Dynamic Coupling among Protein Binding, Sliding, and DNA Bending Revealed by Molecular Dynamics

Influence of DNA Sequences on the Thermodynamic and Structural Stability of the ZTA Transcription Factor─DNA Complex: An All-Atom Molecular Dynamics Study

The Epstein-Barr virus (EBV) is one of the cancer-causing gamma-type viruses. Although more than 90% of people are infected by this virus at some point, it remains in the body in a latent state, typically causing only minor symptoms. Our current understanding is that a known transcription factor (TF), the ZTA protein, binds with dsDNA (double-stranded DNA) and plays a crucial role in mediating the viral latent-to-lytic cycle through binding of specific ZTA-responsive elements (ZREs). However, there is no clear understanding of the effect of DNA sequences on the structural stability and quantitative estimation of the binding affinity between ZTA TF and DNA, along with their mechanistic details. In this study, we employed classical all-atom molecular dynamics and enhanced sampling simulations to study the ZTA-dsDNA structural properties, thermodynamics, and mechanistic details for the ZTA protein and for two different dsDNA systems: the core motif and the core motif with flanking end sequences. We conducted residue-level and nucleic acid-level analyses to assess the important protein residues and DNA bases forming interactions between the ZTA and dsDNA systems. We also explored the effect of adding flanking end sequences to the core motif on DNA groove lengths and interstrand hydrogen bonds. Our results indicate that the flanking sequences surrounding the core motif significantly influence the structural stability and binding affinity of the ZTA-dsDNA complex. Among ZRE 1, ZRE 2, and ZRE 3, particularly when paired with their naturally occurring flanking ends, ZRE 3 exhibits higher stability and binding affinity. These findings provide insights into the molecular mechanisms underlying EBV pathogenesis and may indicate potential targets for therapeutic intervention. A detailed explanation of the binding mechanisms will allow for the design of better-targeted therapies against EBV-associated cancers. This study will serve as a holistic benchmark for future studies of these viral protein interactions.

Heterogeneous condensates of transcription factors in embryonic stem cells: Molecular simulations

Biomolecular condensates formed via liquid-liquid phase separation are ubiquitous in cells, especially in the nucleus. While condensates containing one or two kinds of biomolecules have been relatively well characterized, those with more heterogeneous biomolecular components and interactions between biomolecules inside are largely unknown. This study used residue-resolution molecular dynamics simulations to investigate heterogeneous protein assemblies that include four master transcription factors in mammalian embryonic stem cells: Oct4, Sox2, Klf4, and Nanog. Molecular dynamics simulations of the mixture systems showed highly heterogeneous and dynamic behaviors; protein condensates mainly contain Sox2, Klf4, and Nanog, while most Oct4 are dissolved into the dilute phase. The condensate forms loosely interacting clusters where Klf4 is the most abundant, suggesting that Klf4 serves as a scaffold of the condensate, and Sox2 and Nanog are bound to Klf4 for stabilizing the condensate. Oct4 is moderately recruited to the condensate, serving as a client mainly via its interaction with Sox2. This study highlights the importance of intermolecular interaction between different transcription factors on the condensate formations with heterogeneous biomolecular components.

FlowBack: A Generalized Flow-Matching Approach for Biomolecular Backmapping

Coarse-grained models have become ubiquitous in biomolecular modeling tasks aimed at studying slow dynamical processes such as protein folding and DNA hybridization. These models can considerably accelerate sampling but it remains challenging to accurately and efficiently restore all-atom detail to the coarse-grained trajectory, which can be vital for detailed understanding of molecular mechanisms and calculation of observables contingent on all-atom coordinates. In this work, we introduce FlowBack as a deep generative model employing a flow-matching objective to map samples from a coarse-grained prior distribution to an all-atom data distribution. We construct our prior distribution to be agnostic to the coarse-grained map and molecular type. A protein-specific model trained on ∼65k structures from the Protein Data Bank achieves state-of-the-art performance on structural metrics compared to previous generative and rules-based approaches in applications to static PDB structures, all-atom simulations of fast-folding proteins, and coarse-grained trajectories generated by a machine-learned force field. A DNA-protein model trained on ∼1.5k DNA-protein complexes achieves excellent reconstruction and generative capabilities on static DNA-protein complexes from the Protein Data Bank as well as on out-of-distribution coarse-grained dynamical simulations of DNA-protein complexation. FlowBack offers an accurate, efficient, and easy-to-use tool to recover all-atom structures from coarse-grained molecular simulations with higher robustness and fewer steric clashes than previous approaches. We make FlowBack freely available to the community as an open source Python package.

Deciphering the molecular mechanism underlying morphology transition in two-component DNA-protein cophase separation

Nucleic acid and protein co-condensates exhibit diverse morphologies crucial for fundamental cellular processes. Despite many previous studies that advanced our understanding of this topic, several interesting biophysical questions regarding the underlying molecular mechanisms remain. We investigated DNA and human transcription factor p53 co-condensates-a scenario where neither dsDNA nor the protein demonstrates phase-separation behavior individually. Through a combination of experimental assays and theoretical approaches, we elucidated: (1) the phase diagram of DNA-protein co-condensates at a certain observation time, identifying a phase transition between viscoelastic fluid and viscoelastic solid states, and a morphology transition from droplet-like to "pearl chain"-like co-condensates; (2) the growth dynamics of co-condensates. Droplet-like and "pearl chain"-like co-condensates share a common initial critical microscopic cluster size at the nanometer scale during the early stage of phase separation. These findings provide important insights into the biophysical mechanisms underlying multi-component phase separation within cellular environments.

Molecular mechanism of parental H3/H4 recycling at a replication fork

In chromatin replication, faithful recycling of histones from parental DNA to replicated strands is essential for maintaining epigenetic information across generations. A previous experiment has revealed that disrupting interactions between the N-terminal tail of Mcm2, a subunit in DNA replication machinery, and a histone H3/H4 tetramer perturb the recycling. However, the molecular pathways and the factors that regulate the ratio recycled to each strand and the destination location are yet to be revealed. Here, we performed molecular dynamics simulations of yeast DNA replication machinery, an H3/H4 tetramer, and replicated DNA strands. The simulations demonstrated that histones are recycled via Cdc45-mediated and unmediated pathways without histone chaperones, as our in vitro biochemical assays supported. Also, RPA binding regulated the ratio recycled to each strand, whereas DNA bending by Pol ε modulated the destination location. Together, the simulations provided testable hypotheses, which are vital for elucidating the molecular mechanisms of histone recycling.

