Structural and Dynamic Determinants of Protein-Peptide Recognition

Protein-peptide interactions play important roles in many cellular processes, including signal transduction, trafficking, and immune recognition. Protein conformational changes upon binding, an ill-defined peptide binding surface, and the large number of peptide degrees of freedom make the prediction of protein-peptide interactions particularly challenging. To address these challenges, we perform rapid molecular dynamics simulations in order to examine the energetic and dynamic aspects of protein-peptide binding. We find that, in most cases, we recapitulate the native binding sites and native-like poses of protein-peptide complexes. Inclusion of electrostatic interactions in simulations significantly improves the prediction accuracy. Our results also highlight the importance of protein conformational flexibility, especially side-chain movement, which allows the peptide to optimize its conformation. Our findings not only demonstrate the importance of sufficient sampling of the protein and peptide conformations, but also reveal the possible effects of electrostatics and conformational flexibility on peptide recognition

Systems analysis of the transcriptional response of human ileocecal epithelial cells to Clostridium difficile toxins and effects on cell cycle control

<p>Abstract</p> <p>Background</p> <p>Toxins A and B (TcdA and TcdB) are <it>Clostridium difficile</it>'s principal virulence factors, yet the pathways by which they lead to inflammation and severe diarrhea remain unclear. Also, the relative role of either toxin during infection and the differences in their effects across cell lines is still poorly understood. To better understand their effects in a susceptible cell line, we analyzed the transciptome-wide gene expression response of human ileocecal epithelial cells (HCT-8) after 2, 6, and 24 hr of toxin exposure.</p> <p>Results</p> <p>We show that toxins elicit very similar changes in the gene expression of HCT-8 cells, with the TcdB response occurring sooner. The high similarity suggests differences between toxins are due to events beyond transcription of a single cell-type and that their relative potencies during infection may depend on differential effects across cell types within the intestine. We next performed an enrichment analysis to determine biological functions associated with changes in transcription. Differentially expressed genes were associated with response to external stimuli and apoptotic mechanisms and, at 24 hr, were predominately associated with cell-cycle control and DNA replication. To validate our systems approach, we subsequently verified a novel G₁/S and known G₂/M cell-cycle block and increased apoptosis as predicted from our enrichment analysis.</p> <p>Conclusions</p> <p>This study shows a successful example of a workflow deriving novel biological insight from transcriptome-wide gene expression. Importantly, we do not find any significant difference between TcdA and TcdB besides potency or kinetics. The role of each toxin in the inhibition of cell growth and proliferation, an important function of cells in the intestinal epithelium, is characterized.</p

One entropy function to rule them all

We study the entropy of extremal four dimensional black holes and five dimensional black holes and black rings is a unified framework using Sen's entropy function and dimensional reduction. The five dimensional black holes and black rings we consider project down to either static or stationary black holes in four dimensions. The analysis is done in the context of two derivative gravity coupled to abelian gauge fields and neutral scalar fields. We apply this formalism to various examples including $U(1)^3$ minimal supergravity.Comment: 29 pages, 2 figures, revised version for publication, details adde