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

Single-molecule characterization of target search dynamics of DNA-binding proteins in DNA-condensed droplets

Target search models of DNA-binding proteins in cells typically consider search mechanisms that include 3D diffusion and 1D sliding, which can be characterized by single-molecule tracking on DNA. However, the finding of liquid droplets of DNA and nuclear components in cells cast doubt on extrapolation from the behavior in ideal non-condensed DNA conditions to those in cells. In this study, we investigate the target search behavior of DNA-binding proteins in reconstituted DNA-condensed droplets using single-molecule fluorescence microscopy. To mimic nuclear condensates, we reconstituted DNA-condensed droplets using dextran and PEG polymers. In the DNA-condensed droplets, we measured the translational movement of four DNA-binding proteins (p53, Nhp6A, Fis and Cas9) and p53 mutants possessing different structures, sizes, and oligomeric states. Our results demonstrate the presence of fast and slow mobility modes in DNA-condensed droplets for the four DNA-binding proteins. The slow mobility mode capability is correlated strongly to the molecular size and the number of DNA-binding domains on DNA-binding proteins, but only moderately to the affinity to single DNA segments in non-condensed conditions. The slow mobility mode in DNA-condensed droplets is interpreted as a multivalent interaction mode of the DNA-binding protein to multiple DNA segments.

DNA Sequence-Dependent Binding of Linker Histone gH1 Regulates Nucleosome Conformations

Sequence-dependent binding between DNA and proteins in chromatin is an essential part of gene expression. Linker histone H1 is an important protein in the regulation of chromatin compartmentalization and compaction, and its binding with the nucleosome is sensitive to the DNA sequence. Although the interactions of H1 and DNA have been widely investigated, the mechanism of nucleosome conformation changes induced by the DNA-sequence-dependent binding with gH1 (globular H1.0) remains largely unclear at the atomic level. In the present molecular dynamics simulations, both linker and dyad DNAs were mutated to investigate the conformational changes of the nucleosome induced by the sequence-dependent binding of gH1 based on the on-dyad binding mode. Our results indicate that gH1 is insensitive to the DNA sequence of the dyad DNA but presents an apparent preference to linker DNA with an AT-rich sequence. Moreover, this specific binding induces the entry/exit region of a nucleosome to a tight conformation and regulates the accessibility of core histones. Considering that the entry/exit region of the nucleosome is a crucial binding site for many functional proteins related to gene expression, the conformational change at this region could represent an important gene regulation signal.

Influence of Nonspecific Interactions between Proteins and In Vivo Cytoplasmic Crowders in Facilitated Diffusion of Proteins: Theoretical Insights

The binding of proteins to their respective specific sites on the DNA through facilitated diffusion serves as the initial step of various important biological processes. While this search process has been thoroughly investigated via in vitro studies, the cellular environment is complex and may interfere with the protein's search dynamics. The cytosol is heavily crowded, which can potentially modify the search by nonspecifically interacting with the protein that has been mostly overlooked. In this work, we probe the target search dynamics in the presence of explicit crowding agents that have an affinity toward the protein. We theoretically investigate the role of such protein-crowder associations in the target search process using a discrete-state stochastic framework that allows for the analytical description of dynamic properties. It is found that stronger nonspecific associations between the crowder and proteins can accelerate the facilitated diffusion of proteins in comparison with a purely inert, rather weakly interacting cellular environment. This effect depends on how strong these associations are, the spatial positions of the target with respect to the crowders, and the size of the crowded region. Our theoretical results are also tested with Monte Carlo computer simulations. Our predictions are in qualitative agreement with existing experimental observations and computational studies.