Nick Induced Dynamics in Supercoiled DNA Facilitates the Protein Target Search Process

A DNA nick, defined as a discontinuity in a double-stranded DNA molecule where the phosphodiester bond between adjacent nucleotides of one strand is absent due to enzyme action, serves as an effective mechanism to alleviate stress in supercoiled DNA. This stress release is essential for the smooth operation of transcriptional machinery. However, the underlying mechanisms and their impact on protein search dynamics, which are crucial for initiating transcription, remain unclear. Through extensive computer simulations, we unravel the molecular picture, demonstrating that intramolecular stress release due to a DNA nick is driven by a combination of writhing and twisting motions, depending on the nick's position. This stress release is quantitatively manifested as a step-like increase in the linking number. Furthermore, we elucidate that the nicked supercoiled minicircles exhibit enhanced torsional dynamics, promoting rapid conformational changes and frequent shifts in the identities of juxtaposed DNA sites on the plectoneme. The dynamics of the juxtaposition sites facilitates communication between protein and DNA, resulting in faster protein diffusion compared with native DNA with the same topology. Our findings highlight the mechanistic intricacies and underscore the importance of DNA nicks in facilitating transcription elongation by actively managing torsional stress during DNA unwinding by the RNA polymerase.

Role of Shape Deformation of DNA-Binding Sites in Regulating the Efficiency and Specificity in Their Recognition by DNA-Binding Proteins

Accurate transcription of genetic information is crucial, involving precise recognition of the binding motifs by DNA-binding proteins. While some proteins rely on short-range hydrophobic and hydrogen bonding interactions at binding sites, others employ a DNA shape readout mechanism for specific recognition. In this mechanism, variations in DNA shape at the binding motif resulted from either inherent flexibility or binding of proteins at adjacent sites are sensed and capitalized by the searching proteins to locate them specifically. Through extensive computer simulations, we investigate both scenarios to uncover the underlying mechanism and origin of specificity in the DNA shape readout mechanism. Our findings reveal that deformation in shape at the binding motif creates an entropy funnel, allowing information about altered shapes to manifest as fluctuations in minor groove widths. This signal enhances the efficiency of nonspecific search of nearby proteins by directing their movement toward the binding site, primarily driven by a gain in entropy. We propose this as a generic mechanism for DNA shape readout, where specificity arises from the alignment between the molecular frustration of the searching protein and the ruggedness of the entropic funnel governed by molecular features of the protein and arrangement of the DNA bases at the binding site, respectively.

Skipping events impose repeated binding attempts: profound kinetic implications of protein-DNA conformational changes

The kinetics of protein-DNA recognition, along with its thermodynamic properties, including affinity and specificity, play a central role in shaping biological function. Protein-DNA recognition kinetics are characterized by two key elements: the time taken to locate the target site amid various nonspecific alternatives; and the kinetics involved in the recognition process, which may necessitate overcoming an energetic barrier. In this study, we developed a coarse-grained (CG) model to investigate interactions between a transcription factor called the sex-determining region Y (SRY) protein and DNA, in order to probe how DNA conformational changes affect SRY-DNA recognition and binding kinetics. We find that, not only does a requirement for such a conformational DNA transition correspond to a higher energetic barrier for binding and therefore slower kinetics, it may further impede the recognition kinetics by increasing unsuccessful binding events (skipping events) where the protein partially binds its DNA target site but fails to form the specific protein-DNA complex. Such skipping events impose the need for additional cycles protein search of nonspecific DNA sites, thus significantly extending the overall recognition time. Our results highlight a trade-off between the speed with which the protein scans nonspecific DNA and the rate at which the protein recognizes its specific target site. Finally, we examine molecular approaches potentially adopted by natural systems to enhance protein-DNA recognition despite its intrinsically slow kinetics.

GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models

GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.

GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. These schemes are applied to the dynamics of intrinsically disordered protein (IDP) droplets. During the fusion of two droplets, we find that the changes in droplet shape correlate with the mixing of IDP chains. Additionally, we simulate large systems with multiple IDP droplets, achieving simulation sizes comparable to those observed in microscopy. In our MD simulations, we directly observe Ostwald ripening, a phenomenon where small droplets dissolve and their molecules redeposit into larger droplets. These methods have been implemented in CGDYN of the GENESIS software, offering a tool for investigating mesoscopic biological processes using the residue-level CG models.

Three-State Diffusion Model of DNA Glycosylase Translocation along Stretched DNA as Revealed by Free Energy Landscapes at the All-Atom Level

DNA glycosylases play key roles in the maintenance of genomic integrity. These enzymes effectively find rare damaged sites in DNA and participate in subsequent base excision repair. Single-molecule and ensemble experiments have revealed key aspects of this damage-site searching mechanism and the involvement of facilitated diffusion. In this study, we describe free energy landscapes of enzyme translocation along nonspecific DNA obtained using a fully atomistic molecular dynamics (MD) simulation of a well-known DNA glycosylase, human 8-oxoguanine DNA glycosylase 1 (hOGG1). Based on an analysis of simulated free energy profiles, we propose a three-state model for the damage-site searching mechanism. In the three states, named the L1, L2, and L3 states, the L1 state is a helical sliding mode in close contact with DNA, whereas the L2 state is a major- or minor-groove tracking mode in loose contact with DNA and the L3 state is a two-dimensional freely diffusing mode during which hOGG1 is somewhat removed from the DNA surface (∼24 Å away from the surface). This three-state model well describes key experimental findings obtained from single-molecule and ensemble experiments and provides a unified molecular picture of the DNA lesion-searching mechanism of hOGG1.

