In recent years, multiple computational studies have used machine learning models to predict substrate binding and inhibition of ATP-binding cassette (ABC) transporters. However, many of these studies relied on relatively small training sets with lim...
The primary aim of our study was to address the problem of transcriptomic data complexity by introducing a novel transcriptomic response index (TRI), compressing the entire transcriptomic space into a single variable, and linking it with the inhaled ...
This study aims to identify potential DYRK1A inhibitors from a curated database and utilize a QSAR model to predict the bioactivity of drug compounds in inhibiting the enzyme involved in tau protein oligomerization, a key process in AD pathology. 192...
Journal of computer-aided molecular design
Oct 4, 2025
The traditional drug discovery process is often lengthy, costly, and characterized by a high failure rate. There is a pressing need for innovative strategies to optimize this process and improve the chances of identifying effective therapeutic candid...
Arhiv za higijenu rada i toksikologiju
Sep 30, 2025
Water pollution caused by micropollutants has been a global issue for decades, prompting the scientific community and industry professionals to develop new and effective wastewater treatment methods. Understanding the interactions of these compounds ...
Journal of agricultural and food chemistry
Sep 26, 2025
Traditional chemical pesticides have raised significant environmental and health concerns, driving the pursuit of safer alternatives. Aphids, notorious for causing extensive agricultural damage and transmitting plant diseases, represent prime targets...
The increasing use of pesticides in agriculture and urban areas has led to significant contamination of aquatic ecosystems, posing risks to non-target species. Fish, particularly the rainbow trout (Oncorhynchus mykiss), are highly vulnerable due to t...
Journal of chemical information and modeling
Sep 17, 2025
The ability to predict log directly from spectral patterns marks a conceptual shift in cheminformatics. In this work, we demonstrate that H and C NMR spectra, computationally generated from molecular structures and transformed into machine learning-...
The characterization of transformation products (TPs) is crucial for understanding chemical fate and potential environmental hazards. TPs form through (a)biotic processes and can be detected in environmental concentrations comparable to or even excee...
Chemical graph theory and topological indices are key tools in the study of molecular structures and their properties. This research explores anticancer drugs using neighborhood degree-based topological indices and compares their efficacy through reg...
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