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Vasohibin-1 and small vasohibin-binding protein (SVBP) form an intermolecular heterotetramer in the crystal. The heterotetramer was stabilized by exchange of the conserved N-terminal region., Vasohibins regulate angiogenesis, tumor growth, metastasis and neuronal differentiation. They form a complex with small vasohibin-binding protein (SVBP) and show tubulin tyrosine carboxypeptidase activity. Recent crystal structure determinations of vasohibin–SVBP complexes have provided a molecular basis for complex formation, substrate binding and catalytic activity. However, the regulatory mechanism and dynamics of the complex remain elusive. Here, the crystal structure of the VASH1–SVBP complex and a molecular-dynamics simulation study are reported. The overall structure of the complex was similar to previously reported structures. Importantly, however, the structure revealed a domain-swapped heterotetramer that was formed between twofold symmetry-related molecules. This heterotetramerization was stabilized by the mutual exchange of ten conserved N-terminal residues from the VASH1 structural core, which was intramolecular in other structures. Interestingly, a comparison of this region with previously reported structures revealed that the patterns of hydrogen bonding and hydrophobic interactions vary. In the molecular-dynamics simulations, differences were found between the heterotetramer and heterodimer, where the fluctuation of the N-terminal region in the heterotetramer was suppressed. Thus, heterotetramer formation and flexibility of the N-terminal region may be important for enzyme activity and regulation.

Highlights • Generalized epilepsy with tremor phenotype ss a clinical marker of 6q22.1 microdeletion. • Deep brain stimulation may be applicable choince for intractable myoclonic tremor. • Over activation of basal ganglia may be related to this patient's symptoms., We report a patient with a 6q22.1 deletion, who presented with a rare syndrome of generalized epilepsy, myoclonic tremor, and intellectual disability. There was no clinical progression after follow-up for more than 10 years. Our report presents the genetic basis for a phenotype involving a non-progressive generalized epilepsy with tremor. The efficacy of valproic acid for seizure control and the partial efficacy of deep brain stimulation with propranolol for myoclonic tremor is detailed.

Nanoarchaeum equitans is a species of hyperthermophilic archaea with the smallest genome size. Its alanyl-tRNA synthetase genes are split into AlaRS-α and AlaRS-β, encoding the respective subunits. In the current report, we surveyed N. equitans AlaRS-dependent alanylation of RNA minihelices, composed only of the acceptor stem and the T-arm of tRNAAla. Combination of AlaRS-α and AlaRS-β showed a strong alanylation activity specific to a single G3:U70 base pair, known to mark a specific tRNA for charging with alanine. However, AlaRS-α alone had a weak but appreciable alanylation activity that was independent of the G3:U70 base pair. The shorter 16-mer RNA tetraloop substrate mimicking only the first four base pairs of the acceptor stem of tRNAAla, but with C3:G70 base pair, was also successfully aminoacylated by AlaRS-α. The end of the acceptor stem, including CCA-3' terminus and the discriminator A73, was able to function as a minimal structure for the recognition by the enzyme. Our findings imply that aminoacylation by N. equitans AlaRS-α may represent a vestige of a primitive aminoacylation system, before the appearance of the G3:U70 pair as an identity element for alanine.

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc.

The origin of homochirality in L-amino acid in proteins is one of the mysteries of the evolution of life. Experimental studies show that a non-enzymatic aminoacylation reaction of an RNA minihelix has a preference for L-amino acid over D-amino acid. The reaction initiates by approaching of a 3′-oxygen of the RNA minihelix to the carbonyl carbon of an aminoacyl phosphate oligonucleotide. Here, employing molecular dynamics simulations, we examined the possible mechanisms that determine this chiral selectivity. The simulation system adopted a geometry required for the chemical reaction to occur more frequently with L-alanine than that with D-alanine. For L-alanine, the structure with this geometry was formed by a combination of stable dihedral angles along alanyl phosphate backbone with a canonical RNA structure, where the methyl group of alanine was placed on the opposite side of the approaching 3′-hydroxyl group with respect to the carbonyl plane. For D-alanine, the methyl group and the 3′-hydroxyl group were placed on the same side with respect to the carbonyl plane, which significantly decreased its ability to approach 3′-oxygen close to the carbonyl carbon compared to L-alanine. The mechanism suggested herein can explain experimentally observed chiral preferences.