Brewing COFFEE: A Sequence-Specific Coarse-Grained Energy Function for Simulations of DNA-Protein Complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription and gene expression to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse-grained Force Field for Energy Estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the self-organized polymer model with side-chains for proteins and the three interaction site model for DNA in a modular fashion, without recalibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a data set of high-resolution crystal structures. The only parameter in COFFEE is the strength (λDNAPRO) of the DNA-protein contact potential. For an optimal choice of λDNAPRO, the crystallographic B-factors for DNA-protein complexes with varying sizes and topologies are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts scattering profiles that are in quantitative agreement with small-angle X-ray scattering experiments, as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which do not alter the balance of electrostatic interactions but affect chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Dynamic action of an intrinsically disordered protein in DNA compaction that induces mycobacterial dormancy

Mycobacteria are the major human pathogens with the capacity to become dormant persisters. Mycobacterial DNA-binding protein 1 (MDP1), an abundant histone-like protein in dormant mycobacteria, induces dormancy phenotypes, e.g. chromosome compaction and growth suppression. For these functions, the polycationic intrinsically disordered region (IDR) is essential. However, the disordered property of IDR stands in the way of clarifying the molecular mechanism. Here we clarified the molecular and structural mechanism of DNA compaction by MDP1. Using high-speed atomic force microscopy, we observed that monomeric MDP1 bundles two adjacent DNA duplexes side-by-side via IDR. Combined with coarse-grained molecular dynamics simulation, we revealed the novel dynamic DNA cross-linking model of MDP1 in which a stretched IDR cross-links two DNA duplexes like double-sided tape. IDR is able to hijack HU function, resulting in the induction of strong mycobacterial growth arrest. This IDR-mediated reversible DNA cross-linking is a reasonable model for MDP1 suppression of the genomic function in the resuscitable non-replicating dormant mycobacteria.

Nonspecific vs. specific DNA binding free energetics of a transcription factor domain protein

Transcription factor (TF) proteins regulate gene expression by binding to specific sites on the genome. In the facilitated diffusion model, an optimized search process is achieved by the TF alternating between 3D diffusion in the bulk and 1D diffusion along DNA. While undergoing 1D diffusion, the protein can switch from a search mode for fast diffusion along nonspecific DNA to a recognition mode for stable binding to specific DNA. It was recently noticed that, for a small TF domain protein, reorientations on DNA happen between the nonspecific and specific DNA binding. We here conducted all-atom molecular dynamics simulations with steering forces to reveal the protein-DNA binding free energetics, confirming that the search and recognition modes are distinguished primarily by protein orientations on the DNA. As the binding free energy difference between the specific and nonspecific DNA system slightly deviates from that being estimated directly from dissociation constants on 15-bp DNA constructs, we hypothesize that the discrepancy can come from DNA sequences flanking the 6-bp central binding sites that impact on the dissociation kinetics measurements. The hypothesis is supported by a simplified spherical protein-DNA model along with stochastic simulations and kinetic modeling.

OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates

Biomolecular condensates are important structures in various cellular processes but are challenging to study using traditional experimental techniques. In silico simulations with residue-level coarse-grained models strike a balance between computational efficiency and chemical accuracy. They could offer valuable insights by connecting the emergent properties of these complex systems with molecular sequences. However, existing coarse-grained models often lack easy-to-follow tutorials and are implemented in software that is not optimal for condensate simulations. To address these issues, we introduce OpenABC, a software package that greatly simplifies the setup and execution of coarse-grained condensate simulations with multiple force fields using Python scripting. OpenABC seamlessly integrates with the OpenMM molecular dynamics engine, enabling efficient simulations with performance on a single GPU that rivals the speed achieved by hundreds of CPUs. We also provide tools that convert coarse-grained configurations to all-atom structures for atomistic simulations. We anticipate that OpenABC will significantly facilitate the adoption of in silico simulations by a broader community to investigate the structural and dynamical properties of condensates.

Brewing COFFEE: A sequence-specific coarse-grained energy function for simulations of DNA-protein complexes

DNA-protein interactions are pervasive in a number of biophysical processes ranging from transcription, gene expression, to chromosome folding. To describe the structural and dynamic properties underlying these processes accurately, it is important to create transferable computational models. Toward this end, we introduce Coarse grained force field for energy estimation, COFFEE, a robust framework for simulating DNA-protein complexes. To brew COFFEE, we integrated the energy function in the Self-Organized Polymer model with Side Chains for proteins and the Three Interaction Site model for DNA in a modular fashion, without re-calibrating any of the parameters in the original force-fields. A unique feature of COFFEE is that it describes sequence-specific DNA-protein interactions using a statistical potential (SP) derived from a dataset of high-resolution crystal structures. The only parameter in COFFEE is the strength (λ D N A P R O ) of the DNA-protein contact potential. For an optimal choice of λ D N A P R O , the crystallographic B-factors for DNA-protein complexes, with varying sizes and topologies, are quantitatively reproduced. Without any further readjustments to the force-field parameters, COFFEE predicts the scattering profiles that are in quantitative agreement with SAXS experiments as well as chemical shifts that are consistent with NMR. We also show that COFFEE accurately describes the salt-induced unraveling of nucleosomes. Strikingly, our nucleosome simulations explain the destabilization effect of ARG to LYS mutations, which does not alter the balance of electrostatic interactions, but affects chemical interactions in subtle ways. The range of applications attests to the transferability of COFFEE, and we anticipate that it would be a promising framework for simulating DNA-protein complexes at the molecular length-scale.

Micelle-like clusters in phase-separated Nanog condensates: A molecular simulation study

The phase separation model for transcription suggests that transcription factors (TFs), coactivators, and RNA polymerases form biomolecular condensates around active gene loci and regulate transcription. However, the structural details of condensates remain elusive. In this study, for Nanog, a master TF in mammalian embryonic stem cells known to form protein condensates in vitro, we examined protein structures in the condensates using residue-level coarse-grained molecular simulations. Human Nanog formed micelle-like clusters in the condensate. In the micelle-like cluster, the C-terminal disordered domains, including the tryptophan repeat (WR) regions, interacted with each other near the cluster center primarily via hydrophobic interaction. In contrast, hydrophilic disordered N-terminal and DNA-binding domains were exposed on the surface of the clusters. Electrostatic attractions of these surface residues were responsible for bridging multiple micelle-like structures in the condensate. The micelle-like structure and condensate were dynamic and liquid-like. Mutation of tryptophan residues in the WR region which was implicated to be important for a Nanog function resulted in dissolution of the Nanog condensate. Finally, to examine the impact of Nanog cluster to DNA, we added DNA fragments to the Nanog condensate. Nanog DNA-binding domains exposed to the surface of the micelle-like cluster could recruit more than one DNA fragments, making DNA-DNA distance shorter.

How Do Nucleosome Dynamics Regulate Protein Search on DNA?