Protein assembly and crowding simulations

Proteins encounter frequent molecular interactions in biological environments. Computer simulations have become an increasingly important tool in providing mechanistic insights into how such interactions in vivo relate to their biological function. The review here focuses on simulations describing protein assembly and molecular crowding effects as two important aspects that are distinguished mainly by how specific and long-lived protein contacts are. On the topic of crowding, recent simulations have provided new insights into how crowding affects protein folding and stability, modulates enzyme activity, and affects diffusive properties. Recent studies of assembly processes focus on assembly pathways, especially for virus capsids, amyloid aggregation pathways, and the role of multivalent interactions leading to phase separation. Also, discussed are technical challenges in achieving increasingly realistic simulations of interactions in cellular environments.

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.

Semi-Implicit Time Integration with Hessian Eigenvalue Corrections for a Larger Time Step in Molecular Dynamics Simulations

In molecular dynamics simulations, the limited time step size has been a barrier to simulating long-time behaviors. Implicit time integration methods allow markedly larger time steps than the standard explicit time method, although they have major drawbacks such as overheads solving linear systems and instability of Newton iterations. To overcome these issues, we propose a semi-implicit time integration scheme, the semi-implicit Hessian correction (SimHec) scheme, for overdamped Langevin dynamics. The method focuses on the Hessian matrices of bonded and nonbonded interactions, where components with large negative Hessian eigenvalues are cut off in the linear approximation of momentum equations to avoid instability. The narrow band Hessian matrix enables an efficient parallelized linear solution with an overlapping approximation. We tested SimHec for the interdomain fluctuations in adenylate kinase and the powerstroke transition of myosin II using a coarse-grained protein model. SimHec reproduced the same dynamics as the explicit method, although the transition dynamics tended to be accelerated and fluctuations in bonded potentials were slightly reduced. These deviations were corrected using a hybrid method, SimHec-H, which adds explicit time steps after the semi-implicit time step. The proposed scheme allowed us to use time steps 50-200 times larger than those in explicit time integration, which resulted in a speedup factor of 7-30 taking the overhead into account.

Liquid-liquid phase separation as a common organizing principle of intracellular space and biomembranes providing dynamic adaptive responses

This work is devoted to the phenomenon of liquid-liquid phase separation (LLPS), which has come to be recognized as fundamental organizing principle of living cells. We distinguish separation processes with different dimensions. Well-known 3D-condensation occurs in aqueous solution and leads to membraneless organelle (MLOs) formation. 2D-films may be formed near membrane surfaces and lateral phase separation (membrane rafts) occurs within the membranes themselves. LLPS may also occur on 1D structures like DNA and the cyto- and nucleoskeleton. Phase separation provides efficient transport and sorting of proteins and metabolites, accelerates the assembly of metabolic and signaling complexes, and mediates stress responses. In this work, we propose a model in which the processes of polymerization (1D structures), phase separation in membranes (2D structures), and LLPS in the volume (3D structures) influence each other. Disordered proteins and whole condensates may provide membrane raft separation or polymerization of specific proteins. On the other hand, 1D and 2D structures with special composition or embedded IDRs can nucleate condensates. We hypothesized that environmental change may trigger a LLPS which can propagate within the cell interior moving along the cytoskeleton or as an autowave. New phase propagation quickly and using a low amount of energy adjusts cell signaling and metabolic systems to new demands. Cumulatively, the interconnected phase separation phenomena in different dimensions represent a previously unexplored system of intracellular communication and regulation which cannot be ignored when considering both physiological and pathological cell processes.

Multiscale modeling of genome organization with maximum entropy optimization

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.

Dynamic Autoinhibition of the HMGB1 Protein via Electrostatic Fuzzy Interactions of Intrinsically Disordered Regions