Many animals show left-right (LR) asymmetric morphology. The mechanisms of LR asymmetric development are evolutionarily divergent, and they remain elusive in invertebrates. Various organs in Drosophila melanogaster show stereotypic LR asymmetry, including the embryonic gut. The Drosophila embryonic hindgut twists 90° left-handedly, thereby generating directional LR asymmetry. We recently revealed that the hindgut epithelial cell is chiral in shape and other properties; this is termed planar cell chirality (PCC). We previously showed by computer modeling that PCC is sufficient to induce the hindgut rotation. In addition, both the PCC and the direction of hindgut twisting are reversed in Myosin31DF (Myo31DF) mutants. Myo31DF encodes Drosophila MyosinID, an actin-based motor protein, whose molecular functions in LR asymmetric development are largely unknown. Here, to understand how PCC directs the asymmetric cell-shape, we analyzed PCC in genetic mosaics composed of cells homozygous for mutant Myo31DF, some of which also overexpressed wild-type Myo31DF. Wild-type cell-shape chirality only formed in the Myo31DF-overexpressing cells, suggesting that cell-shape chirality was established in each cell and reflects intrinsic PCC. A computer model recapitulating the development of this genetic mosaic suggested that mechanical interactions between cells are required for the cell-shape behavior seen in vivo. Our mosaic analysis also suggested that during hindgut rotation in vivo, wild-type Myo31DF suppresses the elongation of cell boundaries, supporting the idea that cell-shape chirality is an intrinsic property determined in each cell. However, the amount and distribution of F-actin and Myosin II, which are known to help generate the contraction force on cell boundaries, did not show differences between Myo31DF mutant cells and wild-type cells, suggesting that the static amount and distribution of these proteins are not involved in the suppression of cell-boundary elongation. Taken together, our results suggest that cell-shape chirality is intrinsically formed in each cell, and that mechanical force from intercellular interactions contributes to its formation and/or maintenance.

The cytoplasm of a cell is crowded with many different kinds of macromolecules. The macromolecular crowding affects the thermodynamics and kinetics of biological reactions in a living cell, such as protein folding, association, and diffusion. Theoretical and simulation studies using simplified models focus on the essential features of the crowding effects and provide a basis for analyzing experimental data. In most of the previous studies on the crowding effects, a uniform crowder size is assumed, which is in contrast to the inhomogeneous size distribution of macromolecules in a living cell. Here, we evaluate the free energy changes upon macromolecular association in a cell-like inhomogeneous crowding system via a theory of hard-sphere fluids and free energy calculations using Brownian dynamics trajectories. The inhomogeneous crowding model based on 41 different types of macromolecules represented by spheres with different radii mimics the physiological concentrations of macromolecules in the cytoplasm of Mycoplasma genitalium. The free energy changes of macromolecular association evaluated by the theory and simulations were in good agreement with each other. The crowder size distribution affects both specific and non-specific molecular associations, suggesting that not only the volume fraction but also the size distribution of macromolecules are important factors for evaluating in vivo crowding effects. This study relates in vitro experiments on macromolecular crowding to in vivo crowding effects by using the theory of hard-sphere fluids with crowder-size heterogeneity.

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology. DOI: http://dx.doi.org/10.7554/eLife.19274.001, eLife digest Much of the work that has been done to understand how cells work has involved studying parts of a cell in isolation. This is particularly true of studies that have examined the arrangement of atoms in large molecules with elaborate structures like proteins or DNA. However, cells are densely packed with many different molecules and there is little proof that proteins keep the same structures inside cells that they have when they are studied alone. To really understand how cells work, new ways to understand how molecules behave inside cells are needed. While this cannot be achieved directly, technology has now reached the stage where we can, to some extent, study living cells by recreating them virtually. Simulated cells can copy the atomic details of all the molecules in a cell and can estimate how different molecules might behave together. Yu et al. have now developed a computer simulation of part of a cell from the bacterium, Mycoplasma genitalium, one of the simplest forms of life on Earth. This model suggested new possible interactions between molecules inside cells that cannot currently be studied in real cells. The model shows that some proteins have a much less rigid structure in cells than they do in isolation, whilst others are able to work together more closely to carry out certain tasks. Finally, the model predicted that small molecules such as food, water and drugs would move more slowly through cells as they become stuck or trapped by larger molecules. These results could be particularly important in helping to improve drug design. Currently the simulations are limited, and can only model parts of simple cells for less than a thousandth of a second. However, in future it should be possible to recreate larger and more complex cells, including human cells, for longer periods of time. These could be used to better study human diseases and help to design new treatments. The ultimate goal is to simulate a whole cell in full detail by combining all the available experimental data. DOI: http://dx.doi.org/10.7554/eLife.19274.002