Nearly three-fourths of all eukaryotic DNA is occupied by nucleosomes, protein-DNA complexes comprising octameric histone core proteins and ∼150 base pairs of DNA. In addition to acting as a DNA compaction vehicle, the dynamics of nucleosomes regulate the DNA site accessibility for the nonhistone proteins, thereby controlling regulatory processes involved in determining the cell identity and cell fate. Here, we propose an analytical framework to analyze the role of nucleosome dynamics on the target search process of transcription factors through a simple discrete-state stochastic description of the search process. By considering the experimentally determined kinetic rates associated with protein and nucleosome dynamics as the only inputs, we estimate the target search time of a protein via first-passage probability calculations separately during nucleosome breathing and sliding dynamics. Although both the nucleosome dynamics permit transient access to the DNA sites that are otherwise occluded by the histone proteins, our result suggests substantial differences between the protein search mechanism on a nucleosome performing breathing and sliding dynamics. Furthermore, we identify the molecular factors that influence the search efficiency and demonstrate how these factors together portray a highly dynamic landscape of gene regulation. Our analytical results are validated using extensive Monte Carlo simulations.

OpenABC Enables Flexible, Simplified, and Efficient GPU Accelerated Simulations of Biomolecular Condensates

Biomolecular condensates are important structures in various cellular processes but are challenging to study using traditional experimental techniques. In silico simulations with residue-level coarse-grained models strike a balance between computational efficiency and chemical accuracy. They could offer valuable insights by connecting the emergent properties of these complex systems with molecular sequences. However, existing coarse-grained models often lack easy-to-follow tutorials and are implemented in software that is not optimal for condensate simulations. To address these issues, we introduce OpenABC, a software package that greatly simplifies the setup and execution of coarse-grained condensate simulations with multiple force fields using Python scripting. OpenABC seamlessly integrates with the OpenMM molecular dynamics engine, enabling efficient simulations with performances on a single GPU that rival the speed achieved by hundreds of CPUs. We also provide tools that convert coarse-grained configurations to all-atom structures for atomistic simulations. We anticipate that Open-ABC will significantly facilitate the adoption of in silico simulations by a broader community to investigate the structural and dynamical properties of condensates. Open-ABC is available at https://github.com/ZhangGroup-MITChemistry/OpenABC.

Nucleosome breathing facilitates cooperative binding of pluripotency factors Sox2 and Oct4 to DNA

Critical lineage commitment events are staged by multiple transcription factors (TFs) binding to their cognate motifs, often positioned at nucleosome-enriched regions of chromatin. The underlying mechanism remains elusive due to difficulty in disentangling the heterogeneity in chromatin states. Using a novel coarse-grained model and molecular dynamics simulations, here we probe the association of Sox2 and Oct4 proteins that show clustered binding at the entry-exit region of a nucleosome. The model captures the conformational heterogeneity of nucleosome breathing dynamics that features repeated wrap-unwrap transitions of a DNA segment from one end of the nucleosome. During the dynamics, DNA forms bulges that diffuse stochastically and may regulate the target search dynamics of a protein by nonspecifically interacting with it. The overall search kinetics of the TF pair follows a "dissociation-compensated-association" mechanism, where Oct4 binding is facilitated by the association of Sox2. The cooperativity stems from a change in entropy caused by an alteration in the nucleosome dynamics upon TF binding. The binding pattern is consistent with a live-cell single-particle tracking experiment, suggesting the mechanism observed for clustered binding of a TF pair, which is a hallmark of cis-regulatory elements, has broader implications in understanding gene regulation in a complex chromatin environment.

Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.

Mobility of Bacterial Protein Hfq on dsDNA: Role of C-Terminus-Mediated Transient Binding

The mobility of protein is fundamental in the machinery of life. Here, we have investigated the effect of DNA binding in conjunction with DNA segmental fluctuation (internal motion) of the bacterial Hfq master regulator devoid of its amyloid C-terminus domain. Hfq is one of the most abundant nucleoid associated proteins that shape the bacterial chromosome and is involved in several aspects of nucleic acid metabolism. Fluorescence microscopy has been used to track a C-terminus domain lacking mutant form of Hfq on double-stranded DNA, which is stretched by confinement to a rectangular nanofluidic channel. The mobility of the mutant is strongly accelerated with respect to the wild-type variant. Furthermore, it shows a reverse dependence on the internal motion of DNA, in that slower motion results in slower protein diffusion. The results demonstrate the subtle role of DNA internal motion in controlling the mobility of a nucleoid associated protein, and, in particular, the importance of transient binding and moving DNA strands out of the way.

Single-Molecule Methods for Investigating the Double-Stranded DNA Bendability

The various DNA-protein interactions associated with the expression of genetic information involve double-stranded DNA (dsDNA) bending. Due to the importance of the formation of the dsDNA bending structure, dsDNA bending properties have long been investigated in the biophysics field. Conventionally, DNA bendability is characterized by innate averaging data from bulk experiments. The advent of single-molecule methods, such as atomic force microscopy, optical and magnetic tweezers, tethered particle motion, and single-molecule fluorescence resonance energy transfer measurement, has provided valuable tools to investigate not only the static structures but also the dynamic properties of bent dsDNA. Here, we reviewed the single-molecule methods that have been used for investigating dsDNA bendability and new findings related to dsDNA bending. Single-molecule approaches are promising tools for revealing the unknown properties of dsDNA related to its bending, particularly in cells.

Probing Amyloid-DNA Interaction with Nanofluidics

Nanofluidics is an emerging methodology to investigate single biomacromolecules without functionalization and/or attachment of the molecules to a substrate. In conjunction with fluorescence microscopy, it can be used to investigate structural and dynamical aspects of amyloid-DNA interaction. Here, we summarize the methodology for fabricating lab-on-chip devices in relatively cheap polymer resins and featuring quasi one-dimensional nanochannels with a cross-sectional diameter of tens to a few hundred nanometers. Site-specific staining of amyloid-forming protein Hfq with a fluorescence dye is also described. The methodology is illustrated with two application studies. The first study involves assembling bacterial amyloid proteins such as Hfq on double-stranded DNA and monitoring the folding and compaction of DNA in a condensed state. The second study is about the concerted motion of Hfq on DNA and how this is related to DNA's internal motion. Explicit details of procedures and workflows are given throughout.

