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Motivated by experiments connecting linker histone (LH) deficiency to lymphoma progression and retinal disorders, we study by mesoscale chromatin modeling how LH density (ρ) induces gradual, as well sudden, changes in chromatin architecture and how the process depends on DNA linker length, LH binding dynamics and binding mode, salt concentration, tail modifications, and combinations of ρ and linker DNA length. We show that ρ tightly regulates the overall shape and compaction of the fiber, triggering a transition from an irregular disordered state to a compact and ordered structure. Such a structural transition, resembling B to A compartment transition connected with lymphoma of B cells, appears to occur around ρ = 0.5. The associated mechanism is DNA stem formation by LH binding, which is optimal when the lengths of the DNA linker and LH C-terminal domain are similar. Chromatin internal and external parameters are key regulators, promoting or impeding the transition. The LH density thus emerges as a critical tunable variable in controlling cellular functions through structural transitions of the genome.

The frameshifting RNA element (FSE) in coronaviruses (CoVs) regulates the programmed −1 ribosomal frameshift (−1 PRF) mechanism common to many viruses. The FSE is of particular interest as a promising drug candidate. Its associated pseudoknot or stem loop structure is thought to play a large role in frameshifting and thus viral protein production. To investigate the FSE structural evolution, we use our graph theory-based methods for representing RNA secondary structures in the RNA-As-Graphs (RAG) framework to calculate conformational landscapes of viral FSEs with increasing sequence lengths for representative 10 Alpha and 13 Beta-CoVs. By following length-dependent conformational changes, we show that FSE sequences encode many possible competing stems which in turn favor certain FSE topologies, including a variety of pseudoknots, stem loops, and junctions. We explain alternative competing stems and topological FSE changes by recurring patterns of mutations. At the same time, FSE topology robustness can be understood by shifted stems within different sequence contexts and base pair coevolution. We further propose that the topology changes reflected by length-dependent conformations contribute to tuning the frameshifting efficiency. Our work provides tools to analyze virus sequence/structure correlations, explains how sequence and FSE structure have evolved for CoVs, and provides insights into potential mutations for therapeutic applications against a broad spectrum of CoV FSEs by targeting key sequence/structural transitions.

The relationship between chromatin architecture and function defines a central problem in biology and medicine. Many computational chromatin models with atomic, coarse-grained, mesoscale, and polymer resolution have been used to shed light onto the mechanisms that dictate genome folding and regulation of gene expression. The associated simulation techniques range from Monte Carlo to molecular, Brownian, and Langevin dynamics. Here, we present an efficient Compute Unified Device Architecture (CUDA) implementation of Brownian dynamics (BD) to simulate chromatin fibers at the nucleosome resolution with our chromatin mesoscale model. With the CUDA implementation for computer architectures with graphic processing units (GPUs), we significantly accelerate compute-intensive hydrodynamic tensor calculations in the BD simulations by massive parallelization, boosting the performance a hundred-fold compared with central processing unit calculations. We validate our BD simulation approach by reproducing experimental trends on fiber diffusion and structure as a function of salt, linker histone binding, and histone-tail composition, as well as Monte Carlo equilibrium sampling results. Our approach proves to be physically accurate with performance that makes feasible the study of chromatin fibers in the range of kb or hundreds of nucleosomes (small gene). Such simulations are essential to advance the study of biological processes such as gene regulation and aberrant genome-structure related diseases.

