Activation of human factor V by Meizothrombin

A recombinant human prothrombin was prepared in which Arg155 was replaced by Ala. The recombinant prothrombin was converted into a meizothrombin derivative (R155A meizothrombin) that was resistant to autocatalytic removal of the fragment 1 domain. R155A meizothrombin appeared to be a potent factor V activator in reaction mixtures that contained negatively charged phospholipid vesicles. Factor V activation by R155A meizothrombin was characterized by second-order rate constants of 0.06 x 10(6) M-1 S-1 in the absence of phospholipid and 18 x 10(6) M-1 S-1 in the presence of 60 microM phospholipid vesicles composed of a 10:90 mol/mol mixture of phosphatidylserine (PS) and phosphatidylcholine (PC). The rate constant for thrombin-catalyzed activation of factor V was hardly affected by the presence of phospholipid vesicles and was 4.0 x 10(6) M-1 S-1. The initial rate of activation of 3 nM factor V by R155A meizothrombin was a function of the concentration of PS/PC vesicles present in the reaction mixture, and the calculated rate constant reached a plateau value at > or = 50 microM PS/PC. Gel electrophoretic analysis of factor V activation showed that R155A meizothrombin and thrombin cleaved the susceptible peptide bonds in factor V at different rates. However, both activators finally generated a factor Va molecule composed of a heavy chain with an M(r) of 104,000 and a light chain doublet with M(r) values of 74,000 and 71,000. Since meizothrombin is one of the major reaction products formed during the initial phase of prothrombin activation, these findings are indicative of a significant contribution of meizothrombin to in vivo factor V activatio

Structural anomalies in a published NMR-derived structure of IRAK-M

Signaling by Toll-Like Receptors and the Interleukin-1 Receptor (IL1-R) involves intracellular binding of MyD88, followed by assembly of IL1-R Associated Kinases (IRAKs) into the so-called Myddosome. Using NMR, Nechama et al. determined the structure of the IRAK-M death domain monomer (PDBid: 5UKE). With this structure, they performed a docking study to model the location of IRAK-M in the Myddosome. Based on this, they present a molecular basis for selectivity of IRAK-M towards IRAK1 over IRAK2 binding. When we attempted to use 5UKE as a homology modeling template, we noticed that our 5UKE-based models had structural issues, such as disallowed torsion angles and solvent exposed tryptophans. We therefore analyzed the NMR ensemble of 5UKE using structure validation tools and we compared 5UKE with homologous high-resolution X-ray structures. We identified several structural anomalies in 5UKE, including packing issues, frayed helices and improbable side chain conformations. We used Yasara to build a homology model, based on two high resolution death domain crystal structures, as an alternative model for the IRAK-M death domain (atomic coordinates, modeling details and validation are available at https://swift.cmbi.umcn.nl/gv/service/5uke/). Our model agrees better with known death domain structure information than 5UKE and also with the chemical shift data that was deposited for 5UKE

Biochemical, molecular characterization, and glycoproteomic analyses of alpha(1)-proteinase inhibitor products used for replacement therapy

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Structural anomalies in a published NMR-derived structure of IRAK-M

Signaling by Toll-Like Receptors and the Interleukin-1 Receptor (IL1-R) involves intracellular binding of MyD88, followed by assembly of IL1-R Associated Kinases (IRAKs) into the so-called Myddosome. Using NMR, Nechama et al. determined the structure of the IRAK-M death domain monomer (PDBid: 5UKE). With this structure, they performed a docking study to model the location of IRAK-M in the Myddosome. Based on this, they present a molecular basis for selectivity of IRAK-M towards IRAK1 over IRAK2 binding. When we attempted to use 5UKE as a homology modeling template, we noticed that our 5UKE-based models had structural issues, such as disallowed torsion angles and solvent exposed tryptophans. We therefore analyzed the NMR ensemble of 5UKE using structure validation tools and we compared 5UKE with homologous high-resolution X-ray structures. We identified several structural anomalies in 5UKE, including packing issues, frayed helices and improbable side chain conformations. We used Yasara to build a homology model, based on two high resolution death domain crystal structures, as an alternative model for the IRAK-M death domain (atomic coordinates, modeling details and validation are available at https://swift.cmbi.umcn.nl/gv/service/5uke/). Our model agrees better with known death domain structure information than 5UKE and also with the chemical shift data that was deposited for 5UKE

Comparative Analysis of Pharmacophore Screening Tools

The pharmacophore concept is of central importance in computer-aided drug design (CADD) mainly because of its successful application in medicinal chemistry and, in particular, high-throughput virtual screening (HTVS). The simplicity of the pharmacophore definition enables the complexity of molecular interactions between ligand and receptor to be reduced to a handful set of features. With many pharmacophore screening softwares available, it is of the utmost interest to explore the behavior of these tools when applied to different biological systems. In this work, we present a comparative analysis of eight pharmacophore screening algorithms (Catalyst, Unity, LigandScout, Phase, Pharao, MOE, Pharmer, and POT) for their use in typical HTVS campaigns against four different biological targets by using default settings. The results herein presented show how the performance of each pharmacophore screening tool might be specifically related to factors such as the characteristics of the binding pocket, the use of specific pharmacophore features, and the use of these techniques in specific steps/contexts of the drug discovery pipeline. Algorithms with rmsd-based scoring functions are able to predict more compound poses correctly as overlay-based scoring functions. However, the ratio of correctly predicted compound poses versus incorrectly predicted poses is better for overlay-based scoring functions that also ensure better performances in compound library enrichments. While the ensemble of these observations can be used to choose the most appropriate class of algorithm for specific virtual screening projects, we remarked that pharmacophore algorithms are often equally good, and in this respect, we also analyzed how pharmacophore algorithms can be combined together in order to increase the success of hit compound identification. This study provides a valuable benchmark set for further developments in the field of pharmacophore search algorithms, e.g., by using pose predictions and compound library enrichment criteria