ArticleMolecules (Basel, Switzerland)2018
Theoretical Prediction of the Complex P-Glycoprotein Substrate Efflux Based on the Novel Hierarchical Support Vector Regression Scheme.
Article in Molecules (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Development and application of a quantitative physicochemical model of P-gp substrate specificity.Journal of computer-aided molecular design · 2026Article
- CANDID-CNS: AI Unlocks Stereochemistry and Beyond Rule of 5 to Predict CNS Penetration of Small Molecules.Journal of chemical information and modeling · 2025Article
- Imidazolinium-Based NHC-Metal Complexes Overcome Both Cancer Multidrug Resistance and Cisplatin Resistance In Vitro.International journal of molecular sciences · 2025Article
- Prioritisation of co-formulants and plant protection products for non-dietary risk assessment using NAMs.Archives of toxicology · 2025Article
- Bioactive compound nanoparticles for Alzheimer's disease.Inflammopharmacology · 2025Review
- P-Glycoprotein as a Therapeutic Target in Hematological Malignancies: A Challenge to Overcome.International journal of molecular sciences · 2025Review
- Cryo-EM of human P-glycoprotein reveals an intermediate occluded conformation during active drug transport.Nature communications · 2025Article
- Refined ADME Profiles for ATC Drug Classes.Pharmaceutics · 2025Article
- Article
- Synthesis andFrontiers in chemistry · 2024Article
- The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery.Pharmaceutics · 2023Review
- Biomarker Quantification, Spectroscopic, and Molecular Docking Studies of the Active Compounds Isolated from the Edible PlantPharmaceuticals (Basel, Switzerland) · 2023Article
- Recent Advances on P-Glycoprotein (ABCB1) Transporter Modelling with In Silico Methods.International journal of molecular sciences · 2022Review
- The use of machine learning modeling, virtual screening, molecular docking, and molecular dynamics simulations to identify potential VEGFR2 kinase inhibitors.Scientific reports · 2022Article
- Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches.Pharmaceutics · 2022Article
- Integrated bioinformatics-cheminformatics approach toward locating pseudo-potential antiviral marine alkaloids against SARS-CoV-2-Mpro.Proteins · 2022Article
- In Silico Prediction of Skin Permeability Using a Two-QSAR Approach.Pharmaceutics · 2022Article
- Development of a Hierarchical Support Vector Regression-Based In Silico Model for Caco-2 Permeability.Pharmaceutics · 2021Article
- Integrating biokinetics and in vitro studies to evaluate developmental neurotoxicity induced by chlorpyrifos in human iPSC-derived neural stem cells undergoing differentiation towards neuronal and glial cells.Reproductive toxicology (Elmsford, N.Y.) · 2020Article
- In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.International journal of molecular sciences · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
P-glycoprotein (P-gp), a membrane-bound transporter, can eliminate xenobiotics by transporting them out of the cells or blood⁻brain barrier (BBB) at the expense of ATP hydrolysis. Thus, P-gp mediated efflux plays a pivotal role in altering the absorption and disposition of a wide range of substrates. Nevertheless, the mechanism of P-gp substrate efflux is rather complex since it can take place through active transport and passive permeability in addition to multiple P-gp substrate binding sites. A nonlinear quantitative structure⁻activity relationship (QSAR) model was developed in this study using the novel machine learning-based hierarchical support vector regression (HSVR) scheme to explore the perplexing relationships between descriptors and efflux ratio. The predictions by HSVR were found to be in good agreement with the observed values for the molecules in the training set (
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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.