Coarse-grained molecular dynamics simulations of base-pair mismatch recognition protein MutS sliding along DNA

DNA mismatches are frequently generated by various intrinsic and extrinsic factors including DNA replication errors, oxygen species, ultraviolet, and ionizing radiation. These mismatches should be corrected by the mismatches repair (MMR) pathway to maintain genome integrity. In the Escherichia coli (E. coli) MMR pathway, MutS searches and recognizes a base-pair mismatch from millions of base-pairs. Once recognized, ADP bound to MutS is exchanged with ATP, which induces a conformational change in MutS. Previous single-molecule fluorescence microscopy studies have suggested that ADP-bound MutS temporarily slides along double-stranded DNA in a rotation-coupled manner to search a base-pair mismatch and so does ATP-bound MutS in a rotation-uncoupled manner. However, the detailed structural dynamics of the sliding remains unclear. In this study, we performed coarse-grained molecular dynamics simulations of the E. coli MutS bound on DNA in three different conformations: ADP-bound (MutS^ADP), ATP-bound open clamp (MutSOpenATP), and ATP-bound closed clamp (MutSClosedATP) conformations. In the simulations, we observed conformation-dependent diffusion of MutS along DNA. MutS^ADP and MutSClosedATP diffused along DNA in a rotation-coupled manner with rare and frequent groove-crossing events, respectively. In the groove-crossing events, MutS overcame an edge of a groove and temporarily diffused in a rotation-uncoupled manner. It was also indicated that mismatch searches by MutSOpenATP is inefficient in terms of mismatch checking even though it diffuses along DNA and reaches unchecked regions more rapidly than MutS^ADP.

Testing mechanisms of DNA sliding by architectural DNA-binding proteins: dynamics of single wild-type and mutant protein molecules in vitro and in vivo

Architectural DNA-binding proteins (ADBPs) are abundant constituents of eukaryotic or bacterial chromosomes that bind DNA promiscuously and function in diverse DNA reactions. They generate large conformational changes in DNA upon binding yet can slide along DNA when searching for functional binding sites. Here we investigate the mechanism by which ADBPs diffuse on DNA by single-molecule analyses of mutant proteins rationally chosen to distinguish between rotation-coupled diffusion and DNA surface sliding after transient unbinding from the groove(s). The properties of yeast Nhp6A mutant proteins, combined with molecular dynamics simulations, suggest Nhp6A switches between two binding modes: a static state, in which the HMGB domain is bound within the minor groove with the DNA highly bent, and a mobile state, where the protein is traveling along the DNA surface by means of its flexible N-terminal basic arm. The behaviors of Fis mutants, a bacterial nucleoid-associated helix-turn-helix dimer, are best explained by mobile proteins unbinding from the major groove and diffusing along the DNA surface. Nhp6A, Fis, and bacterial HU are all near exclusively associated with the chromosome, as packaged within the bacterial nucleoid, and can be modeled by three diffusion modes where HU exhibits the fastest and Fis the slowest diffusion.

Coarse-grained nucleic acid-protein model for hybrid nanotechnology

The emerging field of hybrid DNA-protein nanotechnology brings with it the potential for many novel materials which combine the addressability of DNA nanotechnology with the versatility of protein interactions. However, the design and computational study of these hybrid structures is difficult due to the system sizes involved. To aid in the design and in silico analysis process, we introduce here a coarse-grained DNA/RNA-protein model that extends the oxDNA/oxRNA models of DNA/RNA with a coarse-grained model of proteins based on an anisotropic network model representation. Fully equipped with analysis scripts and visualization, our model aims to facilitate hybrid nanomaterial design towards eventual experimental realization, as well as enabling study of biological complexes. We further demonstrate its usage by simulating DNA-protein nanocage, DNA wrapped around histones, and a nascent RNA in polymerase.

Discrete-state stochastic kinetic models for target DNA search by proteins: Theory and experimental applications

To perform their functions, transcription factors and DNA-repair/modifying enzymes randomly search DNA in order to locate their specific targets on DNA. Discrete-state stochastic kinetic models have been developed to explain how the efficiency of the search process is influenced by the molecular properties of proteins and DNA as well as by other factors such as molecular crowding. These theoretical models not only offer explanations on the relation of microscopic processes to macroscopic behavior of proteins, but also facilitate the analysis and interpretation of experimental data. In this review article, we provide an overview on discrete-state stochastic kinetic models and explain how these models can be applied to experimental investigations using stopped-flow, single-molecule, nuclear magnetic resonance (NMR), and other biophysical and biochemical methods.

Linker DNA Length is a Key to Tri-nucleosome Folding

The folding of a nucleosome array has long been one of the fundamental and unsolved problems in chromatin biology. In this study, we address how nucleosome array folding depends on the length of linker DNA. We performed molecular dynamics simulations of a tri-nucleosome, a minimal model of chromatin folding, with various linker lengths (LLs) ranging from 20 to 40 base pairs (bps). We found that the tri-nucleosome folding strongly depends on LLs, and classified the structure ensemble into five classes, named from trinuc-1 to trinuc-5. As a function of LL, the different classes appear, on average, every 2 bps with a period of 10 bps, and are characterized by distinct inter-nucleosome interactions. The trinuc-1 conformation corresponds to LL ~ 10n, where n is an integer, and is stabilized by the tight packing between the first and the third nucleosomes, consistent with a zigzag fiber form. Structures of the other four classes are more diverse and distributed continuously in the space of possible configurations. Histone-DNA electrostatic interactions in the tri-nucleosome are further analyzed.

The HMGB chromatin protein Nhp6A can bypass obstacles when traveling on DNA

DNA binding proteins rapidly locate their specific DNA targets through a combination of 3D and 1D diffusion mechanisms, with the 1D search involving bidirectional sliding along DNA. However, even in nucleosome-free regions, chromosomes are highly decorated with associated proteins that may block sliding. Here we investigate the ability of the abundant chromatin-associated HMGB protein Nhp6A from Saccharomyces cerevisiae to travel along DNA in the presence of other architectural DNA binding proteins using single-molecule fluorescence microscopy. We observed that 1D diffusion by Nhp6A molecules is retarded by increasing densities of the bacterial proteins Fis and HU and by Nhp6A, indicating these structurally diverse proteins impede Nhp6A mobility on DNA. However, the average travel distances were larger than the average distances between neighboring proteins, implying Nhp6A is able to bypass each of these obstacles. Together with molecular dynamics simulations, our analyses suggest two binding modes: mobile molecules that can bypass barriers as they seek out DNA targets, and near stationary molecules that are associated with neighboring proteins or preferred DNA structures. The ability of mobile Nhp6A molecules to bypass different obstacles on DNA suggests they do not block 1D searches by other DNA binding proteins.