With the rapid rate of COVID-19 infections and deaths, treatments and cures besides hand washing, social distancing, masks, isolation, and quarantines are urgently needed. The treatments and vaccines rely on the basic biophysics of the complex viral apparatus. Although proteins are serving as main drug and vaccine targets, therapeutic approaches targeting the 30,000 nucleotide RNA viral genome form important complementary approaches. Indeed, the high conservation of the viral genome, its close evolutionary relationship to other viruses, and the rise of gene editing and RNA-based vaccines all argue for a focus on the RNA agent itself. One of the key steps in the viral replication cycle inside host cells is the ribosomal frameshifting required for translation of overlapping open reading frames. The RNA frameshifting element (FSE), one of three highly conserved regions of coronaviruses, is believed to include a pseudoknot considered essential for this ribosomal switching. In this work, we apply our graph-theory-based framework for representing RNA secondary structures, "RAG (or RNA-As-Graphs)," to alter key structural features of the FSE of the SARS-CoV-2 virus. Specifically, using RAG machinery of genetic algorithms for inverse folding adapted for RNA structures with pseudoknots, we computationally predict minimal mutations that destroy a structurally important stem and/or the pseudoknot of the FSE, potentially dismantling the virus against translation of the polyproteins. Our microsecond molecular dynamics simulations of mutant structures indicate relatively stable secondary structures. These findings not only advance our computational design of RNAs containing pseudoknots, they pinpoint key residues of the SARS-CoV-2 virus as targets for antiviral drugs and gene editing approaches.

The life and work of crystallography pioneer Isabella L. Karle is recounted (1921–2017), as researched from the literature and personal stories of colleagues and family. Her story includes her family background, education at the University of Michigan, research on the Manhattan Project, and 63 productive years at the Naval Research Laboratory. Her life-long partnership and scientific collaboration with husband Jerome Karle, 1985 Nobel Prize winner in Chemistry with Herbert Hauptman, is a big part of her story; however, Isabella has also established herself as a crystallographer extraordinaire through her Symbolic Addition Procedure to solve the phase problem, and her unique ability to solve the structures of complex biological molecules, including toxins, antibiotics, and peptides. Her rich family life with three daughters in a lake-front home, do-it-yourself attitude, and passions outside of science round up this portrait of a fascinating and brilliant woman.

With the rapid rate of COVID-19 infections and deaths, treatments and cures besides hand washing, social distancing, masks, isolation, and quarantines are urgently needed. The treatments and vaccines rely on the basic biophysics of the complex viral apparatus. Although proteins are serving as main drug and vaccine targets, therapeutic approaches targeting the 30,000 nucleotide RNA viral genome form important complementary approaches. Indeed, the high conservation of the viral genome, its close evolutionary relationship to other viruses, and the rise of gene editing and RNA-based vaccines all argue for a focus on the RNA agent itself. One of the key steps in the viral replication cycle inside host cells is the ribosomal frameshifting required for translation of overlapping open reading frames. The RNA frameshifting element (FSE), one of three highly conserved regions of coronaviruses, is believed to include a pseudoknot considered essential for this ribosomal switching. In this work, we apply our graph-theory-based framework for representing RNA secondary structures, "RAG (or RNA-As-Graphs)," to alter key structural features of the FSE of the SARS-CoV-2 virus. Specifically, using RAG machinery of genetic algorithms for inverse folding adapted for RNA structures with pseudoknots, we computationally predict minimal mutations that destroy a structurally important stem and/or the pseudoknot of the FSE, potentially dismantling the virus against translation of the polyproteins. Our microsecond molecular dynamics simulations of mutant structures indicate relatively stable secondary structures. These findings not only advance our computational design of RNAs containing pseudoknots, they pinpoint key residues of the SARS-CoV-2 virus as targets for antiviral drugs and gene editing approaches.

Linker histone H1 proteins bind to nucleosomes and facilitate chromatin compaction1, although their biological functions are poorly understood. Mutations in the genes that encode H1 isoforms B–E (H1B, H1C, H1D and H1E; also known as H1-5, H1-2, H1-3 and H1-4, respectively) are highly recurrent in B cell lymphomas, but the pathogenic relevance of these mutations to cancer and the mechanisms that are involved are unknown. Here we show that lymphoma-associated H1 alleles are genetic driver mutations in lymphomas. Disruption of H1 function results in a profound architectural remodelling of the genome, which is characterized by large-scale yet focal shifts of chromatin from a compacted to a relaxed state. This decompaction drives distinct changes in epigenetic states, primarily owing to a gain of histone H3 dimethylation at lysine 36 (H3K36me2) and/or loss of repressive H3 trimethylation at lysine 27 (H3K27me3). These changes unlock the expression of stem cell genes that are normally silenced during early development. In mice, loss of H1c and H1e (also known as H1f2 and H1f4, respectively) conferred germinal centre B cells with enhanced fitness and self-renewal properties, ultimately leading to aggressive lymphomas with an increased repopulating potential. Collectively, our data indicate that H1 proteins are normally required to sequester early developmental genes into architecturally inaccessible genomic compartments. We also establish H1 as a bona fide tumour suppressor and show that mutations in H1 drive malignant transformation primarily through three-dimensional genome reorganization, which leads to epigenetic reprogramming and derepression of developmentally silenced genes. Mutations in histone H1 induce the remodelling of chromatin architecture to a more relaxed state, which leads to malignant transformation through changes in histone modifications and the expression of stem cell genes.