Elucidating the global and local rules that govern genome-wide, hierarchical chromatin architecture remains a critical challenge. Current high-throughput chromosome conformation capture (Hi-C) technologies have identified large-scale chromatin structural motifs, such as topologically associating domains and looping. However, structural rules at the smallest or nucleosome scale remain poorly understood. Here, we coupled nucleosome-resolved Hi-C technology with simulated annealing-molecular dynamics (SA-MD) simulation to reveal 3D spatial distributions of nucleosomes and their genome-wide orientation in chromatin. Our method, called Hi-CO, revealed distinct nucleosome folding motifs across the yeast genome. Our results uncovered two types of basic secondary structural motifs in nucleosome folding: α-tetrahedron and β-rhombus analogous to α helix and β sheet motifs in protein folding. Using mutants and cell-cycle-synchronized cells, we further uncovered motifs with specific nucleosome positioning and orientation coupled to epigenetic features at individual loci. By illuminating molecular-level structure-function relationships in eukaryotic chromatin, our findings establish organizational principles of nucleosome folding.

Hydrodynamic interactions (HI) give rise to collective motions between molecules, which are known to be important in the dynamics of random coil polymers and colloids. However, their role in the biological self-assembly of many molecule systems has not been investigated. Here, using Brownian dynamics simulations, we evaluate the importance of HI on the kinetics of self-assembly of lipid membranes. One-thousand coarse-grained lipid molecules in periodic simulation boxes were allowed to assemble into stable bilayers in the presence and absence of intermolecular HI. Hydrodynamic interactions reduce the monomer-monomer association rate by 50%. In contrast, the rate of association of lipid clusters is much faster in the presence of intermolecular HI. In fact, with intermolecular HI, the membrane self-assembly rate is 3–10 times faster than that without intermolecular HI. We introduce an analytical model to describe the size dependence of the diffusive encounter rate of particle clusters, which can qualitatively explain our simulation results for the early stage of the membrane self-assembly process. These results clearly suggest that HI greatly affects the kinetics of self-assembly and that simulations without HI will significantly underestimate the kinetic parameters of such processes.

The effect of macromolecular crowding on protein diffusion has been extensively studied in order to understand the protein dynamics in cellular environments. Previous studies have generally focused on proteins as crowding agents as they are known to occupy 20-30% of the cell volume. The volume fraction of the nucleoid in bacterial cells is also significant, around 10-20%, but the effect of chromosomal DNA as a crowding agent on protein diffusion has drawn relatively limited attention. Using recently build high-resolution models of bacterial nucleoids, Brownian and Stokesian dynamics simulations of coarse-grained model systems containing chromosomal DNA and proteins were carried out to investigate the effect of nucleoid crowding on protein diffusion. The coarse-grained model for the nucleoid is an experimentally-derived 3D model of the Caulobacter crescentus chromosome at base-pair resolution built by combining topological information of chromosomal DNA with distance restraints obtained from high-throughput Chromosome Conformation Capture (HiC) experiments, while proteins in the systems are modeled as hard-spheres. Results show that diffusion of proteins are slower around the nucleoid compared to in protein crowding and that there is size-dependent exclusion of proteins from the chromosome interior. Further analysis was carried to examine the degree of anomalous diffusion at different time and length scales.

