This chapter introduces the basis of computational chemistry and discusses how computational methods have been extended from physical to biological properties, and toxicology in particular, modeling. Since about three decades, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Animal and wet experiments, aimed at providing a standardized result about a biological property, can be mimicked by modeling methods, globally called in silico methods, all characterized by deducing properties starting from the chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (quantitative structure-activity relationships), and models that check relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. Virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.
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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 PDFPharmaceuticals (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 PDFMutat 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 PDFJ Xenobiot
December 2024
Department of Environmental, Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy.
In this study, models for NOEL (No Observed Effect Level) and NOEC (No Observed Effect Concentration) related to long-term/reproduction toxicity of various organic pesticides are built up, evaluated, and compared with similar models proposed in the literature. The data have been obtained from the EFSA OpenFoodTox database, collecting only data for the Bobwhite quail (. Models have been developed using the CORAL-2023 program, which can be used to develop quantitative structure-property/activity relationships (QSPRs/QSARs) and the Monte Carlo method for the optimization of the model.
View Article and Find Full Text PDFSAR QSAR Environ Res
January 2025
Department of Biotechnology, National Institute of Technology, Durgapur, India.
Protein arginylation mediated by arginyltransferase 1 is a crucial regulator of cellular processes in eukaryotes by affecting protein stability, function, and interaction with other macromolecules. This enzyme and its targets are of immense interest for modulating cellular processes in diseased states like obesity and cancer. Despite being an important target molecule, no highly potent drug against this enzyme exists.
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