Role of Internal DNA Motion on the Mobility of a Nucleoid-Associated Protein

Protein transport on DNA is at the core of the machinery of life. Here we investigated the influence of DNA internal motion on the mobility of Hfq, which is involved in several aspects of nucleic acid metabolism and is one of the nucleoid-associated proteins that shape the bacterial chromosome. Fluorescence microscopy was used to follow Hfq on double-stranded DNA that was stretched by confinement to a channel with a diameter of 125 nm. The protein mobility shows a strong dependence on the internal motion of DNA in that slower motion results in faster protein diffusion. A model of released diffusion is proposed that is based on three-dimensional diffusion through the interior of the DNA coil interspersed by periods in which the protein is immobilized in a bound state. We surmise that the coupling between DNA internal motion and protein mobility has important implications for DNA metabolism and protein-binding-related regulation of gene expression.

Nucleosome allostery in pioneer transcription factor binding

While recent experiments revealed that some pioneer transcription factors (TFs) can bind to their target DNA sequences inside a nucleosome, the binding dynamics of their target recognitions are poorly understood. Here we used the latest coarse-grained models and molecular dynamics simulations to study the nucleosome-binding procedure of the two pioneer TFs, Sox2 and Oct4. In the simulations for a strongly positioning nucleosome, Sox2 selected its target DNA sequence only when the target was exposed. Otherwise, Sox2 entropically bound to the dyad region nonspecifically. In contrast, Oct4 plastically bound on the nucleosome mainly in two ways. First, the two POU domains of Oct4 separately bound to the two parallel gyres of the nucleosomal DNA, supporting the previous experimental results of the partial motif recognition. Second, the POU_S domain of Oct4 favored binding on the acidic patch of histones. Then, simulating the TFs binding to a genomic nucleosome, the LIN28B nucleosome, we found that the recognition of a pseudo motif by Sox2 induced the local DNA bending and shifted the population of the rotational position of the nucleosomal DNA. The redistributed DNA phase, in turn, changed the accessibility of a distant TF binding site, which consequently affected the binding probability of a second Sox2 or Oct4. These results revealed a nucleosomal DNA-mediated allosteric mechanism, through which one TF binding event can change the global conformation, and effectively regulate the binding of another TF at distant sites. Our simulations provide insights into the binding mechanism of single and multiple TFs on the nucleosome.

Molecular mechanism of histone variant H2A.B on stability and assembly of nucleosome and chromatin structures

BACKGROUND

H2A.B, the most divergent histone variant of H2A, can significantly modulate nucleosome and chromatin structures. However, the related structural details and the underlying mechanism remain elusive to date. In this work, we built atomic models of the H2A.B-containing nucleosome core particle (NCP), chromatosome, and chromatin fiber. Multiscale modeling including all-atom molecular dynamics and coarse-grained simulations were then carried out for these systems.

RESULTS

It is found that sequence differences at the C-terminal tail, the docking domain, and the L2 loop, between H2A.B and H2A are directly responsible for the DNA unwrapping in the H2A.B NCP, whereas the N-terminus of H2A.B may somewhat compensate for the aforementioned unwrapping effect. The assembly of the H2A.B NCP is more difficult than that of the H2A NCP. H2A.B may also modulate the interactions of H1 with both the NCP and the linker DNA and could further affect the higher-order structure of the chromatin fiber.

CONCLUSIONS

The results agree with the experimental results and may shed new light on the biological function of H2A.B. Multiscale modeling may be a valuable tool for investigating structure and dynamics of the nucleosome and the chromatin induced by various histone variants.

Single molecule analysis reveals monomeric XPA bends DNA and undergoes episodic linear diffusion during damage search

Nucleotide excision repair (NER) removes a wide range of DNA lesions, including UV-induced photoproducts and bulky base adducts. XPA is an essential protein in eukaryotic NER, although reports about its stoichiometry and role in damage recognition are controversial. Here, by PeakForce Tapping atomic force microscopy, we show that human XPA binds and bends DNA by ∼60° as a monomer. Furthermore, we observe XPA specificity for the helix-distorting base adduct N-(2'-deoxyguanosin-8-yl)-2-acetylaminofluorene over non-damaged dsDNA. Moreover, single molecule fluorescence microscopy reveals that DNA-bound XPA exhibits multiple modes of linear diffusion between paused phases. The presence of DNA damage increases the frequency of pausing. Truncated XPA, lacking the intrinsically disordered N- and C-termini, loses specificity for DNA lesions and shows less pausing on damaged DNA. Our data are consistent with a working model in which monomeric XPA bends DNA, displays episodic phases of linear diffusion along DNA, and pauses in response to DNA damage.

Whole-Cell Models and Simulations in Molecular Detail

Comprehensive data about the composition and structure of cellular components have enabled the construction of quantitative whole-cell models. While kinetic network-type models have been established, it is also becoming possible to build physical, molecular-level models of cellular environments. This review outlines challenges in constructing and simulating such models and discusses near- and long-term opportunities for developing physical whole-cell models that can connect molecular structure with biological function.

Nucleosome Crowding in Chromatin Slows the Diffusion but Can Promote Target Search of Proteins

Dynamics of nuclear proteins in crowded chromatin has only been poorly understood. Here, we address the diffusion, target search, and structural dynamics of three proteins in a model chromatin using coarse-grained molecular simulations run on the K computer. We prepared two structures of chromatin made of 20 nucleosomes with different nucleosome densities and investigated dynamics of two transcription factors, HMGB1 and p53, and one signaling protein, ERK, embedded in the chromatin. We found fast and normal diffusion of the nuclear proteins in the low-density chromatins and slow and subdiffusional movements in the high-density chromatin. The diffusion of the largest transcription factor, p53, is slowed by high-density chromatin most markedly. The on rates and off rates for DNA binding are increased and decreased, respectively, in the high-density chromatin. To our surprise, the DNA sequence search was faster in chromatin with high nucleosome density, though the diffusion is slower. We also found that the three nuclear proteins preferred to bind on the linker DNA and the entry and exit regions of nucleosomal DNA. In addition to these regions, HMGB1 and p53 also bound to the dyad.

