In silico approach to inhibition of signaling pathways of Toll-like receptors 2 and 4 by ST2L

Toll-like receptors (TLRs) activate a potent immunostimulatory response. There is clear evidence that overactivation of TLRs leads to infectious and inflammatory diseases. Recent biochemical studies have shown that the membrane-bound form of ST2 (ST2L), a member of the Toll-like/IL-1 receptor superfamily, negatively regulates MyD88-dependent TLR signaling pathways by sequestrating the adapters MyD88 and Mal (TIRAP). Specifically, ST2L attenuates the recruitment of Mal and MyD88 adapters to their receptors through its intracellular TIR domain. Thus, ST2L is a potent molecule that acts as a key regulator of endotoxin tolerance and modulates innate immunity. So far, the inhibitory mechanism of ST2L at the molecular level remains elusive. To develop a working hypothesis for the interactions between ST2L, TLRs (TLR1, 2, 4, and 6), and adapter molecules (MyD88 and Mal), we constructed three-dimensional models of the TIR domains of TLR4, 6, Mal, and ST2L based on homology modeling. Since the crystal structures of the TIR domains of TLR1, 2 as well as the NMR solution structure of MyD88 are known, we utilized these structures in our analysis. The TIR domains of TLR1, 2, 4, 6, MyD88, Mal and ST2L were subjected to molecular dynamics (MD) simulations in an explicit solvent environment. The refined structures obtained from the MD simulations were subsequently used in molecular docking studies to probe for potential sites of interactions. Through protein-protein docking analysis, models of the essential complexes involved in TLR2 and 4 signaling and ST2L inhibiting processes were developed. Our results suggest that ST2L may exert its inhibitory effect by blocking the molecular interface of Mal and MyD88 adapters mainly through its BB-loop region. Our predicted oligomeric signaling models may provide a basis for the understanding of the assembly process of TIR domain interactions, which has thus far proven to be difficult via in vivo studies.     

Genomic inference accurately predicts the timing and severity of a recent bottleneck in a nonmodel insect population

The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here, we present and evaluate a method of SNP discovery using RNA sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has as experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all‐in‐one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other nonmodel systems.     

Truthful online double auction based dynamic resource provisioning for multi-objective trade-offs in IaaS clouds

Auction designs have recently been adopted for static and dynamic resource provisioning in IaaS clouds, such as Microsoft Azure and Amazon EC2. However, the existing mechanisms are mostly restricted to simple auctions, single-objective, offline setting, one-sided interactions either among cloud users or cloud service providers (CSPs), and possible misreports of cloud user’s private information. This paper proposes a more realistic scenario of online auctioning for IaaS clouds, with the unique characteristics of elasticity for time-varying arrival of cloud user requests under the time-based server maintenance in cloud data centers. We propose an online truthful double auction technique for balancing the multi-objective trade-offs between energy, revenue, and performance in IaaS clouds, consisting of a weighted bipartite matching based winning-bid determination algorithm for resource allocation and a Vickrey–Clarke–Groves (VCG) driven algorithm for payment calculation of winning bids. Through rigorous theoretical analysis and extensive trace-driven simulation studies exploiting Google cluster workload traces, we demonstrate that our mechanism significantly improves the performance while promising truthfulness, heterogeneity, economic efficiency, individual rationality, and has a polynomial-time computational complexity.

     

Enhanced prostacyclin formation and Wnt signaling in sclerostin deficient osteocytes and bone

We show that prostacyclin production is increased in bone and osteocytes from sclerostin (Sost) knockout mice which have greatly increased bone mass. The addition of prostacyclin or a prostacyclin analog to bone forming osteoblasts enhances differentiation and matrix mineralization of osteoblasts. The increase in prostacyclin synthesis is linked to increases in β-catenin concentrations and activity as shown by enhanced binding of lymphoid enhancer factor, Lef1, to promoter elements within the prostacyclin synthase promoter. Blockade of Wnt signaling reduces prostacyclin production in osteocytes. Increased prostacyclin production by osteocytes from sclerostin deficient mice could potentially contribute to the increased bone formation seen in this condition.     

Modeling amyloid beta-peptide insertion into lipid bilayers

Inspired by recent suggestions that the Alzheimer's amyloid beta peptide (Abeta) can insert into cell membranes and form harmful ion channels, we model insertion of the 40- and 42-residue forms of the peptide into cell membranes using a Monte Carlo code which is specific at the amino acid level. We examine insertion of the regular Abeta peptide as well as mutants causing familial Alzheimer's disease, and find that all but one of the mutants change the insertion behavior by causing the peptide to spend more simulation steps in only one leaflet of the bilayer. We also find that Abeta42, because of the extra hydrophobic residues relative to Abeta40, is more likely to adopt this conformation than Abeta40 in both wild-type and mutant forms. We argue qualitatively why these effects happen. Here, we present our results and develop the hypothesis that this partial insertion increases the probability of harmful channel formation. This hypothesis can partly explain why these mutations are neurotoxic simply due to peptide insertion behavior. We further apply this model to various artificial Abeta mutants which have been examined experimentally, and offer testable experimental predictions contrasting the roles of aggregation and insertion with regard to toxicity of Abeta mutants. These can be used through further experiments to test our hypothesis.     

Discovery and initial optimization of 5,5′-disubstituted aminohydantoins as potent β-secretase (BACE1) inhibitors

8,8-Diphenyl-2,3,4,8-tetrahydroimidazo[1,5-a]pyrimidin-6-amine (1) was identified through HTS, as a weak (micromolar) inhibitor of BACE1. X-Ray crystallographic studies indicate the 2-aminoimidazole ring forms key H-bonding interactions with Asp32 and Asp228 in the catalytic site of BACE1. Lead optimization using structure-based focused libraries led to the identification of low nanomolar BACE1 inhibitors such as 20b with substituents which extend from the S₁ to the S₃ pocket.     

Crystallographic Study of Novel Transthyretin Ligands Exhibiting Negative-Cooperativity between Two Thyroxine Binding Sites

Background

Transthyretin (TTR) is a homotetrameric serum and cerebrospinal fluid protein that transports thyroxine (T4) and retinol by binding to retinol binding protein. Rate-limiting tetramer dissociation and rapid monomer misfolding and disassembly of TTR lead to amyloid fibril formation in different tissues causing various amyloid diseases. Based on the current understanding of the pathogenesis of TTR amyloidosis, it is considered that the inhibition of amyloid fibril formation by stabilization of TTR in native tetrameric form is a viable approach for the treatment of TTR amyloidosis.

Methodology and Principal Findings

We have examined interactions of the wtTTR with a series of compounds containing various substitutions at biphenyl ether skeleton and a novel compound, previously evaluated for binding and inhibiting tetramer dissociation, by x-ray crystallographic approach. High resolution crystal structures of five ligands in complex with wtTTR provided snapshots of negatively cooperative binding of ligands in two T4 binding sites besides characterizing their binding orientations, conformations, and interactions with binding site residues. In all complexes, the ligand has better fit and more potent interactions in first T4 site i.e. (AC site) than the second T4 site (BD site). Together, these results suggest that AC site is a preferred ligand binding site and retention of ordered water molecules between the dimer interfaces further stabilizes the tetramer by bridging a hydrogen bond interaction between Ser117 and its symmetric copy.

Conclusion

Novel biphenyl ether based compounds exhibit negative-cooperativity while binding to two T4 sites which suggests that binding of only single ligand molecule is sufficient to inhibit the TTR tetramer dissociation.