Affinity, stoichiometry and cooperativity of heterochromatin protein 1 (HP1) binding to nucleosomal arrays

Heterochromatin protein 1 (HP1) participates in establishing and maintaining heterochromatin via its histone-modification-dependent chromatin interactions. In recent papers HP1 binding to nucleosomal arrays was measured in vitro and interpreted in terms of nearest-neighbour cooperative binding. This mode of chromatin interaction could lead to the spreading of HP1 along the nucleosome chain. Here, we reanalysed previous data by representing the nucleosome chain as a 1D binding lattice and showed how the experimental HP1 binding isotherms can be explained by a simpler model without cooperative interactions between neighboring HP1 dimers. Based on these calculations and spatial models of dinucleosomes and nucleosome chains, we propose that binding stoichiometry depends on the nucleosome repeat length (NRL) rather than protein interactions between HP1 dimers. According to our calculations, more open nucleosome arrays with long DNA linkers are characterized by a larger number of binding sites in comparison to chains with a short NRL. Furthermore, we demonstrate by Monte Carlo simulations that the NRL dependent folding of the nucleosome chain can induce allosteric changes of HP1 binding sites. Thus, HP1 chromatin interactions can be modulated by the change of binding stoichiometry and the type of binding to condensed (methylated) and non-condensed (unmethylated) nucleosome arrays in the absence of direct interactions between HP1 dimers

Using Energy Landscape Theory to Uncover the Organization of Conformational Space of Proteins in Their Native States.

The functional motions of proteins navigate on rugged energy landscapes. Hence, mapping of these multidimensional landscapes into lower dimensional manifolds is imperative for gaining deeper insights into the functional dynamics. In the present work we implement novel computational schemes and means of analysis to characterize the topography of conformational space of selected proteins and also to elucidate their functional implications. The present thesis is divided into two parts, where we focus on the case studies of the intrinsically disordered histone tails and the representative allosteric protein Adenlyate Kinase. In particular, analyzing the energy landscapes of histone tails, we find preferential clustering of transient secondary structural elements in the conformational ensembles, which have a dramatic impact on the chain statistics, conformational dynamics and the binding pathways. In the study of Adenylate Kinase we use a novel nonlinear order parameter to rigorously estimate the free energy difference between allosteric states and map out the plausible pathway of transition, which reveals important structural and thermodynamic insights about the mechanism of allostery in Adenylate Kinase. Taken together our findings indicate that the organization of conformational space of functional proteins is delicately crafted to ensure efficient functional regulation and robust response to external signals

A flexible integrative approach based on random forest improves prediction of transcription factor binding sites

Transcription factor binding sites (TFBSs) are DNA sequences of 6-15 base pairs. Interaction of these TFBSs with transcription factors (TFs) is largely responsible for most spatiotemporal gene expression patterns. Here, we evaluate to what extent sequence-based prediction of TFBSs can be improved by taking into account the positional dependencies of nucleotides (NPDs) and the nucleotide sequence-dependent structure of DNA. We make use of the random forest algorithm to flexibly exploit both types of information. Results in this study show that both the structural method and the NPD method can be valuable for the prediction of TFBSs. Moreover, their predictive values seem to be complementary, even to the widely used position weight matrix (PWM) method. This led us to combine all three methods. Results obtained for five eukaryotic TFs with different DNA-binding domains show that our method improves classification accuracy for all five eukaryotic TFs compared with other approaches. Additionally, we contrast the results of seven smaller prokaryotic sets with high-quality data and show that with the use of high-quality data we can significantly improve prediction performance. Models developed in this study can be of great use for gaining insight into the mechanisms of TF binding

Monte Carlo, harmonic approximation, and coarse-graining approaches for enhanced sampling of biomolecular structure

The rugged energy landscape of biomolecules and associated large-scale conformational changes have triggered the development of many innovative enhanced sampling methods, either based or not based on molecular dynamics (MD) simulations. Surveyed here are methods in the latter class - including Monte Carlo methods, harmonic approximations, and coarse graining - many of which yield valuable conformational insights into biomolecular structure and flexibility, despite altered kinetics. MD-based methods are surveyed in an upcoming issue of F1000 Biology Reports

Intrinsic flexibility of B-DNA: the experimental TRX scale

B-DNA flexibility, crucial for DNA–protein recognition, is sequence dependent. Free DNA in solution would in principle be the best reference state to uncover the relation between base sequences and their intrinsic flexibility; however, this has long been hampered by a lack of suitable experimental data. We investigated this relationship by compiling and analyzing a large dataset of NMR 31P chemical shifts in solution. These measurements reflect the BI ↔ BII equilibrium in DNA, intimately correlated to helicoidal descriptors of the curvature, winding and groove dimensions. Comparing the ten complementary DNA dinucleotide steps indicates that some steps are much more flexible than others. This malleability is primarily controlled at the dinucleotide level, modulated by the tetranucleotide environment. Our analyses provide an experimental scale called TRX that quantifies the intrinsic flexibility of the ten dinucleotide steps in terms of Twist, Roll, and X-disp (base pair displacement). Applying the TRX scale to DNA sequences optimized for nucleosome formation reveals a 10 base-pair periodic alternation of stiff and flexible regions. Thus, DNA flexibility captured by the TRX scale is relevant to nucleosome formation, suggesting that this scale may be of general interest to better understand protein-DNA recognition

MiOS, an integrated imaging and computational strategy to model gene folding with nucleosome resolution

The linear sequence of DNA provides invaluable information about genes and their regulatory elements along chromosomes. However, to fully understand gene function and regulation, we need to dissect how genes physically fold in the three-dimensional nuclear space. Here we describe immuno-OligoSTORM, an imaging strategy that reveals the distribution of nucleosomes within specific genes in super-resolution, through the simultaneous visualization of DNA and histones. We combine immuno-OligoSTORM with restraint-based and coarse-grained modeling approaches to integrate super-resolution imaging data with Hi-C contact frequencies and deconvoluted micrococcal nuclease-sequencing information. The resulting method, called Modeling immuno-OligoSTORM, allows quantitative modeling of genes with nucleosome resolution and provides information about chromatin accessibility for regulatory factors, such as RNA polymerase II. With Modeling immuno-OligoSTORM, we explore intercellular variability, transcriptional-dependent gene conformation, and folding of housekeeping and pluripotency-related genes in human pluripotent and differentiated cells, thereby obtaining the highest degree of data integration achieved so far to our knowledge

Specific DNA structural attributes modulate platinum anticancer drug site selection and cross-link generation

Heavy metal compounds have toxic and medicinal potential through capacity to form strong specific bonds with macromolecules, and the interaction of platinum drugs at the major groove nitrogen atom of guanine bases primarily underlies their therapeutic activity. By crystallographic analysis of transition metal-and in particular platinum compound-DNA site selectivity in the nucleosome core, we establish that steric accessibility, which is controlled by specific structural parameters of the double helix, modulates initial guanine-metal bond formation. Moreover, DNA conformational features can be linked to both similarities and distinctions in platinum drug adduct formation between the naked and nucleosomal DNA states. Notably, structures that facilitate initial platinum-guanine bond formation can oppose cross-link generation, rationalizing the occurrence of long-lived therapeutically ineffective monofunctional adducts. These findings illuminate DNA structure-dependent reactivity and provide a novel framework for understanding metal-double helix interactions, which should facilitate the development of improved chromatin-targeting medicinal agent