Free energy landscape of RNA binding dynamics in start codon recognition by eukaryotic ribosomal pre-initiation complex.

Specific interaction between the start codon, 5'-AUG-3', and the anticodon, 5'-CAU-3', ensures accurate initiation of translation. Recent studies show that several near-cognate start codons (e.g. GUG and CUG) can play a role in initiating translation in eukaryotes. However, the mechanism allowing initiation through mismatched base-pairs at the ribosomal decoding site is still unclear at an atomic level. In this work, we propose an extended simulation-based method to evaluate free energy profiles, through computing the distance between each base-pair of the triplet interactions involved in recognition of start codons in eukaryotic translation pre-initiation complex. Our method provides not only the free energy penalty for mismatched start codons relative to the AUG start codon, but also the preferred pathways of transitions between bound and unbound states, which has not been described by previous studies. To verify the method, the binding dynamics of cognate (AUG) and near-cognate start codons (CUG and GUG) were simulated. Evaluated free energy profiles agree with experimentally observed changes in initiation frequencies from respective codons. This work proposes for the first time how a G:U mismatch at the first position of codon (GUG)-anticodon base-pairs destabilizes the accommodation in the initiating eukaryotic ribosome and how initiation at a CUG codon is nearly as strong as, or sometimes stronger than, that at a GUG codon. Our method is expected to be applied to study the affinity changes for various mismatched base-pairs.

The synergistic antitumor effect of combination therapy with a MEK inhibitor and YAP inhibitor on pERK-positive neuroblastoma.

BACKGROUND: We previously reported the in vitro and in vivo antitumor effects of trametinib, a MEK inhibitor, on neuroblastoma with MAPK pathway mutations. As we observed eventual resistance to trametinib in our previous study, we evaluated the combination therapy of CA3, a YAP inhibitor, with trametinib, based on a recent report suggesting the potential involvement of YAP in the mechanism underlying the resistance to trametinib in neuroblastoma. METHODS: SK-N-AS cells (a neuroblastoma cell line harboring RAS mutation) were treated with CA3 in vitro and subjected to a viability assay, immunocytochemistry and flow cytometry. Next, we analyzed the in vitro combination effect of CA3 and trametinib using the CompuSyn software program. Finally, we administered CA3, trametinib or both to SK-N-AS xenograft mice for 10 weeks to analyze the combination effect. RESULTS: CA3 inhibited cell proliferation by both cell cycle arrest and apoptosis in vitro. Combination of CA3 and trametinib induced a significant synergistic effect in vitro (Combination Index <1). Regarding the in vivo experiment, combination therapy suppressed tumor growth, and 100% of mice in the combination therapy group survived, whereas the survival rates were 0% in the CA3 group and 33% in the trametinib group. However, despite this promising survival rate in the combination group, the tumors gradually grew after seven weeks with MAPK reactivation. CONCLUSION: Our results indicated that CA3 and trametinib exerted synergistic antitumor effects on neuroblastoma in vitro and in vivo, and CA3 may be a viable option for concomitant drug therapy with trametinib, since it suppressed the resistance to trametinib. However, this combination effect was not sufficient to achieve complete remission. Therefore, we need to adjust the protocol to obtain a better outcome by determining the mechanism underlying regrowth in the future.

Immunohistochemical staining of phosphorylated-ERK in post-chemotherapeutic samples is a potential predictor of the prognosis of neuroblastoma.

PURPOSE: The majority of relapsed neuroblastomas have mitogen-activated protein kinase (MAPK) pathway activating mutations. We previously showed the in vitro and in vivo anti-tumor effects of MAPK/ERK kinase (MEK) inhibitors in MAPK-activated neuroblastoma. We herein assessed the correlation between MAPK activation and the prognosis in neuroblastoma patients using phosphorylated extra-cellular signal-regulated kinase (pERK) immunohistochemistry to establish the protocol for the clinical administration of MEK inhibitors. METHODS: Neuroblastoma samples from patients treated in our hospital were immunostained with pERK. The clinical outcomes were retrospectively collected from medical records. The correlation between pERK positivity and the prognosis was analyzed. RESULTS: Regarding pre-chemotherapeutic specimens, there were no differences in the pERK status between tumors with a good and bad prognosis in both the nuclei and cytoplasm. Regarding post-chemotherapeutic specimens, one of eight tumors with a good prognosis and four of six tumors with a poor prognosis showed pERK-positive nuclear staining (p = 0.0909) and five of eight tumors with a good prognosis and four of six tumors with a poor prognosis showed pERK-positive cytoplasmic staining (p > 0.9999). CONCLUSION: These findings suggested post-chemotherapeutic-not pre-chemotherapeutic-nuclear pERK-positive neuroblastoma tends to be associated with a poor prognosis and may be a potential therapeutic target for MEK inhibitor treatment.