The intricacies of the 3D hierarchical organization of the genome have been approached by many creative modeling studies. The specific model/simulation technique combination defines and restricts the system and phenomena that can be investigated. We present the latest modeling developments and studies of the genome, involving models ranging from nucleosome systems and small polynucleosome arrays to chromatin fibers in the kb-range, chromosomes, and whole genomes, while emphasizing gene folding from first principles. Clever combinations allow the exploration of many interesting phenomena involved in gene regulation, such as nucleosome structure and dynamics, nucleosome-nucleosome stacking, polynucleosome array folding, protein regulation of chromatin architecture, mechanisms of gene folding, loop formation, compartmentalization, and structural transitions at the chromosome and genome levels. Gene-level modeling with full details on nucleosome positions, epigenetic factors, and protein binding, in particular, can in principle be scaled up to model chromosomes and cells to study fundamental biological regulation.

A longstanding hypothesis is that chromatin fiber folding mediated by interactions between nearby nucleosomes represses transcription. However, it has been difficult to determine the relationship between local chromatin fiber compaction and transcription in cells. Further, global changes in fiber diameters have not been observed, even between interphase and mitotic chromosomes. We show that an increase in the range of local inter-nucleosomal contacts in quiescent yeast drives the compaction of chromatin fibers genome-wide. Unlike actively dividing cells, inter-nucleosomal interactions in quiescent cells require a basic patch in the histone H4 tail. This quiescence-specific fiber folding globally represses transcription and inhibits chromatin loop extrusion by condensin. These results reveal that global changes in chromatin fiber compaction can occur during cell state transitions, and establish physiological roles for local chromatin fiber folding in regulating transcription and chromatin domain formation.

The growing interest in the complexity of biological interactions is continuously driving the need to increase system size in biophysical simulations, requiring not only powerful and advanced hardware but adaptable software that can accommodate a large number of atoms interacting through complex forcefields. To address this, we developed and implemented strategies in the GENESIS molecular dynamics package designed for large numbers of processors. Long-range electrostatic interactions were parallelized by minimizing the number of processes involved in communication. A novel algorithm was implemented for nonbonded interactions to increase single instruction multiple data (SIMD) performance, reducing memory usage for ultra large systems. Memory usage for neighbor searches in real-space nonbonded interactions was reduced by approximately 80%, leading to significant speedup. Using experimental data describing physical 3D chromatin interactions, we constructed the first atomistic model of an entire gene locus (GATA4). Taken together, these developments enabled the first billion-atom simulation of an intact biomolecular complex, achieving scaling to 65,000 processes (130,000 processor cores) with 1 ns/day performance. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.

