In this study, a quantitative threshold was determined for the high/low extent of urinary excretion (UE) of compounds in humans, using a straightforward but robust statistical method known as receiver operating characteristic curve (ROC) analysis, and also 18 potential physicochemical determinants of UE were evaluated. Data on the percent of drug excreted unchanged into the urine, %Ae , were used to determine the threshold for high/low UE. Compounds can be divided into high/low UE groups using the threshold value of Ae = 16.8%, namely those with Ae > 16.8% are classified as high UE and those with Ae ≤ 16.8% as low UE. The %Ae negatively correlated with cLogP (r = -0.56); however, cLogP could not quantitatively predict the value of %Ae (R(2) adj. = 0.32). Several determinants of the extent of UE, including cLogP, ACD labs cLogP and ACD labs cLogD(pH=7.4) , were successfully evaluated as a priori indicators of the extent of UE using two cut-off values for each parameter. Moreover, 87% of the 90 compounds in the external validation set were correctly classified using this approach. Analysis of the physicochemical spaces of compounds in these two groups showed significant overlap, which hinders the a priori determination of the extent of UE of compounds using a single threshold/cut-off value of simple physicochemical parameters. In conclusion, 16.8% is a quantitative threshold value to distinguish between high and low UE and new molecular entities with cLogP and ACD labs cLogP values of ≤0.7 and ≥1.0 and ACD labs cLogD(pH=7.4) values of ≤0.0 and ≥0.5 could be identified as exhibiting high and low UE, respectively. Copyright © 2016 John Wiley & Sons, Ltd.
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http://dx.doi.org/10.1002/bdd.2013 | DOI Listing |
SAGE Open Med
October 2024
Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Background: In silico predictions are now being utilized in drug discovery and design to assess the physicochemical, pharmacokinetics, and safety properties of compounds at the beginning of the drug discovery process. This early evaluation of the physicochemical, pharmacokinetics, and safety properties of compounds helps the researchers to invest their time and resources only in the best prospective lead compounds by eliminating compounds with a low chance of success.
Objective: The purpose of this study was to explore a promising lead compound designed from 1-piperazine indole hybrid with nicotinic amide and nicotinic acid analogs targeted on phosphofructokinase for Trypanosomiasis activity by using in silico predictions strategy.
Ther Adv Med Oncol
September 2024
Division of Gynecologic Oncology, Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Background: In Part 1 of the phase III RUBY trial (NCT03981796) in patients with primary advanced or recurrent endometrial cancer (EC), dostarlimab plus carboplatin-paclitaxel (CP) significantly improved progression-free survival and overall survival compared with CP alone. Limited safety data have been reported for the combination of immunotherapies plus chemotherapy in this setting.
Objectives: The objective of this analysis was to identify the occurrence of treatment-related adverse events (TRAEs) and immune-related adverse events (irAEs) and to describe irAE management in Part 1 of the RUBY trial.
J Cell Biol
September 2024
Department of Microbiology, Max Perutz Labs Vienna, University of Vienna, Immunobiology and Genetics, Vienna, Austria.
Hematopoietic stem cells (HSCs) continuously replenish mature blood cells with limited lifespans. To maintain the HSC compartment while ensuring output of differentiated cells, HSCs undergo asymmetric cell division (ACD), generating two daughter cells with different fates: one will proliferate and give rise to the differentiated cells' progeny, and one will return to quiescence to maintain the HSC compartment. A balance between MEK/ERK and mTORC1 pathways is needed to ensure HSC homeostasis.
View Article and Find Full Text PDFJ Chem Inf Model
April 2024
Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Pepparedsleden 1, 43183 Mölndal, Sweden.
In the pursuit of improved compound identification and database search tasks, this study explores heteronuclear single quantum coherence (HSQC) spectra simulation and matching methodologies. HSQC spectra serve as unique molecular fingerprints, enabling a valuable balance of data collection time and information richness. We conducted a comprehensive evaluation of the following four HSQC simulation techniques: ACD/Labs (ACD), MestReNova (MNova), Gaussian NMR calculations (DFT), and a graph-based neural network (ML).
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