To begin to elucidate the principles of intermolecular dynamics in the crowded environment of cells, employing Brownian dynamics (BD) simulations, we examined possible mechanism(s) responsible for the great reduction in diffusion constants of macromolecules in vivo from that at infinite dilution. In an Escherichia coli cytoplasm model comprised of 15 different macromolecule types at physiological concentrations, BD simulations of molecular-shaped and equivalent sphere representations were performed with a soft repulsive potential. At cellular concentrations, the calculated diffusion constant of GFP is much larger than experiment, with no significant shape dependence. Next, using the equivalent sphere system, hydrodynamic interactions (HI) were considered. Without adjustable parameters, the in vivo experimental GFP diffusion constant was reproduced. Finally, the effects of nonspecific attractive interactions were examined. The reduction in diffusivity is very sensitive to macromolecular radius with the motion of the largest macromolecules dramatically slowed down; this is not seen if HI dominate. In addition, long-lived clusters involving the largest macromolecules form if attractions dominate, whereas HI give rise to significant, size independent intermolecular dynamic correlations. These qualitative differences provide a testable means of differentiating the importance of HI vs. nonspecific attractive interactions on macromolecular motion in cells.

ブラウン動力学（Brownian Dynamics；BD）法は溶媒を明示的に扱わないため計算を高速化することができる。従来のBD法は水環境でのタンパク質シミュレーションを対象にしていたため、膜タンパク質には適用できなかった。本研究では膜環境をも非明示的に再現することによってBD法を膜タンパク質のシミュレーションに適用できるように拡張した。αヘリックス構造のポリアラニンペプチドやパピロマーウイルス由来のE5タンパク質、蜂毒のメリチンをモデルとしてシミュレーションした結果、疎水性であるポリアラニンとE5膜タンパク質は膜中で安定に存在した。また、両親媒性であるメリチンペプチドは膜表面に安定に結合していた。これらの結果から、本膜モデルを用いたBD法は膜タンパク質のシミュレーションに有効であると考えられる。

Chromatin dynamics and arrangement are involved in many biological processes in nuclei of eukaryotes including plants. Plants have to respond rapidly to various environmental stimuli to achieve growth and development because they cannot move. It is assumed that the alteration of chromatin dynamics and arrangement support the response to these stimuli; however, there is little information in plants. In this study, we investigated the chromatin dynamics and arrangement with DNA damage in Arabidopsis thaliana by live-cell imaging with the lacO/LacI-EGFP system and simulation analysis. It was revealed that homologous loci kept a constant distance in nuclei of A. thaliana roots in general growth. We also found that DNA double-strand breaks (DSBs) induce the approach of the homologous loci with γ-irradiation. Furthermore, AtRAD54, which performs an important role in the homologous recombination repair pathway, was involved in the pairing of homologous loci with γ-irradiation. These results suggest that homologous loci approach each other to repair DSBs and AtRAD54 mediates these phenomena.

DNA binding proteins efficiently search for their cognitive sites on long genomic DNA by combining 3D diffusion and 1D diffusion (sliding) along the DNA. Recent experimental results and theoretical analyses revealed that the proteins show a rotation-coupled sliding along DNA helical pitch. Here, we performed Brownian dynamics simulations using newly developed coarse-grained protein and DNA models for evaluating how hydrodynamic interactions between the protein and DNA molecules, binding affinity of the protein to DNA, and DNA fluctuations affect the one dimensional diffusion of the protein on the DNA. Our results indicate that intermolecular hydrodynamic interactions reduce 1D diffusivity by 30%. On the other hand, structural fluctuations of DNA give rise to steric collisions between the CG-proteins and DNA, resulting in faster 1D sliding of the protein. Proteins with low binding affinities consistent with experimental estimates of non-specific DNA binding show hopping along the CG-DNA. This hopping significantly increases sliding speed. These simulation studies provide additional insights into the mechanism of how DNA binding proteins find their target sites on the genome., Author Summary DNA binding proteins efficiently search for their cognitive sites on long genomic DNA in cells to control biological activities. Recent experimental studies have revealed that the proteins use not only three-dimensional diffusion, but also one-dimensional diffusion (sliding) on DNA for this search process. For a better understanding of this biological process, we need to elucidate the mechanism of sliding. We report here molecular simulations using newly developed coarse-grained protein and DNA models for elucidating the nature of the sliding motions. Our simulation results show that: 1) hydrodynamic interactions between protein and DNA reduce sliding rate by 30%, 2) structural fluctuations of DNA give rise to steric collisions between proteins and DNA, which facilitate sliding motions, and 3) proteins with low binding affinities to DNA can hop along the DNA, resulting in a significant increase in sliding speed. These simulation studies provide additional insights into the mechanism of how DNA binding proteins find their target sites on the genome.