The complex role of linker histone (LH) on chromatin compaction regulation has been highlighted by recent discoveries of the effect of LH binding variability and isoforms on genome structure and function. Here we examine the effect of two LH variants and variable binding modes on the structure of chromatin fibers. Our mesoscale modeling considers oligonucleosomes with H1C and H1E, bound in three different on and off-dyad modes, and spanning different LH densities (0.5–1.6 per nucleosome), over a wide range of physiologically relevant nucleosome repeat lengths (NRLs). Our studies reveal an LH-variant and binding-mode dependent heterogeneous ensemble of fiber structures with variable packing ratios, sedimentation coefficients, and persistence lengths. For maximal compaction, besides dominantly interacting with parental DNA, LHs must have strong interactions with nonparental DNA and promote tail/nonparental core interactions. An off-dyad binding of H1E enables both; others compromise compaction for bendability. We also find that an increase of LH density beyond 1 is best accommodated in chromatosomes with one on-dyad and one off-dyad LH. We suggest that variable LH binding modes and concentrations are advantageous, allowing tunable levels of chromatin condensation and DNA accessibility/interactions. Thus, LHs add another level of epigenetic regulation of chromatin.

Gene expression is orchestrated at the structural level by nucleosome positioning, histone tail acetylation, and linker histone (LH) binding. Here, we integrate available data on nucleosome positioning, nucleosome-free regions (NFRs), acetylation islands, and LH binding sites to “fold” in silico the 55-kb HOXC gene cluster and investigate the role of each feature on the gene’s folding. The gene cluster spontaneously forms a dynamic connection hub, characterized by hierarchical loops which accommodate multiple contacts simultaneously and decrease the average distance between promoters by [Formula: see text] 100 nm. Contact probability matrices exhibit “stripes” near promoter regions, a feature associated with transcriptional regulation. Interestingly, while LH proteins alone decrease long-range contacts and acetylation alone increases transient contacts, combined LH and acetylation produce long-range contacts. Thus, our work emphasizes how chromatin architecture is coordinated strongly by epigenetic factors and opens the way for nucleosome resolution models incorporating epigenetic modifications to understand and predict gene activity.

Chromatin structure, dynamics, and function are being intensely investigated by a variety of methods, including microscopy, X-ray diffraction, nuclear magnetic resonance, biochemical crosslinking, chromosome conformation capture, and computation. A range of experimental techniques combined with modeling is clearly valuable to help interpret experimental data and, importantly, generate configurations and mechanisms related to the 3D organization and function of the genome. Contact maps, in particular, as obtained by a variety of chromosome conformation capture methods, are of increasing interest due to their implications on genome structure and regulation on many levels. In this perspective, using seven examples from our group's studies, we illustrate how molecular modeling can help interpret such experimental data. Specifically, we show how computed contact maps related to experimental systems can be used to explain structures of nucleosomes, chromatin higher-order folding, domain segregation mechanisms, gene organization, and the effect on chromatin structure of external and internal fiber parameters, such as nucleosome positioning, presence of nucleosome free regions, histone posttranslational modifications, and linker histone binding. We argue that such computations on multiple spatial and temporal scales will be increasingly important for the integration of genomic, epigenomic, and biophysical data on chromatin structure and related cellular processes.

The biomolecular modeling field has flourished since its early days in the 1970s due to the rapid adaptation and tailoring of state-of-the-art technology. The resulting dramatic increase in size and timespan of biomolecular simulations has outpaced Moore's law. Here, we discuss the role of knowledge-based versus physics-based methods and hardware versus software advances in propelling the field forward. This rapid adaptation and outreach suggests a bright future for modeling, where theory, experimentation and simulation define three pillars needed to address future scientific and biomedical challenges.

Monte Carlo simulations of a mesoscale model of oligonucleosomes are analyzed to examine the role of dynamic-linker histone (LH) binding/unbinding in high monovalent salt with divalent ions, and to further interpret noted chromatin fiber softening by dynamic LH in monovalent salt conditions. We find that divalent ions produce a fiber stiffening effect that competes with, but does not overshadow, the dramatic softening triggered by dynamic-LH behavior. Indeed, we find that in typical in vivo conditions, dynamic-LH binding/unbinding reduces fiber stiffening dramatically (by a factor of almost 5, as measured by the elasticity modulus) compared with rigidly fixed LH, and also the force needed to initiate chromatin unfolding, making it consistent with those of molecular motors. Our data also show that, during unfolding, divalent ions together with LHs induce linker-DNA bending and DNA-DNA repulsion screening, which guarantee formation of heteromorphic superbeads-on-a-string structures that combine regions of loose and compact fiber independently of the characteristics of the LH-core bond. These structures might be important for gene regulation as they expose regions of the DNA selectively. Dynamic control of LH binding/unbinding, either globally or locally, in the presence of divalent ions, might constitute a mechanism for regulation of gene expression.

