No interactions between heparin and atacicept, an antagonist of B cell survival cytokines.

The TNF family ligands, B cell activating factor of the TNF family (BAFF, also known as B lymphocyte stimulator, BLyS) and a proliferation-inducing ligand (APRIL), share the transmembrane activator and calcium-modulator and cyclophilin ligand (CAML)-interactor (TACI) as one of their common receptors. Atacicept, a chimeric recombinant TACI/IgG1-Fc fusion protein, inhibits both ligands. TACI and APRIL also bind to proteoglycans and to heparin that is structurally related to proteoglycans. It is unknown whether the portion of TACI contained in atacicept can bind directly to proteoglycans, or indirectly via APRIL, and whether this could interfere with the anti-coagulant properties of heparin. Binding of atacicept and APRIL to proteoglycan-positive cells was measured by FACS. Activities of heparin and atacicept were measured with activated factor Xa inhibition and cell-based assays. Effects of heparin on circulating atacicept was monitored in mice. Atacicept did not bind to proteoglycan-positive cells, but when complexed to APRIL could do so indirectly via APRIL. Multimers of atacicept obtained after exposure to cysteine or BAFF 60-mer bound directly to proteoglycans. Atacicept alone, or in complex with APRIL, or in a multimeric form did not interfere with heparin activity in vitro. Conversely, heparin did not influence inhibition of BAFF and APRIL by atacicept and did not change circulating levels of atacicept. Lack of detectable interference of APRIL-bound or free atacicept on heparin activity makes it unlikely that atacicept at therapeutic doses will interfere with the function of heparin in vivo

Quantum mechanics/molecular mechanics modeling of drug metabolism:Mexiletine N-hydroxylation by cytochrome P450 1A2

The mechanism of cytochrome P450­(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (<i>R</i>)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM­(B3LYP-D)/MM­(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site, but this is not a prerequisite for reaction via either mechanism. Several active site residues play a role in the binding of mexiletine in the active site, including Thr124 and Phe226. This work reveals key details of the N-hydroxylation of mexiletine and further demonstrates that mechanistic studies using QM/MM methods are useful for understanding drug metabolism

Identification of New Alleles and the Determination of Alleles and Genotypes Frequencies at the CYP2D6 Gene in Emiratis

CYP2D6 belongs to the cytochrome P450 superfamily of enzymes and plays an important role in the metabolism of 20–25% of clinically used drugs including antidepressants. It displays inter-individual and inter-ethnic variability in activity ranging from complete absence to excessive activity which causes adverse drug reactions and toxicity or therapy failure even at normal drug doses. This variability is due to genetic polymorphisms which form poor, intermediate, extensive or ultrarapid metaboliser phenotypes. This study aimed to determine CYP2D6 alleles and their frequencies in the United Arab Emirates (UAE) local population. CYP2D6 alleles and genotypes were determined by direct DNA sequencing in 151 Emiratis with the majority being psychiatric patients on antidepressants. Several new alleles have been identified and in total we identified seventeen alleles and 49 genotypes. CYP2D6*1 (wild type) and CYP2D6*2 alleles (extensive metaboliser phenotype) were found with frequencies of 39.1% and 12.2%, respectively. CYP2D6*41 (intermediate metaboliser) occurred in 15.2%. Homozygous CYP2D6*4 allele (poor metaboliser) was found with a frequency of 2% while homozygous and heterozygous CYP2D6*4 occurred with a frequency of 9%. CYP2D6*2xn, caused by gene duplication (ultrarapid metaboliser) had a frequency of 4.3%. CYP2D6 gene duplication/multiduplication occurred in 16% but only 11.2% who carried more than 2 active functional alleles were considered ultrarapid metabolisers. CYP2D6 gene deletion in one copy occurred in 7.5% of the study group. In conclusion, CYP2D6 gene locus is heterogeneous in the UAE national population and no significant differences have been identified between the psychiatric patients and controls

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases

Individual Preferences and Social Interactions Determine the Aggregation of Woodlice

n°e17389.info:eu-repo/semantics/publishe