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Regulatory T cells (Tregs) reside in nonlymphoid tissues where they carry out unique functions. The molecular mechanisms responsible for Treg accumulation and maintenance in these tissues are relatively unknown. Using an unbiased discovery approach, we identified LAYN (layilin), a C-type lectin-like receptor, to be preferentially and highly expressed on a subset of activated Tregs in healthy and diseased human skin. Expression of layilin on Tregs was induced by TCR-mediated activation in the presence of IL-2 or TGF-β. Mice with a conditional deletion of layilin in Tregs had reduced accumulation of these cells in tumors. However, these animals somewhat paradoxically had enhanced immune regulation in the tumor microenvironment, resulting in increased tumor growth. Mechanistically, layilin expression on Tregs had a minimal effect on their activation and suppressive capacity in vitro. However, expression of this molecule resulted in a cumulative anchoring effect on Treg dynamic motility in vivo. Taken together, our results suggest a model whereby layilin facilitates Treg adhesion in skin and, in doing so, limits their suppressive capacity. These findings uncover a unique mechanism whereby reduced Treg motility acts to limit immune regulation in nonlymphoid organs and may help guide strategies to exploit this phenomenon for therapeutic benefit.

MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/).

A study shows that classical electrostatistics describes the quantitative description of, both the binding of the diatomic ligands XO (X= C. N, O) to the heme group in myoglobin and the dependence of their vibrational frequencies upon an external field by classical electrolysis. It is suggested that ligand binding occurs via an electrostatic bond, a generalization of the standard ionic bond to include induction, and that classical electrostatics can replace quantum mechanics for a considerable simplification of some complex problems.

A polarizable, flexible and transferable potential for water, POLIR, is presented. In addition to providing a good description of the usual structural and kinetic properties, POLIR correctly describes the vibrational frequencies, absolute infrared intensities, and HOH angle in clusters, liquid water, and ice, offering the possibility of a comprehensive classical theory of vibrational spectroscopy. The high degree of transferability suggests applications to solvation and to water that is confined, interfacial, and under the extreme conditions encountered in the geological and planetary sciences. [ABSTRACT FROM AUTHOR]

Far-infrared intermolecular and midinfrared vibrational spectra of CO liquid have been calculated by Fourier transforming the quantum-corrected classical dipole correlation. The time dependence of the coordinates is determined from a standard nonpolarizable force field, and the dipole is determined from the coordinates with a “spectroscopic model” proposed herein. The model includes intramolecular induction and atomic charges, polarizabilities, and permanent dipoles. A good agreement with available experimental spectra is achieved. Our results demonstrate that the use of an anharmonic potential is necessary to reproduce the experimentally observed shift upon going from gas to liquid. The behavior of the simulated dipole time correlation functions suggests that CO liquid at 80 K exhibits aspects of both free rotation and solidlike caging. The proposition of some free rotation present in CO liquid supports Ewing’s experimental hypothesis. [ABSTRACT FROM AUTHOR]

Background: The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets. Methods and Results: Integration of miRNA and gene patterns yielded evidence that proximal pairs of miRNAs are processed from polycistronic primary transcripts, and that intronic miRNAs and their host gene mRNAs derive from common transcripts. Patterns of miRNA expression revealed multiple tumor subtypes and a set of 34 miRNAs predictive of overall patient survival. In a global analysis, miRNA:mRNA pairs anti-correlated in expression across tumors showed a higher frequency of in silico predicted target sites in the mRNA 3'-untranslated region (with less frequency observed for coding sequence and 5'-untranslated regions). The miR-29 family and predicted target genes were among the most strongly anticorrelated miRNA:mRNA pairs; over-expression of miR-29a in vitro repressed several anti-correlated genes (including DNMT3A and DNMT3B) and substantially decreased ovarian cancer cell viability. Conclusions: This study establishes miRNAs as having a widespread impact on gene expression programs in ovarian cancer, further strengthening our understanding of miRNA biology as it applies to human cancer. As with gene transcripts, miRNAs exhibit high diversity reflecting the genomic heterogeneity within a clinically homogeneous disease population. Putative miRNA:mRNA interactions, as identified using integrative analysis, can be validated. TCGA data are a valuable resource for the identification of novel tumor suppressive miRNAs in ovarian as well as other cancers. [ABSTRACT FROM AUTHOR]