The basic and intrinsically disordered C-terminal domain (CTD) of the linker histone (LH) is essential for chromatin compaction. However, its conformation upon nucleosome binding and its impact on chromatin organization remain unknown. Our mesoscale chromatin model with a flexible LH CTD captures a dynamic, salt-dependent condensation mechanism driven by charge neutralization between the LH and linker DNA. Namely, at low salt concentration, CTD condenses, but LH only interacts with the nucleosome and one linker DNA, resulting in a semi-open nucleosome configuration; at higher salt, LH interacts with the nucleosome and two linker DNAs, promoting stem formation and chromatin compaction. CTD charge reduction unfolds the domain and decondenses chromatin, a mechanism in consonance with reduced counterion screening in vitro and phosphorylated LH in vivo. Divalent ions counteract this decondensation effect by maintaining nucleosome stems and expelling the CTDs to the fiber exterior. Additionally, we explain that the CTD folding depends on the chromatin fiber size, and we show that the asymmetric structure of the LH globular head is responsible for the uneven interaction observed between the LH and the linker DNAs. All these mechanisms may impact epigenetic regulation and higher levels of chromatin folding.

We reassess progress in the field of biomolecular modeling and simulation, following up on our perspective published in 2011. By reviewing metrics for the field's productivity and providing examples of success, we underscore the productive phase of the field, whose short-term expectations were overestimated and long-term effects underestimated. Such successes include prediction of structures and mechanisms; generation of new insights into biomolecular activity; and thriving collaborations between modeling and experimentation, including experiments driven by modeling. We also discuss the impact of field exercises and web games on the field's progress. Overall, we note tremendous success by the biomolecular modeling community in utilization of computer power; improvement in force fields; and development and application of new algorithms, notably machine learning and artificial intelligence. The combined advances are enhancing the accuracy andscope of modeling and simulation, establishing an exemplary discipline where experiment and theory or simulations are full partners.

Novel RNA motif design is of great practical importance for technology and medicine. Increasingly, computational design plays an important role in such efforts. Our coarse-grained RAG (RNA-As-Graphs) framework offers strategies for enumerating the universe of RNA 2D folds, selecting “RNA-like” candidates for design, and determining sequences that fold onto these candidates. In RAG, RNA secondary structures are represented as tree or dual graphs. Graphs with known RNA structures are called “existing”, and the others are labeled “hypothetical”. By using simplified features for RNA graphs, we have clustered the hypothetical graphs into “RNA-like” and “non RNA-like” groups, and proposed RNA-like graphs as candidates for design. Here, we propose a new way of designing graph features by using Fiedler vectors. The new features reflect graph shapes better, and they lead to a more clustered organization of existing graphs. We show significant increases in K-means clustering accuracy by using the new features (e.g., up to 95% and 98% accuracy for tree and dual graphs, respectively). In addition, we propose a scoring model for top graph candidate selection. This scoring model allows users to set a threshold for candidates, and it incorporates weighing of existing graphs based on their corresponding number of known RNAs. We include a list of top scored RNA-like candidates, which we hope will stimulate future novel RNA design.

SUMMARY Nucleosomes form heterogeneous groups in vivo, named clutches. Clutches are smaller and less dense in mouse embryonic stem cells (ESCs) compared to neural progenitor cells (NPCs). Using coarse-grained modeling of the pluripotency Pou5f1 gene, we show that the genome-wide clutch differences between ESCs and NPCs can be reproduced at a single gene locus. Larger clutch formation in NPCs is associated with changes in the compaction and internucleosome contact probability of the Pou5f1 fiber. Using single-molecule tracking (SMT), we further show that the core histone protein H2B is dynamic, and its local mobility relates to the structural features of the chromatin fiber. H2B is less stable and explores larger areas in ESCs compared to NPCs. The amount of linker histone H1 critically affects local H2B dynamics. Our results have important implications for how nucleosome organization and H2B dynamics contribute to regulate gene activity and cell identity., Graphical Abstract, In Brief Gómez-García et al. show that the Pou5f1 gene folds into nucleosome clutches, with larger clutches in differentiated cells than in stem cells. These clutch changes are accompanied by enhanced hierarchical looping in differentiated cells. H2B dynamics is cell-type specific, correlates with clutch patterns, and is regulated by linker histone H1.