Highly negatively charged segments containing only aspartate or glutamate residues ("D/E repeats") are found in many eukaryotic proteins. For example, the C-terminal 30 residues of the HMGB1 protein are entirely D/E repeats. Using nuclear magnetic resonance (NMR), fluorescence, and computational approaches, we investigated how the D/E repeats causes the autoinhibition of HMGB1 against its specific binding to cisplatin-modified DNA. By varying ionic strength in a wide range (40-900 mM), we were able to shift the conformational equilibrium between the autoinhibited and uninhibited states toward either of them to the full extent. This allowed us to determine the macroscopic and microscopic equilibrium constants for the HMGB1 autoinhibition at various ionic strengths. At a macroscopic level, a model involving the autoinhibited and uninhibited states can explain the salt concentration-dependent binding affinity data. Our data at a microscopic level show that the D/E repeats and other parts of HMGB1 undergo electrostatic fuzzy interactions, each of which is weaker than expected from the macroscopic autoinhibitory effect. This discrepancy suggests that the multivalent nature of the fuzzy interactions enables strong autoinhibition at a macroscopic level despite the relatively weak intramolecular interaction at each site. Both experimental and computational data suggest that the D/E repeats interact preferentially with other intrinsically disordered regions (IDRs) of HMGB1. We also found that mutations mimicking post-translational modifications relevant to nuclear export of HMGB1 can moderately modulate DNA-binding affinity, possibly by impacting the autoinhibition. This study illuminates a functional role of the fuzzy interactions of D/E repeats.

Linker DNA and histone contributions in nucleosome binding by p53

The tumour suppressor protein p53 regulates various genes involved in cell-cycle arrest, apoptosis and DNA repair in response to cellular stress, and apparently functions as a pioneer transcription factor. The pioneer transcription factors can bind nucleosomal DNA, where many transcription factors are largely restricted. However, the mechanisms by which p53 recognizes the nucleosomal DNA are poorly understood. In the present study, we found that p53 requires linker DNAs for the efficient formation of p53-nucleosome complexes. p53 forms an additional specific complex with the nucleosome, when the p53 binding sequence is located around the entry/exit region of the nucleosomal DNA. We also showed that p53 directly binds to the histone H3-H4 complex via its N-terminal 1–93 amino acid region. These results shed light on the mechanism of nucleosome recognition by p53.

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.

Exploring Successful Parameter Region for Coarse-Grained Simulation of Biomolecules by Bayesian Optimization and Active Learning

Accompanied with an increase of revealed biomolecular structures owing to advancements in structural biology, the molecular dynamics (MD) approach, especially coarse-grained (CG) MD suitable for macromolecules, is becoming increasingly important for elucidating their dynamics and behavior. In fact, CG-MD simulation has succeeded in qualitatively reproducing numerous biological processes for various biomolecules such as conformational changes and protein folding with reasonable calculation costs. However, CG-MD simulations strongly depend on various parameters, and selecting an appropriate parameter set is necessary to reproduce a particular biological process. Because exhaustive examination of all candidate parameters is inefficient, it is important to identify successful parameters. Furthermore, the successful region, in which the desired process is reproducible, is essential for describing the detailed mechanics of functional processes and environmental sensitivity and robustness. We propose an efficient search method for identifying the successful region by using two machine learning techniques, Bayesian optimization and active learning. We evaluated its performance using F1-ATPase, a biological rotary motor, with CG-MD simulations. We successfully identified the successful region with lower computational costs (12.3% in the best case) without sacrificing accuracy compared to exhaustive search. This method can accelerate not only parameter search but also biological discussion of the detailed mechanics of functional processes and environmental sensitivity based on MD simulation studies.

How p53 Molecules Solve the Target DNA Search Problem: A Review

Interactions between DNA and DNA-binding proteins play an important role in many essential cellular processes. A key function of the DNA-binding protein p53 is to search for and bind to target sites incorporated in genomic DNA, which triggers transcriptional regulation. How do p53 molecules achieve "rapid" and "accurate" target search in living cells? The search dynamics of p53 were expected to include 3D diffusion in solution, 1D diffusion along DNA, and intersegmental transfer between two different DNA strands. Single-molecule fluorescence microscopy enabled the tracking of p53 molecules on DNA and the characterization of these dynamics quantitatively. Recent intensive single-molecule studies of p53 succeeded in revealing each of these search dynamics. Here, we review these studies and discuss the target search mechanisms of p53.