Enhanced metastatic growth after local tumor resection in the presence of synchronous metastasis in a mouse allograft model of neuroblastoma.

PURPOSE: We investigated how local tumor resection affects metastatic lesions in neuroblastoma. METHODS: MYCN Tg tumor-derived cells were injected subcutaneously into 129+Ter/SvJcl wild-type mice. First, the frequency of metastasis-bearing mice was investigated immunohistochemically (metastatic ratio) at endpoint or post-injection day (PID) 90. Second, the threshold volume of local tumor in mice bearing microscopic lymph node metastasis (mLNM) was investigated at PID 30. Finally, local tumors were resected after exceeding the threshold. Mice were divided into local tumor resection (Resection) and observation (Observation) groups, and the metastatic ratio and volume of LNM were compared between the groups at endpoint or PID 74. RESULTS: The metastatic ratio without local resection was 88% at PID 78-90. The threshold local tumor volume in the mice with mLNM was 745 mm3 at PID 30, so local tumors were resected after exceeding 700 mm3. The metastatic ratio and LNM volume were significantly greater in the Resection group (n = 16) than in the Observation group (n = 16) (94% vs. 38%, p < 0.001; 2092 ± 2310 vs. 275 ± 218 mm3, p < 0.01; respectively) at PID 50-74. CONCLUSION: Local tumor resection might augment the growth of synchronous microscopic metastases. Our results provide insights into the appropriate timing of local resection for high-risk neuroblastoma.

Coarse-Grained Protein Dynamics Studies Using Elastic Network Models.

Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.

Designed Elastic Networks: Models of Complex Protein Machinery.

Recently, the design of mechanical networks with protein-inspired responses has become increasingly popular. Here, we review contributions which were motivated by studies of protein dynamics employing coarse-grained elastic network models. First, the concept of evolutionary optimization that we developed to design network structures which execute prescribed tasks is explained. We then review what presumably marks the origin of the idea to design complex functional networks which encode protein-inspired behavior, namely the design of an elastic network structure which emulates the cycles of ATP-powered conformational motion in protein machines. Two recent applications are reviewed. First, the construction of a model molecular motor, whose operation incorporates both the tight coupling power stroke as well as the loose coupling Brownian ratchet mechanism, is discussed. Second, the evolutionary design of network structures which encode optimal long-range communication between remote sites and represent mechanical models of allosteric proteins is presented. We discuss the prospects of designed protein-mimicking elastic networks as model systems to elucidate the design principles and functional signatures underlying the operation of complex protein machinery.

Dynamic Nucleosome Movement Provides Structural Information of Topological Chromatin Domains in Living Human Cells.

The mammalian genome is organized into submegabase-sized chromatin domains (CDs) including topologically associating domains, which have been identified using chromosome conformation capture-based methods. Single-nucleosome imaging in living mammalian cells has revealed subdiffusively dynamic nucleosome movement. It is unclear how single nucleosomes within CDs fluctuate and how the CD structure reflects the nucleosome movement. Here, we present a polymer model wherein CDs are characterized by fractal dimensions and the nucleosome fibers fluctuate in a viscoelastic medium with memory. We analytically show that the mean-squared displacement (MSD) of nucleosome fluctuations within CDs is subdiffusive. The diffusion coefficient and the subdiffusive exponent depend on the structural information of CDs. This analytical result enabled us to extract information from the single-nucleosome imaging data for HeLa cells. Our observation that the MSD is lower at the nuclear periphery region than the interior region indicates that CDs in the heterochromatin-rich nuclear periphery region are more compact than those in the euchromatin-rich interior region with respect to the fractal dimensions as well as the size. Finally, we evaluated that the average size of CDs is in the range of 100-500 nm and that the relaxation time of nucleosome movement within CDs is a few seconds. Our results provide physical and dynamic insights into the genome architecture in living cells.

Integrin LFA-1 regulates cell adhesion via transient clutch formation.