Sliding Mechanism at a Coiled-Coil Interface

The α-helical coiled coil (CC) is a common protein motif that because of the simplicity of its sequence/structure relationship, it has been studied extensively to address fundamental questions in protein science as well as to develop strategies for designing protein with novel architectures. Nevertheless, a complete understanding of CC structures and their dynamics is still far from achieved. Particularly, spontaneous sliding at interfaces of CC proteins was observed for some systems, but its mechanism and usage as an intrinsic conformational change at CCs in protein-protein interfaces is unclear. Using coarse-grained and atomistic simulations, we study various sequences of homodimeric CC, in both parallel and antiparallel configurations. Both the strength of the hydrophobic core and the existence of salt bridges at the periphery of the interface affect sliding dynamics at the CC interface. Although the energy landscape for sliding along a CC interface is different for parallel and antiparallel configurations, both are characterized by a free energy of 1-1.5 kcal/mol, depending on the residues that constitute the CC interface. These barrier heights suggest that sliding kinetics is relatively slow in CC systems and are not expected to be of long length scale, yet they can be involved in functional motions. Our study explains the sliding that has been experimentally observed for the antiparallel CC of the dynein stalk region and the nuclear pore complex and suggests that this one-dimensional motion is an intrinsic feature in CC systems that can be involved in other CC systems.

Chromatin remodelers couple inchworm motion with twist-defect formation to slide nucleosomal DNA

ATP-dependent chromatin remodelers are molecular machines that control genome organization by repositioning, ejecting, or editing nucleosomes, activities that confer them essential regulatory roles on gene expression and DNA replication. Here, we investigate the molecular mechanism of active nucleosome sliding by means of molecular dynamics simulations of the Snf2 remodeler translocase in complex with a nucleosome. During its inchworm motion driven by ATP consumption, the translocase overwrites the original nucleosome energy landscape via steric and electrostatic interactions to induce sliding of nucleosomal DNA unidirectionally. The sliding is initiated at the remodeler binding location via the generation of a pair of twist defects, which then spontaneously propagate to complete sliding throughout the entire nucleosome. We also reveal how remodeler mutations and DNA sequence control active nucleosome repositioning, explaining several past experimental observations. These results offer a detailed mechanistic picture of remodeling important for the complete understanding of these key biological processes.

Nucleosomes are the protein-DNA complexes underlying Eukaryotic genome organization, and serve as regulators of gene expression by occluding DNA to other proteins. This regulation requires the precise positioning of nucleosomes along DNA. Chromatin remodelers are the molecular machines that consume ATP to slide nucleosome at their correct locations, but the mechanisms of remodeling are still unclear. Based on the static structural information of a remodeler bound on nucleosome, we performed molecular dynamics computer simulations revealing the details of how remodelers slide nucleosomal DNA: the inchworm-like motion of remodelers create small DNA deformations called twist defects, which then spontaneously propagate throughout the nucleosome to induce sliding. These simulations explain several past experimental findings and are important for our understanding of genome organization.

Force-extension behavior of DNA in the presence of DNA-bending nucleoid associated proteins

Interactions between nucleoid associated proteins (NAPs) and DNA affect DNA polymer conformation, leading to phenomena such as concentration dependent force-extension behavior. These effects, in turn, also impact the local binding behavior of the protein, such as high forces causing proteins to unbind, or proteins binding favorably to locally bent DNA. We develop a coarse-grained NAP-DNA simulation model that incorporates both force- and concentration-dependent behaviors, in order to study the interplay between NAP binding and DNA conformation. This model system includes multi-state protein binding and unbinding, motivated by prior work, but is now dependent on the local structure of the DNA, which is related to external forces acting on the DNA strand. We observe the expected qualitative binding behavior, where more proteins are bound at lower forces than at higher forces. Our model also includes NAP-induced DNA bending, which affects DNA elasticity. We see semi-quantitative matching of our simulated force-extension behavior to the reported experimental data. By using a coarse-grained simulation, we are also able to look at non-equilibrium behaviors, such as dynamic extension of a DNA strand. We stretch a DNA strand at different rates and at different NAP concentrations to observe how the time scales of the system (such as pulling time and unbinding time) work in concert. When these time scales are similar, we observe measurable rate-dependent changes in the system, which include the number of proteins bound and the force required to extend the DNA molecule. This suggests that the relative time scales of different dynamic processes play an important role in the behavior of NAP-DNA systems.

Super-Temporal-Resolved Microscopy Reveals Multistep Desorption Kinetics of α-Lactalbumin from Nylon

Insight into the mechanisms driving protein-polymer interactions is constantly improving due to advances in experimental and computational methods. In this study, we used super-temporal-resolved microscopy (STReM) to study the interfacial kinetics of a globular protein, α-lactalbumin (α-LA), adsorbing at the water-nylon 6,6 interface. The improved temporal resolution of STReM revealed that residence time distributions involve an additional step in the desorption process. Increasing the ionic strength in the bulk solution accelerated the desorption rate of α-LA, attributed to adsorption-induced conformational changes. Ensemble circular dichroism measurements were used to support a consecutive reaction mechanism. Without the improved temporal resolution of STReM, the desorption intermediate was not resolvable, highlighting both STReM's potential to uncover new kinetic mechanisms and the continuing need to push for better time and space resolution.

DNA sliding in nucleosomes via twist defect propagation revealed by molecular simulations

While nucleosomes are highly stable structures as fundamental units of chromatin, they also slide along the DNA, either spontaneously or by active remodelers. Here, we investigate the microscopic mechanisms of nucleosome sliding by multiscale molecular simulations, characterizing how the screw-like motion of DNA proceeds via the formation and propagation of twist defects. Firstly, coarse-grained molecular simulations reveal that the sliding dynamics is highly dependent on DNA sequence. Depending on the sequence and the nucleosome super-helical location, we find two distinct types of twist defects: a locally under-twisted DNA region, previously observed in crystal structures, and a locally over-twisted DNA, an unprecedented feature. The stability of the over-twist defect was confirmed via all-atom simulations. Analysis of our trajectories via Markov state modeling highlights how the sequence-dependence of the sliding dynamics is due to the different twist defect energy costs, and in particular how nucleosome regions where defects cannot easily form introduce the kinetic bottlenecks slowing down repositioning. Twist defects can also mediate sliding of nucleosomes made with strong positioning sequences, albeit at a much lower diffusion coefficient, due to a high-energy intermediate state. Finally, we discuss how chromatin remodelers may exploit these spontaneous fluctuations to induce unidirectional sliding of nucleosomes.

