ArticleRSC advances2018
Discovery of VEGFR2 inhibitors by integrating naïve Bayesian classification, molecular docking and drug screening approaches.
Article in RSC advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 48 citations in OpenAlex.
- Explainable Artificial Intelligence (XAI) and Molecular Modeling Techniques to Discover Putative HER2 Inhibitors.International journal of molecular sciences · 2026Article
- Enhancing PI3Kγ inhibitor discovery: a machine learning-based virtual screening approach integrating pharmacophores, docking, and molecular descriptors.Molecular diversity · 2025Article
- Identification of novel covalent JAK3 inhibitors through consensus scoring virtual screening: integration of common feature pharmacophore and covalent docking.Molecular diversity · 2025Article
- Virtual Screening and Bioassay of Novel Protoporphyrinogen Oxidase andMolecules (Basel, Switzerland) · 2025Article
- Comprehensive applications of the artificial intelligence technology in new drug research and development.Health information science and systems · 2024Review
- Article
- From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.ChemMedChem · 2024Article
- An efficient and simple approach for synthesizing indazole compounds using palladium-catalyzed Suzuki-Miyaura cross-coupling.RSC advances · 2024Article
- Exploring Darunavir, Rilpivirine and Etravirine as Potential Therapies for Bladder Cancer: Efficacy and Synergistic Effects.Biomedicines · 2024Article
- Application of Support Vector Machine Classification Model to Identification of Vascular Endothelial Growth Factor Receptor Inhibitors.Advanced biomedical research · 2024Article
- Optimized models and deep learning methods for drug response prediction in cancer treatments: a review.PeerJ. Computer science · 2024Article
- Drug Repurposing to Circumvent Immune Checkpoint Inhibitor Resistance in Cancer Immunotherapy.Pharmaceutics · 2023Review
- Evolution of Antiretroviral Drug Rilpivirine and Approach to Oncology.International journal of molecular sciences · 2023Review
- New benzoxazole derivatives as potential VEGFR-2 inhibitors and apoptosis inducers: design, synthesis, anti-proliferative evaluation, flowcytometric analysis, andJournal of enzyme inhibition and medicinal chemistry · 2022Article
- Discovery of new nicotinamides as apoptotic VEGFR-2 inhibitors: virtual screening, synthesis, anti-proliferative, immunomodulatory, ADMET, toxicity, and molecular dynamic simulation studies.Journal of enzyme inhibition and medicinal chemistry · 2022Article
- Benzoxazole derivatives as new VEGFR-2 inhibitors and apoptosis inducers: design, synthesis,Journal of enzyme inhibition and medicinal chemistry · 2022Article
- The use of machine learning modeling, virtual screening, molecular docking, and molecular dynamics simulations to identify potential VEGFR2 kinase inhibitors.Scientific reports · 2022Article
- In Silico Identification of Promising New Pyrazole Derivative-Based Small Molecules for Modulating CRMP2, C-RAF, CYP17, VEGFR, C-KIT, and HDAC-Application towards Cancer Therapeutics.Current issues in molecular biology · 2022Article
- Big data and artificial intelligence (AI) methodologies for computer-aided drug design (CADD).Biochemical Society transactions · 2022Article
- Synthesis and Rational Design of New Appended 1,2,3-Triazole-uracil Ensembles as Promising Anti-Tumor Agents via In Silico VEGFR-2 Transferase Inhibition.Molecules (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The high morbidity and mortality of cancer make it one of the leading causes of global death, thus it is an urgent need to develop effective drugs for cancer therapy. Vascular endothelial growth factor receptor-2 (VEGFR2) acts as a central modulator of angiogenesis, and is therefore an important pharmaceutical target for developing anti-angiogenic agents. In this study, ligand-based naïve Bayesian (NB) models and structure-based molecular docking were combined to develop a virtual screening (VS) pipeline for identifying potential VEGFR2 inhibitors from FDA-approved drugs. The best validated naïve Bayesian model (NB-c) gave Matthews correlation coefficients of 0.966 and 0.951 for the test set and external validation set, respectively. 1841 FDA-approved drugs were sequentially screened by the optimal model NB-c and molecular docking module LibDock. By analyzing the results of VS, 9 top ranked drugs with EstPGood value ≥ 0.6 and LibDock Score ≥ 120 were chosen for biological validation. VEGFR2 kinase assay results demonstrated that flubendazole, rilpivirine and papaverine showed VEGFR2 inhibitory activities with IC
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.