Correction to Designing QSARs for Parameters of High Throughput Toxicokinetic Models Using Open-Source Descriptors.

The intrinsic metabolic clearance rate (Cl) and fraction of chemical unbound in plasma () serve as important parameters for high throughput toxicokinetic models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable predictions for a diverse set of chemicals regulated under U.S.

Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors.

The intrinsic metabolic clearance rate (Cl) and the fraction of the chemical unbound in plasma () serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable predictions for a diverse set of chemicals regulated under the U.S.

Genetic Mutations in the S-loop of Human Glutathione Synthetase: Links Between Substrate Binding, Active Site Structure and Allostery.

The second step in the biosynthesis of the cellular antioxidant glutathione (GSH) is catalyzed by human glutathione synthetase (hGS), a negatively cooperative homodimer. Patients with mutations in hGS have been reported to exhibit a range of symptoms from hemolytic anemia and metabolic acidosis to neurological disorders and premature death. Several patient mutations occur in the S-loop of hGS, a series of residues near the negatively cooperative γ-GC substrate binding site.

Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability.

The free fraction of a xenobiotic in plasma (F) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data are scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict F for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals.

The acetaminophen metabolite N-acetyl-p-benzoquinone imine (NAPQI) inhibits glutathione synthetase in vitro; a clue to the mechanism of 5-oxoprolinuric acidosis?

1. Metabolic acidosis due to accumulation of l-5-oxoproline is a rare, poorly understood, disorder associated with acetaminophen treatment in malnourished patients with chronic morbidity. l-5-Oxoprolinuria signals abnormal functioning of the γ-glutamyl cycle, which recycles and synthesises glutathione.

The role of strong electrostatic interactions at the dimer interface of human glutathione synthetase.

The obligate homodimer human glutathione synthetase (hGS) provides an ideal system for exploring the role of protein-protein interactions in the structural stability, activity and allostery of enzymes. The two active sites of hGS, which are 40 Å apart, display allosteric modulation by the substrate γ-glutamylcysteine (γ-GC) during the synthesis of glutathione, a key cellular antioxidant. The two subunits interact at a relatively small dimer interface dominated by electrostatic interactions between S42, R221, and D24.