Structural genomics projects are beginning to produce protein structures with unknown functions, thereby creating a need for high-throughput methods to predict functions. Although sequence-based function prediction methods have been used extensively, structure-based prediction is believed to provide higher specificity and sensitivity because functions are closely related to the three-dimensional structures of functional sites, which are more strongly conserved during evolution than sequence. We have developed FCANAL, a method to predict functions using a score matrix obtained from the distances between Cα atoms and frequencies of appearance [1]. The previous report used key residues predicted from sequence comparisons (motifs). In this report, we have expanded the method to include enzymes and binding proteins with key residues predicted on the basis of three-dimensional structures. Using FCANAL, we constructed score matrices for 31 enzymes. When we applied them to all of the structure entries deposited in the Protein Data Bank, FCANAL could detect functional sites with high accuracy. This suggests that FCANAL will help identify the functions of newly determined structures and pinpoint their functionally important regions.

A new simple implicit solvent model, effective charge (EC) model, was introduced into the Brownian dynamics algorithm based on AMBER united-atom force field. In the EC model, an atomic charge was decreased as a function of solvent-accessible surface area of the atom. We carried out the Brownian dynamics simulations of a 28-mer ββα fold peptide using four implicit solvent models: a generalized Born/solvent-accessible surface area (GB/SA) model, a solvent-accessible surface area (SA) based solvent model, a SA in combination with distance-dependent dielectric (DD/SA) and the EC combined with DD/SA (DD/SA/EC) model; and the calculated results on structure and dynamics of the peptide were compared with those of molecular dynamics simulation using explicit solvent model. Several artifacts were observed in the simulation using the GB/SA model. On the other hand, simulation using the DD/SA and DD/SA/EC implicit solvent models were free from such artifacts. Especially BD with the DD/SA/EC model gave the most stable trajectory as judged by root mean square deviations from the initial structure without large computational cost.

We developed the object-oriented class library "YLO" to study molecular structures. YLO is written in C++ and composed of a set of classes, which are a kind of program units, resembling subroutines in Fortran. Each class performs a certain job independently in a whole program. YLO deals with non-organic, organic molecules and biological macromolecules. The coordinate file of a molecule is read / written in PDB format. Using the YLO library, one can make various types of application programs efficiently, such as Monte Carlo simulator, Genetic Algorithm optimizer and so on.

We report the implementation of an atomistic Brownian dynamics simulation of proteins. A protein was described by united-atom model with AMBER91 force field. The solvent was treated by distance-dependent dielectric/surface area model. The computation time of the Brownian dynamics and the calculated results on structure and dynamics of 28-mer ββα fold peptide with the implicit solvent model were compared with those of molecular dynamics simulation with explicit solvent. The Brownian dynamics simulation was 53 times faster than molecular dynamics simulation with explicit solvent. The simulation was stable and the artifacts often observed in simulations at vacuum condition were reduced. The results indicate that the Brownian dynamics with the implicit solvent model can be widely used in studies of protein dynamics by long time simulation in future.

The interiors of all living cells are highly crowded with macromolecules, which results in a considerable difference between the thermodynamics and kinetics of biological reactions in vivo from that in vitro. To begin to elucidate the principles of intermolecular dynamics in the crowded environment of cells, employing Brownian dynamics (BD) simulations, we examined possible mechanism(s) responsible for the great reduction in diffusion constants of macromolecules in vivo from that at infinite dilution. In an E. coli cytoplasm modelcomprised of 15 different macromolecule types at physiological concentrations, where macromolecules were represented by spheres with their Stokes radii, BD simulations were performed with and without hydrodynamic interactions (HI). Without HI, the calculated diffusion constant of green fluorescent protein (GFP) is much larger than experiment. On the other hand, when HI were considered, the in vivo experimental GFP diffusion constant is almost reproduced without adjustable parameters. In addition, HI give rise to significant, size independent intermolecular dynamic correlations. These results suggest that HI play an important role on macromolecular dynamics in vivo.