Integrin LFA-1 regulates immune cell adhesion and trafficking by binding to ICAM-1 upon chemokine stimulation. Integrin-mediated clutch formation between extracellular ICAM-1 and the intracellular actin cytoskeleton is important for cell adhesion. We applied single-molecule tracking analysis to LFA-1 and ICAM-1 in living cells to examine the ligand-binding kinetics and mobility of the molecular clutch under chemokine-induced physiological adhesion and Mn(2+)-induced tight adhesion. Our results show a transient LFA-1-mediated clutch formation that lasts a few seconds and leads to a transient lower-mobility is sufficient to promote cell adhesion. Stable clutch formation was observed for Mn(2+)-induced high affinity LFA-1, but was not required for physiological adhesion. We propose that fast cycling of the clutch formation by intermediate-affinity integrin enables dynamic cell adhesion and migration.

Asymmetric Periodic Boundary Conditions for All-Atom Molecular Dynamics and Coarse-Grained Simulations of Nucleic Acids.

Periodic boundary conditions are commonly applied in molecular dynamics simulations in the microcanonical (NVE), canonical (NVT), and isothermal-isobaric (NpT) ensembles. In their simplest application, a biological system of interest is placed in the middle of a solvation box, which is chosen 'sufficiently large' to minimize any numerical artifacts associated with the periodic boundary conditions. This practical approach brings limitations to the size of biological systems that can be simulated. Here, we study simulations of effectively infinitely long nucleic acids, which are solvated in the directions perpendicular to the polymer chain, while periodic boundary conditions are also applied along the polymer chain. We study the effects of these asymmetric periodic boundary conditions (APBC) on the simulated results, including the mechanical properties of biopolymers and the properties of the surrounding solvent. To get some further insights into the advantages of using the APBC, a coarse-grained worm-like chain model is first studied, illustrating how the persistence length can be extracted from the local properties of the polymer chain, which are less affected by the APBC than some global averages. This is followed by all-atom molecular dynamics simulations of DNA in ionic solutions, where we use the APBC to investigate sequence-dependent properties of DNA molecules and properties of the surrounding solvent.

Myosin-V as a mechanical sensor: an elastic network study.

According to recent experiments, the molecular-motor myosin behaves like a strain sensor, exhibiting different functional responses when loads in opposite directions are applied to its tail. Within an elastic-network model, we explore the sensitivity of the protein to the forces acting on the tail and find, in agreement with experiments, that such forces invoke conformational changes that should affect filament binding and ADP release. Furthermore, conformational responses of myosin to the application of forces to individual residues in its principal functional regions are systematically investigated and a detailed sensitivity map of myosin-V is thus obtained. The results suggest that the strain-sensor behavior is involved in the intrinsic operation of this molecular motor.

Molecular dynamics analysis of biomolecular systems including nucleic acids.

With the recent progress in structural biology and genome biology, structural dynamics of molecular systems that include nucleic acids has attracted attention in the context of gene regulation. The structure-function relationship is an important topic that highlights the importance of the physicochemical properties of nucleotides, as well as that of amino acids in proteins. Simulations are a useful tool for the detailed analysis of molecular dynamics that complement experiments in molecular biology; however, molecular simulation of nucleic acids is less well developed than that of proteins partly due to the physical nature of nucleic acids. In this review, we briefly describe the current status and future directions of the field as a guide to promote collaboration between experimentalists and computational biologists.

Translational recoding by chemical modification of non-AUG start codon ribonucleotide bases.

In contrast to prokaryotes wherein GUG and UUG are permissive start codons, initiation frequencies from non-AUG codons are generally low in eukaryotes, with CUG being considered as strongest. Here, we report that combined 5-cytosine methylation (5mC) and pseudouridylation (Ψ) of near-cognate non-AUG start codons convert GUG and UUG initiation strongly favored over CUG initiation in eukaryotic translation under a certain context. This prokaryotic-like preference is attributed to enhanced NUG initiation by Ψ in the second base and reduced CUG initiation by 5mC in the first base. Molecular dynamics simulation analysis of tRNAiMet anticodon base pairing to the modified codons demonstrates that Ψ universally raises the affinity of codon:anticodon pairing within the ribosomal preinitiation complex through partially mitigating discrimination against non-AUG codons imposed by eukaryotic initiation factor 1. We propose that translational control by chemical modifications of start codon bases can offer a new layer of proteome diversity regulation and therapeutic mRNA technology.