Reconstruction of Atomistic Structures from Coarse-Grained Models for Protein-DNA Complexes

While coarse-grained (CG) simulations have widely been used to accelerate structure sampling of large biomolecular complexes, they are unavoidably less accurate and thus the reconstruction of all-atom (AA) structures and the subsequent refinement is desirable. In this study we developed an efficient method to reconstruct AA structures from sampled CG protein-DNA complex models, which attempts to model the protein-DNA interface accurately. First we developed a method to reconstruct atomic details of DNA structures from a three-site per nucleotide CG model, which uses a DNA fragment library. Next, for the protein-DNA interface, we referred to the side chain orientations in the known structure of the target interface when available. The other parts are modeled by existing tools. We confirmed the accuracy of the protocol in various aspects including the structure deviation in the self-reproduction, the base pair reproducibility, atomic contacts at the protein-DNA interface, and feasibility of the posterior AA simulations.

Effects of electrostatic interactions on ligand dissociation kinetics

We study unbinding of multivalent cationic ligands from oppositely charged polymeric binding sites sparsely grafted on a flat neutral substrate. Our molecular dynamics simulations are suggested by single-molecule studies of protein-DNA interactions. We consider univalent salt concentrations spanning roughly a 1000-fold range, together with various concentrations of excess ligands in solution. To reveal the ionic effects on unbinding kinetics of spontaneous and facilitated dissociation mechanisms, we treat electrostatic interactions both at a Debye-Hückel (DH) (or implicit ions, i.e., use of an electrostatic potential with a prescribed decay length) level and by the more precise approach of considering all ionic species explicitly in the simulations. We find that the DH approach systematically overestimates unbinding rates, relative to the calculations where all ion pairs are present explicitly in solution, although many aspects of the two types of calculation are qualitatively similar. For facilitated dissociation (FD) (acceleration of unbinding by free ligands in solution) explicit-ion simulations lead to unbinding at lower free-ligand concentrations. Our simulations predict a variety of FD regimes as a function of free-ligand and ion concentrations; a particularly interesting regime is at intermediate concentrations of ligands where nonelectrostatic binding strength controls FD. We conclude that explicit-ion electrostatic modeling is an essential component to quantitatively tackle problems in molecular ligand dissociation, including nucleic-acid-binding proteins.

Role of Macromolecular Crowding on the Intracellular Diffusion of DNA Binding Proteins

Recent experiments suggest that cellular crowding facilitates the target search dynamics of proteins on DNA, the mechanism of which is not yet known. By using large scale computer simulations, we show that two competing factors, namely the width of the depletion layer that separates the crowder cloud from the DNA molecule and the degree of protein-crowder crosstalk, act in harmony to affect the target search dynamics of proteins. The impacts vary from nonspecific to specific target search regime. During a nonspecific search, dynamics of a protein is only minimally affected, whereas, a significantly different behaviour is observed when the protein starts forming a specific protein-DNA complex. We also find that the severity of impacts largely depends upon physiological crowder concentration and deviation from it leads to attenuation in the binding kinetics. Based on extensive kinetic study and binding energy landscape analysis, we further present a comprehensive molecular description of the search process that allows us to interpret the experimental findings.

High Free-Energy Barrier of 1D Diffusion Along DNA by Architectural DNA-Binding Proteins

Architectural DNA-binding proteins function to regulate diverse DNA reactions and have the defining property of significantly changing DNA conformation. Although the 1D movement along DNA by other types of DNA-binding proteins has been visualized, the mobility of architectural DNA-binding proteins on DNA remains unknown. Here, we applied single-molecule fluorescence imaging on arrays of extended DNA molecules to probe the binding dynamics of three structurally distinct architectural DNA-binding proteins: Nhp6A, HU, and Fis. Each of these proteins was observed to move along DNA, and the salt concentration independence of the 1D diffusion implies sliding with continuous contact to DNA. Nhp6A and HU exhibit a single sliding mode, whereas Fis exhibits two sliding modes. Based on comparison of the diffusion coefficients and sizes of many DNA binding proteins, the architectural proteins are categorized into a new group distinguished by an unusually high free-energy barrier for 1D diffusion. The higher free-energy barrier for 1D diffusion by architectural proteins can be attributed to the large DNA conformational changes that accompany binding and impede rotation-coupled movement along the DNA grooves.

Sequence-dependent nucleosome sliding in rotation-coupled and uncoupled modes revealed by molecular simulations

While nucleosome positioning on eukaryotic genome play important roles for genetic regulation, molecular mechanisms of nucleosome positioning and sliding along DNA are not well understood. Here we investigated thermally-activated spontaneous nucleosome sliding mechanisms developing and applying a coarse-grained molecular simulation method that incorporates both long-range electrostatic and short-range hydrogen-bond interactions between histone octamer and DNA. The simulations revealed two distinct sliding modes depending on the nucleosomal DNA sequence. A uniform DNA sequence showed frequent sliding with one base pair step in a rotation-coupled manner, akin to screw-like motions. On the contrary, a strong positioning sequence, the so-called 601 sequence, exhibits rare, abrupt transitions of five and ten base pair steps without rotation. Moreover, we evaluated the importance of hydrogen bond interactions on the sliding mode, finding that strong and weak bonds favor respectively the rotation-coupled and -uncoupled sliding movements.

How proteins bind to DNA: target discrimination and dynamic sequence search by the telomeric protein TRF1

Target search as performed by DNA-binding proteins is a complex process, in which multiple factors contribute to both thermodynamic discrimination of the target sequence from overwhelmingly abundant off-target sites and kinetic acceleration of dynamic sequence interrogation. TRF1, the protein that binds to telomeric tandem repeats, faces an intriguing variant of the search problem where target sites are clustered within short fragments of chromosomal DNA. In this study, we use extensive (>0.5 ms in total) MD simulations to study the dynamical aspects of sequence-specific binding of TRF1 at both telomeric and non-cognate DNA. For the first time, we describe the spontaneous formation of a sequence-specific native protein-DNA complex in atomistic detail, and study the mechanism by which proteins avoid off-target binding while retaining high affinity for target sites. Our calculated free energy landscapes reproduce the thermodynamics of sequence-specific binding, while statistical approaches allow for a comprehensive description of intermediate stages of complex formation.