Some organs in animals display left-right (LR) asymmetry. To better understand LR asymmetric morphogenesis in Drosophila, we studied LR directional rotation of the hindgut epithelial tube. Hindgut epithelial cells adopt a LR asymmetric (chiral) cell shape within their plane, and we refer to this cell behavior as planar cell-shape chirality (PCC). Drosophila E-cadherin (DE-Cad) is distributed to cell boundaries with LR asymmetry, which is responsible for the PCC formation. Myosin ID switches the LR polarity found in PCC and in DE-Cad distribution, which coincides with the direction of rotation. An in silico simulation showed that PCC is sufficient to induce the directional rotation of this tissue. Thus, the intrinsic chirality of epithelial cells in vivo is an underlying mechanism for LR asymmetric tissue morphogenesis.

The interiors of all living cells are highly crowded with macromolecules, which differs considerably the thermodynamics and kinetics of biological reactions between in vivo and in vitro. For example, the diffusion of green fluorescent protein (GFP) in E. coli is ~10-fold slower than in dilute conditions. In this study, we performed Brownian dynamics (BD) simulations of rigid macromolecules in a crowded environment mimicking the cytosol of E. coli to study the motions of macromolecules. The simulation systems contained 35 70S ribosomes, 750 glycolytic enzymes, 75 GFPs, and 392 tRNAs in a 100 nm × 100 nm × 100 nm simulation box, where the macromolecules were represented by rigid-objects of one bead per amino acid or four beads per nucleotide models. Diffusion tensors of these molecules in dilute solutions were estimated by using a hydrodynamic theory to take into account the diffusion anisotropy of arbitrary shaped objects in the BD simulations. BD simulations of the system where each macromolecule is represented by its Stokes radius were also performed for comparison. Excluded volume effects greatly reduce the mobility of molecules in crowded environments for both molecular-shaped and equivalent sphere systems. Additionally, there were no significant differences in the reduction of diffusivity over the entire range of molecular size between two systems. However, the reduction in diffusion of GFP in these systems was still 4–5 times larger than for the in vivo experiment. We will discuss other plausible factors that might cause the large reduction in diffusion in vivo.

WL-O系統,WL-B系統及び内在性ウイルス遺伝子の部分発現のある個体群の3群を用いて,内在性ウイルス遺伝子と細胞表面レセプター遺伝子が鶏染色体上でどういう位置関係にあるのかを後代検定法を用いて調査した。その結果,gs抗原とchf活性の分離比はそれぞれの遺伝子座が同一染色体上にある場合の期待値に近く,我々は,少なくとも一対のgag遺伝子とenv遺伝子が同一染色体上にあるものと結論した。そして,これらの遺伝子は,ev-3遺伝子座のGsとgsの対立遺伝子と同じ性質のものであろうと推定した。一方,B亜群ウイルスに対する細胞の感受性と,gs抗原及びchf活性の分離比については,両座位が独立の場合の期待分離比に近いので,B亜群ウイルスに対する細胞のレセプター遺伝子座とこの内在性ウイルス遺伝子座とは異なる染色体上にあるものと思われた。

鶏白血病ウイルス(ALV)抗体測定法としての酵素抗体法(ELISA)について抗原抗体反応系の解析を行い,さらに血清中和法(SN),蛍光抗体法(FA)との相関関係と感度の比較を行った。1)A亜群,B亜群2種の抗原に対する抗体価の推移をELISA,SN,FAで確認すると,ELISA,FAでは主として群特異抗体(gs抗体)を,SNは亜群特異抗体を検出していると思われた。2)gs抗体を産生する抗原成分として3種の蛋白が確認された。そして,それぞれに対する抗体の発現順序は,まずp27,つぎにgp85,さらにp15に対する抗体であった。3)1野外鶏群について,3種の測定方法で算出した抗体価の関係を見ると,いずれにも相関が認められた。4)測定方法による検出感度を比較すると,ELISAは,SNの約10倍,FAはSNとほぼ同感度であった。

