Introduction: The therapeutic outcome of oximes used as reactivators of phosphorylated human acetylcholinesterase (AChE) is influenced, among other factors, by their biological distribution, their in vivo ability to achieve the nucleophilic attack and their affinity for the anionic center of the intact/inhibited AChE.
Areas Covered: An in silico evaluation of the molecular descriptors and biopharmaceutical properties of 454 set of oximes has been achieved. The available pharmacokinetic (PK) data was analyzed, in an attempt to illustrate their common characteristics and particularities. Based on the observed high water solubility and low permeability across biological barriers, we applied the officially adopted classification systems based on biopharmaceutical properties to identify the existing biopharmaceutical differences between the various oxime entities and to predict their in vivo fate.
Expert Opinion: The structural differences of the organophosphorus compounds (OP) and the available oximes reactivators of OP-inhibited AChE generate distinct toxicokinetic or PK profiles. The tissue compartment specific distribution is one of the key elements for assessment of reactivating efficiency. The distribution through highly specialized barriers, such as blood-brain barrier remains a considerable challenge. The high solubility - low permeability biopharmaceutical profile of oximes can be used to suggest the possible involvement of active transport systems.
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http://dx.doi.org/10.1517/17425255.2015.980813 | DOI Listing |
Eur J Pharm Biopharm
January 2025
Background: Given the challenges of pediatric antibacterial therapy, it is crucial to formulate antibiotics with a lower potential for interaction with dietary interventions and tailor them for optimal administration in children. Chemometric methods allow us to analyze multiple interrelated variables simultaneously and uncover correlations.
Aim: We applied a chemometric approach to examine how food, beverages, antacids, and mineral supplements affect antibiotic bioavailability in adults and children, aiming to explore relationships between antibiotic structure, physicochemical properties, and post-meal changes in pharmacokinetic (PK) parameters.
J Chem Inf Model
January 2025
Industrial and Molecular Pharmaceutics, Purdue University, West Lafayette, Indiana 47907, United States.
Drug-drug interaction can lead to diminished therapeutic effects or increased toxicity, posing significant risks, especially in polypharmacy, and cytochrome P450 plays an indispensable role in this interaction. Cytochrome P450, responsible for the metabolism and detoxification of most drugs, metabolizes about 90% of Food and Drug Administration-approved drugs, making early detection of potential drug-drug interactions. Over the years, in-silico modeling has become a valuable tool for predicting drug-drug interactions.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Maize Research Institute Zemun Polje, Slobodana Bajića 1, 11185 Belgrade, Serbia.
Driven by the growing demands for plant-based protein in Europe and attempts of soybean breeding programs to improve the productivity of created varieties, this study aimed to enhance genetic resource utilization efficiency by providing information relevant to well-focused breeding targets. A set of 90 accessions was subjected to a comprehensive assessment of genetic diversity in a soybean working collection using three marker types: morphological descriptors, agronomic traits, and SSRs. Genotype grouping patterns varied among the markers, displaying the best congruence with pedigree data and maturity for SSRs and agronomic traits, respectively.
View Article and Find Full Text PDFPharmaceuticals (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 PDFAntibiotics (Basel)
January 2025
Department of Food Chemistry and Nutrition, Faculty of Pharmacy, Jagiellonian University Medical College, 31-008 Cracow, Poland.
Background/objectives: Developing antifungal drugs with lower potential for interactions with food may help to optimize treatment and reduce the risk of antimicrobial resistance. Chemometrics uses statistical and mathematical methods to analyze multivariate chemical data, enabling the identification of key correlations and simplifying data interpretation. We used the partial least squares (PLS) approach to explore the correlations between various characteristics of oral antifungal drugs (including antifungal antibiotics) and dietary interventions, aiming to identify patterns that could inform the optimization of antifungal therapy.
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