A quantitative structure-activity relationship analysis of the 2-methylquinazolin-4-one and quinazolin-4-imine derivatives, well-known antifolate thymidylate synthase (TYMS) inhibitors, has been performed in the range IC = 0.4÷380000.0 nmoL/L using the GUSAR 2013 program. Based on the MNA and QNA descriptors using the self-consistent regression, 6 statistically significant consensus models for predicting the IC numerical values have been constructed. These models demonstrate high and moderate prognostic accuracies for the training and external validation test sets, respectively. The molecular fragments of TYMS inhibitors regulating their antitumor activity are identified. The obtained data open opportunities for developing novel promising inhibitors of TYMS.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jmgm.2018.09.002 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A Simple Machine Learning-Based Quantitative Structure-Activity Relationship Model for Predicting pIC Inhibition Values of FLT3 Tyrosine Kinase.
Pharmaceuticals (Basel)
January 2025
Centro de Química Médica, Facultad de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago 7780272, Chile.
Acute myeloid leukemia (AML) presents significant therapeutic challenges, particularly in cases driven by mutations in the FLT3 tyrosine kinase. This study aimed to develop a robust and user-friendly machine learning-based quantitative structure-activity relationship (QSAR) model to predict the inhibitory potency (pIC values) of FLT3 inhibitors, addressing the limitations of previous models in dataset size, diversity, and predictive accuracy. Using a dataset which was 14 times larger than those employed in prior studies (1350 compounds with 1269 molecular descriptors), we trained a random forest regressor, chosen due to its superior predictive performance and resistance to overfitting.
View Article and Find Full Text PDFMachine Learning-Assisted Drug Repurposing Framework for Discovery of Aurora Kinase B Inhibitors.
Pharmaceuticals (Basel)
December 2024
Faculty of Pharmacy, "Carol Davila" University of Medicine and Pharmacy, Traian Vuia 6, 020956 Bucharest, Romania.
Aurora kinase B (AurB) is a pivotal regulator of mitosis, making it a compelling target for cancer therapy. Despite significant advances in protein kinase inhibitor development, there are currently no AurB inhibitors readily available for therapeutic use. This study introduces a machine learning-assisted drug repurposing framework integrating quantitative structure-activity relationship (QSAR) modeling, molecular fingerprints-based classification, molecular docking, and molecular dynamics (MD) simulations.
View Article and Find Full Text PDFQuantitative Structure-Activity Relationship (QSAR) Modeling of Chiral CCR2 Antagonists with a Multidimensional Space of Novel Chirality Descriptors.
Molecules
January 2025
Independent Researcher, 1802 Stanford Avenue, Duluth, MN 55811, USA.
The development of chirality descriptors for quantitative chirality structure-activity relationship (QCSAR) modeling has always attracted attention, owing to the importance of chiral molecules in pharmaceutical, agriculture, food, and fragrance industries, and environmental toxicology. The utility of a multidimensional space of novel relative chirality indices (RCIs) in the QCSAR modeling of twenty CCR2 antagonists is reported upon in this paper. The numerical characterization of chirality by the RCI approach gives a large pool of chirality descriptors with different degrees of mutual correlation (the correlation coefficient among the computed descriptors varied from 0.
View Article and Find Full Text PDFIn silico and in vitro assessments of the mutagenicity of the azilsartan photoproduct.
Mutat Res Genet Toxicol Environ Mutagen
January 2025
Research & Development, Kongo Chemical Co., Ltd, Himata, Toyama 9300912, Japan.
Photodegradation of azilsartan yields a phenanthridine derivative (APP). We suspected that APP could be a DNA-reactive substance, since many phenanthridine derivatives are mutagenic. In silico quantitative structure-activity relationship analysis indicated potential mutagenicity of APP, due to DNA reactivity at the 6-aminophenanthridine moiety.
View Article and Find Full Text PDFQuantitative structure-activity relationship (QSAR) hazard assessment of the banned pesticides by the National Agency for Food and Drugs Administration and Control.
Naunyn Schmiedebergs Arch Pharmacol
January 2025
Department of Biochemistry, University of Ilorin, Kwara State, Ilorin, Nigeria.
This study carried out a quantitative structure-activity relationship hazard assessment of the banned pesticides in Nigeria with a view of identifying the dangers posed by these pesticides. Structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs), which link a compound's chemical structure to its biological activity, can be used to create safer and more effective insecticides, prioritize chemicals for testing, and reduce the number of animal studies necessary throughout the regulatory process. The QSAR hazard assessment of the banned pesticides was carried out on the VEGA software.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!