Determining the conformation of chromatin in cells at the nucleosome level and its relationship to cellular processes has been a central challenge in biology. We show that in quiescent yeast, widespread transcriptional repression coincides with the local compaction of chromatin fibers into structures that are less condensed and more heteromorphic than canonical 30-nanometer forms. Acetylation or substitution of H4 tail residues decompacts fibers and leads to global transcriptional de-repression. Fiber decompaction also increases the rate of loop extrusion by condensin. These findings establish a role for H4 tail-dependent local chromatin fiber folding in regulating transcription and loop extrusion in cells. They also demonstrate the physiological relevance of canonical chromatin fiber folding mechanisms even in the absence of regular 30-nanometer structures.

With the rapid rate of Covid-19 infections and deaths, treatments and cures besides hand washing, social distancing, masks, isolation, and quarantines are urgently needed. The treatments and vaccines rely on the basic biophysics of the complex viral apparatus. While proteins are serving as main drug and vaccine targets, therapeutic approaches targeting the 30,000 nucleotide RNA viral genome form important complementary approaches. Indeed, the high conservation of the viral genome, its close evolutionary relationship to other viruses, and the rise of gene editing and RNA-based vaccines all argue for a focus on the RNA agent itself. One of the key steps in the viral replication cycle inside host cells is the ribosomal frameshifting required for translation of overlapping open reading frames. The frameshifting element (FSE), one of three highly conserved regions of coronaviruses, includes an RNA pseudoknot considered essential for this ribosomal switching. In this work, we apply our graph-theory-based framework for representing RNA secondary structures, “RAG” (RNA-As Graphs), to alter key structural features of the FSE of the SARS-CoV-2 virus. Specifically, using RAG machinery of genetic algorithms for inverse folding adapted for RNA structures with pseudoknots, we computationally predict minimal mutations that destroy a structurally-important stem and/or the pseudoknot of the FSE, potentially dismantling the virus against translation of the polyproteins. Additionally, our microsecond molecular dynamics simulations of mutant structures indicate relatively stable secondary structures. These findings not only advance our computational design of RNAs containing pseudoknots; they pinpoint to key residues of the SARS-CoV-2 virus as targets for anti-viral drugs and gene editing approaches.SIGNIFICANCESince the outbreak of Covid-19, numerous projects were launched to discover drugs and vaccines. Compared to protein-focused approaches, targeting the RNA genome, especially highly conserved crucial regions, can destruct the virus life cycle more fundamentally and avoid problems of viral mutations. We choose to target the small frame-shifting element (FSE) embedded in the Open Reading Frame 1a,b of SARS-CoV-2. This FSE is essential for translating overlapping reading frames and thus controlling the viral protein synthesis pathway. By applying graph-theory-based computational algorithms, we identify structurally crucial residues in the FSE as potential targets for anti-viral drugs and gene editing.

We write to introduce our novel group formed to confront some of the issues raised by the COVID-19 pandemic. Information about the group, which we named "cure COVid for Ever and for All" (RxCOVEA), its dynamic membership (changing regularly), and some of its activities-described in more technical detail for expert perusal and commentary-are available upon request.

