Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development.

During differentiation of embryonic stem cells, chromatin reorganizes to establish cell type-specific expression programs. Here, we have dissected the linkages between DNA methylation (5mC), hydroxymethylation (5hmC), nucleosome repositioning, and binding of the transcription factor CTCF during this process. By integrating MNase-seq and ChIP-seq experiments in mouse embryonic stem cells (ESC) and their differentiated counterparts with biophysical modeling, we found that the interplay between these factors depends on their genomic context. The mostly unmethylated CpG islands have reduced nucleosome occupancy and are enriched in cell type-independent binding sites for CTCF. The few remaining methylated CpG dinucleotides are preferentially associated with nucleosomes. In contrast, outside of CpG islands most CpGs are methylated, and the average methylation density oscillates so that it is highest in the linker region between nucleosomes. Outside CpG islands, binding of TET1, an enzyme that converts 5mC to 5hmC, is associated with labile, MNase-sensitive nucleosomes. Such nucleosomes are poised for eviction in ESCs and become stably bound in differentiated cells where the TET1 and 5hmC levels go down. This process regulates a class of CTCF binding sites outside CpG islands that are occupied by CTCF in ESCs but lose the protein during differentiation. We rationalize this cell type-dependent targeting of CTCF with a quantitative biophysical model of competitive binding with the histone octamer, depending on the TET1, 5hmC, and 5mC state.

Synthesis, SAR and molecular docking study of novel non-ß-lactam inhibitors of TEM type ß-lactamase.

The novel classes of acylated phenoxyanilide and thiourea compounds were investigated for their ability to inhibit TEM type ß-lactamase enzyme. Two compounds 4g and 5c reveal the inhibition potency in micromolar range and show their action by non-covalent binding in the vicinity of the TEM-171 active site. The structure activity relationship around carbon chain length and different substituents in ortho- and para-positions of acylated phenoxyanilide as well as molecular modelling study has been performed.

Regulation of the nucleosome repeat length in vivo by the DNA sequence, protein concentrations and long-range interactions.

The nucleosome repeat length (NRL) is an integral chromatin property important for its biological functions. Recent experiments revealed several conflicting trends of the NRL dependence on the concentrations of histones and other architectural chromatin proteins, both in vitro and in vivo, but a systematic theoretical description of NRL as a function of DNA sequence and epigenetic determinants is currently lacking. To address this problem, we have performed an integrative biophysical and bioinformatics analysis in species ranging from yeast to frog to mouse where NRL was studied as a function of various parameters. We show that in simple eukaryotes such as yeast, a lower limit for the NRL value exists, determined by internucleosome interactions and remodeler action. For higher eukaryotes, also the upper limit exists since NRL is an increasing but saturating function of the linker histone concentration. Counterintuitively, smaller H1 variants or non-histone architectural proteins can initiate larger effects on the NRL due to entropic reasons. Furthermore, we demonstrate that different regimes of the NRL dependence on histone concentrations exist depending on whether DNA sequence-specific effects dominate over boundary effects or vice versa. We consider several classes of genomic regions with apparently different regimes of the NRL variation. As one extreme, our analysis reveals that the period of oscillations of the nucleosome density around bound RNA polymerase coincides with the period of oscillations of positioning sites of the corresponding DNA sequence. At another extreme, we show that although mouse major satellite repeats intrinsically encode well-defined nucleosome preferences, they have no unique nucleosome arrangement and can undergo a switch between two distinct types of nucleosome positioning.

Taking into account nucleosomes for predicting gene expression.

The eukaryotic genome is organized in a chain of nucleosomes that consist of 145-147 bp of DNA wrapped around a histone octamer protein core. Binding of transcription factors (TF) to nucleosomal DNA is frequently impeded, which makes it a challenging task to calculate TF occupancy at a given regulatory genomic site for predicting gene expression. Here, we review methods to calculate TF binding to DNA in the presence of nucleosomes. The main theoretical problems are (i) the computation speed that is becoming a bottleneck when partial unwrapping of DNA from the nucleosome is considered, (ii) the perturbation of the binding equilibrium by the activity of ATP-dependent chromatin remodelers, which translocate nucleosomes along the DNA, and (iii) the model parameterization from high-throughput sequencing data and fluorescence microscopy experiments in living cells. We discuss strategies that address these issues to efficiently compute transcription factor binding in chromatin.

