ArticleScientific reports2022
QSAR analysis on a large and diverse set of potent phosphoinositide 3-kinase gamma (PI3Kγ) inhibitors using MLR and ANN methods.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- AI-driven generative framework integrating ML-QSAR and fragment learning for isoform-selective PI3K inhibitor design.Molecular diversity · 2026Article
- QSAR-Guided and Fragment-Based Drug Design of Monoterpenoid Inhibitors Targeting Ebola Virus Glycoprotein.International journal of molecular sciences · 2026Article
- Machine Learning and Molecular Modeling for Drug Repurposing Targeting Potential PI3Kα Inhibitors in Post-CoViD-19 Pulmonary Fibrosis.ACS omega · 2026Article
- Selective phosphoinositide 3-kinase inhibitors and implication in diabetic retinopathy as pharmacological tools.Frontiers in pharmacology · 2026Review
- Tracking protein kinase targeting advances: integrating QSAR into machine learning for kinase-targeted drug discovery.Future science OA · 2025Review
- Identification of potential PI3Kγ inhibitors among FDA approved drugs using integrated computational and quantum chemical approaches.Scientific reports · 2025Article
- Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of α-glucosidase inhibitors.Computational and structural biotechnology journal · 2024Review
- Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phosphorylation of PI3Kγ as a member of lipid kinases-enzymes, plays a crucial role in regulating immune cells through the generation of intracellular signals. Deregulation of this pathway is involved in several tumors. In this research, diverse sets of potent and selective isoform-specific PI3Kγ inhibitors whose drug-likeness was confirmed based on Lipinski's rule of five were used in the modeling process. Genetic algorithm (GA)-based multivariate analysis was employed on the half-maximal inhibitory concentration (IC
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Registered trials
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