Nonlinearity of mechanochemical motions in motor proteins.

The assumption of linear response of protein molecules to thermal noise or structural perturbations, such as ligand binding or detachment, is broadly used in the studies of protein dynamics. Conformational motions in proteins are traditionally analyzed in terms of normal modes and experimental data on thermal fluctuations in such macromolecules is also usually interpreted in terms of the excitation of normal modes. We have chosen two important protein motors--myosin V and kinesin KIF1A--and performed numerical investigations of their conformational relaxation properties within the coarse-grained elastic network approximation. We have found that the linearity assumption is deficient for ligand-induced conformational motions and can even be violated for characteristic thermal fluctuations. The deficiency is particularly pronounced in KIF1A where the normal mode description fails completely in describing functional mechanochemical motions. These results indicate that important assumptions of the theory of protein dynamics may need to be reconsidered. Neither a single normal mode nor a superposition of such modes yields an approximation of strongly nonlinear dynamics.

A mesoscopic model for protein enzymatic dynamics in solution.

A multi-scale, coarse-grained description of protein conformational dynamics in a solvent is presented. The focus of the paper is on the description of the conformational motions that may accompany enzyme catalysis as the enzyme executes a catalytic cycle, starting with substrate binding and ending with product release and return to the original unbound enzyme. The protein is modeled by a network of beads representing amino acid residues, the solvent is described by multiparticle collision dynamics, and substrate binding and unbinding events are modeled stochastically by conformation-dependent transitions that modify the bonding in the network to correspond to the different binding states of the protein. The solvent dynamics is coupled to that of the protein and hydrodynamic interactions, which are important for the large-scale protein motions, are taken into account. The multi-scale model is used to study the dynamics of the adenylate kinase enzyme in solution. A potential function that describes the different binding and conformational states of the protein and accounts for partial unfolding during the catalytic cycle is constructed as a network built from elastic network and soft potential links. The conformational dynamics of the protein as it undergoes cyclic enzymatic dynamics, as well as its translational diffusion and orientational motion, are investigated using both multiparticle collision dynamics and dynamics that suppresses hydrodynamic coupling. Hydrodynamic interactions are found to have important effects on the large scale conformational motions of the protein and significantly affect the translational diffusion coefficients and orientational correlation times.

Structural dynamics of DNA depending on methylation pattern.

DNA methylation is associated with a number of biological phenomena, and plays crucial roles in epigenetic regulation of eukaryotic gene expression. It is also suggested that DNA methylation alters the mechanical properties of DNA molecules, which is likely to affect epigenetic regulation. However, it has not been systematically investigated how methylation changes the structural and dynamic features of DNA. In this research, to elucidate the effects of methylation on DNA mechanics, a fully atomic molecular dynamics simulation of double-stranded DNA with several methylation patterns was performed. Through the analysis of the relative positioning of the nucleotides (base-step variables), characteristic changes in terms of local flexibility were observed, which further affected the overall DNA geometry and stiffness. These findings may serve as a basis for a discussion on methylation-dependent DNA dynamics in physiological conditions.

Anti-relapse effect of trametinib on a local minimal residual disease neuroblastoma mouse model.

PURPOSE: We reported the in vitro and in vivo anti-tumor effects of trametinib, an MEK inhibitor, on neuroblastoma. However, long-term trametinib administration for bulky tumors failed to prevent local relapse. In this study, we established a local minimal residual disease (L-MRD) model to develop an optimal clinical protocol. METHODS: We prepared an l-MRD model by implanting neuroblastoma cells (SK-N-AS) into the renal capsule of nude mice with total tumorectomy or sham operation 14 days later. These mice received post-operative administration of trametinib or vehicle for eight weeks. Relapse was measured once weekly. Flow cytometry was performed with SK-N-AS cells treated by trametinib. RESULTS: Tumorectomy+trametinib dramatically suppressed relapse, and all mice survived during trametinib administration, while other treatments failed to suppress relapse. The survival rates for other groups were 20% in sham+trametinib, 17% in tumorectomy+vehicle, and 0% in sham+vehicle. Relapse occurred in the tumorectomy+trametinib group after withdrawal of trametinib administration. Flow cytometry revealed G1 arrest in SK-N-AS cells treated with trametinib. CONCLUSION: These findings suggested that trametinib was able to suppress relapse from minimal residual tumor cells. Therefore, we propose that trametinib be administered as an option for maintenance therapy after surgical and chemotherapeutic treatments for neuroblastoma in future clinical protocols.

