Project description:Pharmacologic effects elicited by drugs most directly relate to their unbound concentrations. Measurement of binding in blood, plasma and target tissues are used to estimate these concentrations by determining the fraction of total concentration in a biological matrix that is not bound. In the case of attempting to estimate R- and S-bupropion concentrations in plasma and brain following racemic bupropion administration, reversible chiral inversion and irreversible degradation of the enantiomers were hypothesized to confound attempts at unbound fraction estimation. To address this possibility, a kinetic modeling approach was used to quantify inversion and degradation specific processes for each enantiomer from separate incubations of each enantiomer in the two matrices, and in pH 7.4 buffer, which is also used in binding experiments based on equilibrium dialysis. Modeling analyses indicated that chiral inversion kinetics were two to four-fold faster in plasma and brain than degradation, with only inversion observed in buffer. Inversion rate was faster for S-bupropion in the three media; whereas, degradation rates were similar for the two enantiomers in plasma and brain, with overall degradation in plasma approximately 2-fold higher than in brain homogenate. Incorporation of degradation and chiral inversion kinetic terms into a model to predict enantiomer-specific binding in plasma and brain revealed that, despite existence of these two processes, empirically derived estimates of fraction unbound were similar to model-derived values, leading to a firm conclusion that observed extent of plasma and brain binding are accurate largely because binding kinetics are faster than parallel degradation and chiral inversion processes.
Project description:Large-scale initiatives for obtaining spatial protein structures by experimental or computational means have accentuated the need for the critical assessment of protein structure determination and prediction methods. These include blind test projects such as the critical assessment of protein structure prediction (CASP) and the critical assessment of protein structure determination by nuclear magnetic resonance (CASD-NMR). An important aim is to establish structure validation criteria that can reliably assess the accuracy of a new protein structure. Various quality measures derived from the coordinates have been proposed. A universal structural quality assessment method should combine multiple individual scores in a meaningful way, which is challenging because of their different measurement units. Here, we present a method based on a generalized linear model (GLM) that combines diverse protein structure quality scores into a single quantity with intuitive meaning, namely the predicted coordinate root-mean-square deviation (RMSD) value between the present structure and the (unavailable) "true" structure (GLM-RMSD). For two sets of structural models from the CASD-NMR and CASP projects, this GLM-RMSD value was compared with the actual accuracy given by the RMSD value to the corresponding, experimentally determined reference structure from the Protein Data Bank (PDB). The correlation coefficients between actual (model vs. reference from PDB) and predicted (model vs. "true") heavy-atom RMSDs were 0.69 and 0.76, for the two datasets from CASD-NMR and CASP, respectively, which is considerably higher than those for the individual scores (-0.24 to 0.68). The GLM-RMSD can thus predict the accuracy of protein structures more reliably than individual coordinate-based quality scores.
Project description:ObjectivesTo describe the unbound and total flucloxacillin pharmacokinetics in critically ill patients and to define optimal dosing strategies.Patients and methodsObservational multicentre study including a total of 33 adult ICU patients receiving flucloxacillin, given as intermittent or continuous infusion. Pharmacokinetic sampling was performed on two occasions on two different days. Total and unbound flucloxacillin concentrations were measured and analysed using non-linear mixed-effects modelling. Serum albumin was added as covariate on the maximum binding capacity and endogenous creatinine clearance (CLCR) as covariate for renal function. Monte Carlo simulations were performed to predict the unbound flucloxacillin concentrations for different dosing strategies and different categories of endogenous CLCR.ResultsThe measured unbound concentrations ranged from 0.2 to 110 mg/L and the observed unbound fraction varied between 7.0% and 71.7%. An integral two-compartmental linear pharmacokinetic model based on total and unbound concentrations was developed. A dose of 12 g/24 h was sufficient for 99.9% of the population to achieve a concentration of >2.5 mg/L (100% fT>5×MIC, MIC = 0.5 mg/L).ConclusionsCritically ill patients show higher unbound flucloxacillin fractions and concentrations than previously thought. Consequently, the risk of subtherapeutic exposure is low.