BACKGROUND Although transurethral resection of a bladder tumor (TUR-Bt) alone has been standard treatment for single superficial bladder carcinoma, some authors reported a certain prophylactic effect of a single immediate intravesical instillation of chemotherapeutic agent after TUR-Bt. A prospective randomized study was conducted to determine whether a single (2″R)-4′-O-tetrahydropyranyl-doxorubicin (THP) instillation immediately after TUR-Bt is beneficial to patients with a single superficial bladder carcinoma. METHODS One hundred seventy patients with a single resectable superficial bladder carcinoma (Ta-1, primary or recurrent with no recurrence during the last 1 year) were enrolled in this study. THP (30 mg/30 mL of normal saline) was administered into the bladder within 6 hours after TUR-Bt in arm A, while TUR-Bt alone was done in arm B. RESULTS Of the 170 patients, 160 (94.1%) were eligible and were followed up for a median time of 40.8 months. There was a significant difference in the recurrence free curve between the 2 arms (log-rank test; P = 0.0026), with 92.4% recurrence free rate at 1 year, 82.7% at 2 years, and 78.8% at 3 years in arm A (84 patients) and 67.0%, 55.7%, and 52.6%, respectively, in arm B. The recurrence rate per year was 0.11 ± 0.22 in arm A and 0.24 ± 0.36 in arm B, with a significant difference (P = 0.007). Toxicity included pain with micturition in 9 patients (10.7%), urinary frequency/urgency in 5 patients (6.0%), and macroscopic hematuria in 7 patients (8.3%). CONCLUSIONS These data indicate that a single THP instillation immediately after TUR reduces the recurrence of superficial bladder carcinoma. Cancer 2002;94:2363–8. © 2002 American Cancer Society. DOI 10.1002/cncr.10496

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a brownian dynamics simulation. However, the calculation of correlated brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N(2)) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the "block" version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10,000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale brownian dynamics simulations with hydrodynamic interactions.

Self-organization is one of the most fundamental phenomena in biology. Elucidating the mechanisms of the self-assembly of biological molecules, such as protein folding/binding and formation of lipid bilayer membranes, have been a fascinating topic over decades in biological field. Hydrodynamic interactions (HIs) give rise to collective motions between molecules. Therefore, they may play an important role on dynamics of self-assembly. Although there are significant advances in theoretical and computational studies on thermodynamics and kinetics of self-assembling systems recent years, analysis on effects of HIs to the reactions are limited due to their high complexity. Here, by using a Brownian dynamics (BD) simulation technique, we evaluate the importance of HIs on kinetic of self-assembly in a set of examples, formation of lipid membrane and actin polymerization reaction. We first built coarse-grained models of lipid and actin monomer. A cluster of lipid molecules was represented by two particles, one is hydrophilic head group and the other is hydrophobic tail group, and attractive interaction between tail groups was applied. For actin polymerization system, each monomer was represented by two particles and an angle-dependent attractive interaction was applied to form long filaments. In BD simulations, the Rotne-Prager-Yamakawa tensor was used to account for HIs between particles. In the early stage of self-assembly, HIs between inter-monomer particles decelerated the association rate of monomers to form oligomers compared with that in the simulations without inter-monomer HIs in both systems. On the other hand, the HIs accelerate the reaction of oligomers to form a fully-assembled state or much longer polymers. This phenomenon could be explained by the Kirkwood-Riseman theory. Those results clearly suggest that HIs greatly affect kinetics of self-assembly reactions and considering the interactions is crucial for studying dynamics of biological systems.

In order to demonstrate that the extracorporeal shockwave lithotripsy (ESWL) for urolithiasis causes a renal damage, we immunoassayed S100a0 protein and creatine kinase isozymes (CK-B & CK-M) in the serum and urine from patients with renal stone (N = 21) and those with ureteral stone (N = 18) before and after ESWL. S100a0 protein and CK-B, which are localized in the proximal renal tubules at relatively high concentrations, were enhanced more or less both in the urine and serum samples after the treatment in both groups of patients. Since CK-M, which is mainly localized in muscle tissue, also increased in both groups of patients, S100a0 protein and CK-B may be derived not only from kidney, but also from muscle tissues.