Nucleosomes cluster together when chromatin folds in the cell to form heterogeneous groups termed "clutches". These structural units add another level of chromatin regulation, for example during cell differentiation. Yet, the mechanisms that regulate their size and compaction remain obscure. Here, using our chromatin mesoscale model, we dissect clutch patterns in fibers with different combinations of nucleosome positions, linker histone density, and acetylation levels to investigate their role in clutch regulation. First, we isolate the effect of each chromatin parameter by studying systems with regular nucleosome spacing; second, we design systems with naturally-occurring linker lengths that fold onto specific clutch patterns; third, we model gene-encoding fibers to understand how these combined factors contribute to gene structure. Our results show how these chromatin parameters act together to produce different-sized nucleosome clutches. The length of nucleosome free regions (NFRs) profoundly affects clutch size, while the length of linker DNA has a moderate effect. In general, higher linker histone densities produce larger clutches by a chromatin compaction mechanism, while higher acetylation levels produce smaller clutches by a chromatin unfolding mechanism. We also show that it is possible to design fibers with naturally-occurring DNA linkers and NFRs that fold onto specific clutch patterns. Finally, in gene-encoding systems, a complex combination of variables dictates a gene-specific clutch pattern. Together, these results shed light into the mechanisms that regulate nucleosome clutches and suggest a new epigenetic mechanism by which chromatin parameters regulate transcriptional activity via the three-dimensional folded state of the genome at a nucleosome level.

Protein flexibility and disorder is emerging as a crucial modulator of chromatin structure. Histone tail disorder enables transient binding of different molecules to the nucleosomes, thereby promoting heterogeneous and dynamic internucleosome interactions and making possible recruitment of a wide-range of regulatory and remodeling proteins. On the basis of extensive multiscale modeling we reveal the importance of linker histone H1 protein disorder for chromatin hierarchical looping. Our multiscale approach bridges microsecond-long bias-exchange metadynamics molecular dynamics simulations of atomistic 211-bp nucleosomes with coarse-grained Monte Carlo simulations of 100-nucleosome systems. We show that the long C-terminal domain (CTD) of H1—a ubiquitous nucleosome-binding protein—remains disordered when bound to the nucleosome. Notably, such CTD disorder leads to an asymmetric and dynamical nucleosome conformation that promotes chromatin structural flexibility and establishes long-range hierarchical loops. Furthermore, the degree of condensation and flexibility of H1 can be fine-tuned, explaining chromosomal differences of interphase versus metaphase states that correspond to partial and hyperphosphorylated H1, respectively. This important role of H1 protein disorder in large-scale chromatin organization has a wide range of biological implications.

RNA's modular, hierarchical and versatile structure makes possible diverse, essential regulatory and catalytic roles in the cell. It also invites systematic modeling and simulation approaches. Among the diverse computational and theoretical approaches to model RNA structures, graph theory has been applied in various contexts to study RNA structure and function. I will present an overview of recent graph theoretical approaches for predicting and designing RNA topologies using graphical representations of RNA secondary structure, data-mining tools for junction topology prediction, and hierarchical sampling of graphs based on statistical potentials. As evident from the work of many groups in the mathematical and biological sciences, graph theoretical approaches offer a fruitful avenue for designing novel RNA topologies and predicting tertiary structures from given secondary structures.Of possible interest- H.H. Gan, S. Pasquali and T. Schlick, Nucl. Acids Res. 31:2926 (2003)- N. Kim et al., J. Mol. Biol. 341:1129 (2004)- G. Quarta and K. Sin and T. Schlick, PLoS Comput. Biol. 8: e1002368 (2012).- C. Laing, S. Jung, N. Kim, S. Elmetwaly, M. Zharan, and T. Schlick, PLOS One 8(8): e71947 (2013).- N. Kim, C. Laing, S. Elmetwaly, S. Jung, J. Curuksu, and T. Schlick, Proc. Natl. Acad. Sci. USA 111: 4079 (2014).- M. Zharan, C. S. Bayrak, S. Elmetwaly, and T. Schlick, Nuc. Acids Res. 43: 9474 (2015).- N. Baba, S. Elmetwaly, N. Kim, and T. Schlick, J. Mol. Biol. 428: 811 (2016).- L. Hua, Y. Song, N. Kim, C. Laing, J. T. L. Wang, and T. Schlick, PlOS One 11: e0147097 (2016).