Project description:The mathematical foundation of quantum mechanics is built on linear algebra, while the application of nonlinear operators can lead to outstanding discoveries under some circumstances, such as the prediction of positron, a direct outcome of the Dirac equation which stems from the square-root of the Klein-Gordon equation. In this article, we propose a model of square-root higher-order Weyl semimetal (SHOWS) by inheriting features from its parent Hamiltonians. It is found that the SHOWS hosts both "Fermi-arc" surface and hinge states that respectively connect the projection of the Weyl points on the side surface and arris. We theoretically construct and experimentally observe the exotic SHOWS state in three-dimensional (3D) stacked electric circuits with honeycomb-kagome hybridizations and double-helix interlayer couplings. Our results open the door for realizing the square-root topology in 3D solid-state platforms.
Project description:We determined for the first time the profiles of the nine most abundant unbound FFAs (FFAus) in human plasma. Profiles were determined for a standard reference plasma of pooled healthy adults for which the Lipid MAPSMAPS Consortium had determined the total FFA profiles. Measurements were performed by using 20 different acrylodan-labeled fatty acid binding protein mutants (probes), which have complementary specificities for the nine FFAs that comprise more than 96% of long-chain plasma FFA. The acrylodan fluorescence emission for each probe changes upon binding a FFAu. The plasma concentrations of each of the nine FFAus were determined by combining the measured fluorescence ratios of the 20 probes. The total molar FFAu concentration accounted for <10-5 of the total FFA concentration, and the mole fractions of the FFAu profiles were substantially different than the total FFA profiles. Myristic acid, for example, comprises 22% of the unbound versus 2.8% of the total. The most surprising difference is our finding of zero unbound cis-9-palmitoleic acid (POA), whereas the total POA was 7.2%. An unidentified plasma component appears to specifically prevent the release of POA. FFAus are the physiologically active FFAs, and plasma FFAu profiles may provide novel information about human health.
Project description:We present the application of seven binding-site prediction algorithms to a meticulously curated dataset of ligand-bound and ligand-free crystal structures for 304 unique protein sequences (2528 crystal structures). We probe the influence of starting protein structures on the results of binding-site prediction, so the dataset contains a minimum of two ligand-bound and two ligand-free structures for each protein. We use this dataset in a brief survey of five geometry-based, one energy-based, and one machine-learning-based methods: Surfnet, Ghecom, LIGSITEcsc, Fpocket, Depth, AutoSite, and Kalasanty. Distributions of the F scores and Matthew's correlation coefficients for ligand-bound versus ligand-free structure performance show no statistically significant difference in structure type versus performance for most methods. Only Fpocket showed a statistically significant but low magnitude enhancement in performance for holo structures. Lastly, we found that most methods will succeed on some crystal structures and fail on others within the same protein family, despite all structures being relatively high-quality structures with low structural variation. We expected better consistency across varying protein conformations of the same sequence. Interestingly, the success or failure of a given structure cannot be predicted by quality metrics such as resolution, Cruickshank Diffraction Precision index, or unresolved residues. Cryptic sites were also examined.
Project description:Despite improvement in treatment options for myeloma patients, including targeted immunotherapies, multiple myeloma remains a mostly incurable malignancy. High CS1 (SLAMF7) expression on myeloma cells and limited expression on normal cells makes it a promising target for CAR-T therapy. The CS1 protein has two extracellular domains - the distal Variable (V) domain and the proximal Constant 2 (C2) domain. We generated and tested CS1-CAR-T targeting the V domain of CS1 (Luc90-CS1-CAR-T) and demonstrated anti-myeloma killing in vitro and in vivo using two mouse models. Since fratricide of CD8 + cells occurred during production, we generated fratricide resistant CS1 deficient Luc90- CS1- CAR-T (ΔCS1-Luc90- CS1- CAR-T). This led to protection of CD8 + cells in the CAR-T cultures, but had no impact on efficacy. Our data demonstrate targeting the distal V domain of CS1 could be an effective CAR-T treatment for myeloma patients and deletion of CS1 in clinical production did not provide an added benefit using in vivo immunodeficient NSG preclinical models.