PHi-C: deciphering Hi-C data into polymer dynamics.

Genomes are spatiotemporally organized within the cell nucleus. Genome-wide chromosome conformation capture (Hi-C) technologies have uncovered the 3D genome organization. Furthermore, live-cell imaging experiments have revealed that genomes are functional in 4D. Although computational modeling methods can convert 2D Hi-C data into population-averaged static 3D genome models, exploring 4D genome nature based on 2D Hi-C data remains lacking. Here, we describe a 4D simulation method, PHi-C (polymer dynamics deciphered from Hi-C data), that depicts 4D genome features from 2D Hi-C data by polymer modeling. PHi-C allows users to interpret 2D Hi-C data as physical interaction parameters within single chromosomes. The physical interaction parameters can then be used in the simulations and analyses to demonstrate dynamic characteristics of genomic loci and chromosomes as observed in live-cell imaging experiments. PHi-C is available at https://github.com/soyashinkai/PHi-C.

Modeling of Nanomachine/Micromachine Crowds: Interplay between the Internal State and Surroundings.

The activity of biological cells is primarily based on chemical reactions and typically modeled as a reaction-diffusion system. Cells are, however, highly crowded with macromolecules, including a variety of molecular machines such as enzymes. The working cycles of these machines are often coupled with their internal motion (conformational changes). In the crowded environment of a cell, motion interference between neighboring molecules is not negligible, and this interference can affect the reaction dynamics through machine operation. To simulate such a situation, we propose a reaction-diffusion model consisting of particles whose shape depends on an internal state variable, for crowds of nano- to micromachines. The interference between nearby particles is naturally introduced through excluded volume repulsion. In the simulations, we observed segregation and flow-like patterns enhanced by crowding out of relevant molecules, as well as molecular synchronization waves and phase transitions. The presented model is simple and extensible for diverse molecular machinery and may serve as a framework to study the interplay between the mechanical stress/strain network and the chemical reaction network in the cell. Applications to more macroscopic systems, e.g., crowds of cells, are also discussed.

Analyzing Fluctuation Properties in Protein Elastic Networks with Sequence-Specific and Distance-Dependent Interactions.

Simple protein elastic networks which neglect amino-acid information often yield reasonable predictions of conformational dynamics and are broadly used. Recently, model variants which incorporate sequence-specific and distance-dependent interactions of residue pairs have been constructed and demonstrated to improve agreement with experimental data. We have applied the new variants in a systematic study of protein fluctuation properties and compared their predictions with those of conventional anisotropic network models. We find that the quality of predictions is frequently linked to poor estimations in highly flexible protein regions. An analysis of a large set of protein structures shows that fluctuations of very weakly connected network residues are intrinsically prone to be significantly overestimated by all models. This problem persists in the new models and is not resolved by taking into account sequence information. The effect becomes even enhanced in the model variant which takes into account very soft long-ranged residue interactions. Beyond these shortcomings, we find that model predictions are largely insensitive to the integration of chemical information, at least regarding the fluctuation properties of individual residues. One can furthermore conclude that the inherent drawbacks may present a serious hindrance when improvement of elastic network models are attempted.

Histone Tail Dynamics in Partially Disassembled Nucleosomes During Chromatin Remodeling.

Nucleosomes are structural units of the chromosome consisting of DNA wrapped around histone proteins, and play important roles in compaction and regulation of the chromatin structure. While the structure and dynamics of canonical nucleosomes have been studied extensively, those of nucleosomes in intermediate states, that occur when their structure or positioning is modulated, have been less understood. In particular, the dynamic features of partially disassembled nucleosomes have not been discussed in previous studies. Using all-atom molecular dynamics simulations, in this study, we investigated the dynamics and stability of nucleosome structures lacking a histone-dimer. DNA in nucleosomes lacking a histone H2A/H2B dimer was drastically deformed due to loss of local interactions between DNA and histones. In contrast, conformation of DNA in nucleosomes lacking H3/H4 was similar to the canonical nucleosome, as the H2A C-terminal domain infiltrated the space originally occupied by the dissociated H3/H4 histones and restricted DNA dynamics in close proximity. Our results suggest that, besides histone chaperones, the intrinsic dynamics of nucleosomes support the exchange of H2A/H2B, which is significantly more frequent than that of H3/H4.