid glycoside, shows anticancer potential, but due to its poor drug-like properties it requires structural modification. This study investigates pyrazole-modified catalpol derivatives as dual inhibitors for these cancers using Quantitative Structure Activity Relationship (QSAR) modelling, molecular docking, and pharmacokinetic studies. We analyzed fourteen pyrazole-modified catalpol derivatives with reported IC50values against four cancer cell lines(BxPC-3, PANC-1, Eca109, and EC9706). The molecules were optimized using DensityFunctional Theory (DFT), and 2D molecular descriptors were calculated using PaDEL. QSAR models were developed by utilizing a Genetic Function Algorithm (GFA) and Multiple Linear Regression (MLR) and validated using statistical metrics such as R
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