Profiles of equilibrium constants for self-association of aromatic molecules.

Analysis of the noncovalent, noncooperative self-association of identical aromatic molecules assumes that the equilibrium self-association constants are either independent of the number of molecules (the EK-model) or change progressively with increasing aggregation (the AK-model). The dependence of the self-association constant on the number of molecules in the aggregate (i.e., the profile of the equilibrium constant) was empirically derived in the AK-model but, in order to provide some physical understanding of the profile, it is proposed that the sources for attenuation of the equilibrium constant are the loss of translational and rotational degrees of freedom, the ordering of molecules in the aggregates and the electrostatic contribution (for charged units). Expressions are derived for the profiles of the equilibrium constants for both neutral and charged molecules. Although the EK-model has been widely used in the analysis of experimental data, it is shown in this work that the derived equilibrium constant, K(EK), depends on the concentration range used and hence, on the experimental method employed. The relationship has also been demonstrated between the equilibrium constant K(EK) and the real dimerization constant, K(D), which shows that the value of K(EK) is always lower than K(D).

Estimation of the protein-ligand interaction energy for model building and validation.

Macromolecular X-ray crystallography is one of the main experimental techniques to visualize protein-ligand interactions. The high complexity of the ligand universe, however, has delayed the development of efficient methods for the automated identification, fitting and validation of ligands in their electron-density clusters. The identification and fitting are primarily based on the density itself and do not take into account the protein environment, which is a step that is only taken during the validation of the proposed binding mode. Here, a new approach, based on the estimation of the major energetic terms of protein-ligand interaction, is introduced for the automated identification of crystallographic ligands in the indicated binding site with ARP/wARP. The applicability of the method to the validation of protein-ligand models from the Protein Data Bank is demonstrated by the detection of models that are `questionable' and the pinpointing of unfavourable interatomic contacts.

A novel computational approach "BP-STOCH" to study ligand binding to finite lattice.

We report a novel computational algorithm "BP-STOCH" to be used for studying single-type ligand binding with biopolymers of finite lengths, such as DNA oligonucleotides or oligopeptides. It is based on an idea to represent any type of ligand-biopolymer complex in a form of binary number, where "0" and "1" bits stand for vacant and engaged monomers of the biopolymer, respectively. Cycling over all binary numbers from the lowest 0 up to the highest 2(N) - 1 means a sequential generating of all possible configurations of vacant/engaged monomers, which, after proper filtering, results in a full set of possible types of complexes in solution between the ligand and the N-site lattice. The principal advantage of BP-STOCH algorithm is the possibility to incorporate into this cycle any conditions on computation of the concentrations and observed experimental parameters of the complexes in solution, and programmatic access to each monomer of the biopolymer within each binding site of every binding configuration. The latter is equivalent to unlimited extension of the basic reaction scheme and allows to use BP-STOCH algorithm as an alternative to conventional computational approaches.

Does the ligand-biopolymer equilibrium binding constant depend on the number of bound ligands?

Conventional methods, such as Scatchard or McGhee-von Hippel analyses, used to treat ligand-biopolymer interactions, indirectly make the assumption that the microscopic binding constant is independent of the number of ligands, i, already bound to the biopolymer. Recent results on the aggregation of aromatic molecules (Beshnova et al., J Chem Phys 2009, 130, 165105) indicated that the equilibrium constant of self-association depends intrinsically on the number of molecules in an aggregate due to loss of translational and rotational degrees of freedom on formation of the complex. The influence of these factors on the equilibrium binding constant for ligand-biopolymer complexation was analyzed in this work. It was shown that under the conditions of binding of "small" molecules, these factors can effectively be ignored and, hence, do not provide any hidden systematic error in such widely-used approaches, such as the Scatchard or McGhee-von Hippel methods for analyzing ligand-biopolymer complexation. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 932-935, 2010.