No abstract

Gene silencing by Polycomb complexes is central to eukaryotic development. Cold-induced epigenetic repression of () in the plant provides an opportunity to study initiation and maintenance of Polycomb silencing. Here, we show that a subset of Polycomb repressive complex 2 factors nucleate silencing in a small region within, locally increasing H3K27me3 levels. This nucleation confers a silenced state that is metastably inherited, with memory held in the local chromatin. Metastable memory is then converted to stable epigenetic silencing through separate Polycomb factors, which spread across the locus after cold to enlarge the domain that contains H3K27me3. Polycomb silencing at thus has mechanistically distinct phases, which involve specialization of distinct Polycomb components to deliver first metastable then long-term epigenetic silencing.

A major problem in structure-based virtual screening applications is the appropriate selection of a single or even multiple protein structures to be used in the virtual screening process. A priori it is unknown which protein structure(s) will perform best in a virtual screening experiment. We investigated the performance of ensemble docking, as a function of ensemble size, for eight targets of pharmaceutical interest. Starting from single protein structure docking results, for each ensemble size up to 500,000 combinations of protein structures were generated, and, for each ensemble, pose prediction and virtual screening results were derived. Comparison of single to multiple protein structure results suggests improvements when looking at the performance of the worst and the average over all single protein structures to the performance of the worst and average over all protein ensembles of size two or greater, respectively. We identified several key factors affecting ensemble docking performance, including the sampling accuracy of the docking algorithm, the choice of the scoring function, and the similarity of database ligands to the cocrystallized ligands of ligand-bound protein structures in an ensemble. Due to these factors, the prospective selection of optimum ensembles is a challenging task, shown by a reassessment of published ensemble selection protocols.

Temperature is a primary environmental stress to which micro-organisms must be able to adapt and respond rapidly. Whereas some bacteria are restricted to specific niches and have limited abilities to survive changes in their environment, others, such as members of the Enterobacteriaceae, can withstand wide fluctuations in temperature. In addition to regulating cellular physiology, pathogenic bacteria use temperature as a cue for activating virulence gene expression. This work confirms that the nucleoid-associated protein H-NS (histone-like nucleoid structuring protein) is an essential component in thermoregulation of Salmonella. On increasing the temperature from 25 to 37 degrees C, more than 200 genes from Salmonella enterica serovar Typhimurium showed H-NS-dependent up-regulation. The thermal activation of gene expression is extremely rapid and change in temperature affects the DNA-binding properties of H-NS. The reduction in gene repression brought about by the increase in temperature is concomitant with a conformational change in the protein, resulting in the decrease in size of high-order oligomers and the appearance of increasing concentrations of discrete dimers of H-NS. The present study addresses one of the key complex mechanisms by which H-NS regulates gene expression.

The extent of enthalpy-entropy compensation in protein-ligand interactions has long been disputed because negatively correlated enthalpy (DH) and entropy (TDS) changes can arise from constraints imposed by experimental and analytical procedures as well as through a physical compensation mechanism. To distinguish these possibilities, we have created quantitative models of the effects of experimental constraints on isothermal titration calorimetry (ITC) measurements. These constraints are found to obscure any compensation that may be present in common data representations and regression analyses (e.g., in DH vs. -TDS plots). However, transforming the thermodynamic data into DD-plots of the differences between all pairs of ligands that bind each protein diminishes the influence of experimental constraints and representational bias. Statistical analysis of data from 32 diverse proteins shows a significant and widespread tendency to compensation. DDH versus DDG plots reveal a wide variation in the extent of compensation for different ligand modifications. While strong compensation (DDH and 2TDDS opposed and differing by < 20% in magnitude) is observed for 22% of modifications (twice that expected without compensation), 15% of modifications result in reinforcement (DDH and 2TDDS of the same sign). Because both enthalpy and entropy changes arise from changes to the distribution of energy states on binding, there is a general theoretical expectation of compensated behavior. However, prior theoretical studies have focussed on explaining a stronger tendency to compensation than actually found here. These results, showing strong but imperfect compensation, will act as a benchmark for future theoretical models of the thermodynamic consequences of ligand modification.

Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods do little to suggest which interactions within a pocket are the most important for binding. Here we illustrate a method that samples atomic hotspots with simple molecular probes to produce fragment hotspot maps. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. The fragment hotspot map calculation is validated using experimental binding positions of 21 fragments and subsequent lead molecules. The ligands are found in high scoring areas of the fragment hotspot maps, with fragment atoms having a median percentage rank of 97%. Protein kinase B and pantothenate synthetase are examined in detail. In each case, the fragment hotspot maps are able to rationalize a Free-Wilson analysis of SAR data from a fragment-based drug design project.

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The protein databank now contains the structures of over 11,000 ligands bound to proteins. These structures are invaluable in applied areas such as structure-based drug design, but are also the substrate for understanding the energetics of intermolecular interactions with proteins. Despite their obvious importance, the careful analysis of ligands bound to protein structures lags behind the analysis of the protein structures themselves. We present an analysis of the geometry of ligands bound to proteins and highlight the role of small molecule crystal structures in enabling molecular modellers to critically evaluate a ligand model’s quality and investigate protein-induced strain.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-011-9538-6) contains supplementary material, which is available to authorized users.