Histone deacetylase inhibitors (HDACIs) are therapeutic drugs that inhibit deacetylase activity, thereby increasing acetylation of many proteins, including histones. HDACIs have antineoplastic effects in preclinical and clinical trials and are being considered for cancers with unmet therapeutic need, including neuroblastoma (NB). Uncertainty of how HDACI-induced protein acetylation leads to cell death, however, makes it difficult to determine which tumors are likely to be responsive to these agents. Here, we show that NB cells are sensitive to HDACIs, and that the mechanism by which HDACIs induce apoptosis involves Bax. In these cells, Bax associates with cytoplasmic Ku70, a protein that typically increases chemotherapy resistance. Our data show that in NB cells Ku70 binds to Bax in an acetylation-sensitive manner. Upon HDACI treatment, acetylated Ku70 releases Bax, allowing it to translocate to mitochondria and trigger cytochrome c release, leading to caspase-dependent death. This study shows that Ku70 is an important Bax-binding protein, and that this interaction can be therapeutically regulated in NB cells. Whereas the Bax-binding ability of Ku70 allows it to block apoptosis in response to certain agents, it is also a molecular target for the action of HDACIs, and in this context, a mediator of NB cell death.cAMP-response element-binding protein ͉ histone acetyltransferase

The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while the corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model. C 2015 AIP Publishing LLC. [http://dx

We consider the Brownian motion of a particle and present a tutorial review over the last 111 years since Einstein’s paper in 1905. We describe Einstein’s model, Langevin’s model and the hydrodynamic models, with increasing sophistication on the hydrodynamic interactions between the particle and the fluid. In recent years, the effects of interfaces on the nearby Brownian motion have been the focus of several investigations. We summarize various results and discuss some of the controversies associated with new findings about the changes in Brownian motion induced by the interface.

Neuroblastoma is the most common extracranial solid tumor of childhood. N-type neuroblastoma cells (represented by SH-SY5Y and IMR32 cell lines) are characterized by a neuronal phenotype. N-type cell lines are generally N-myc amplified, express the anti-apoptotic protein Bcl-2, and do not express caspase-8. The present study was designed to determine the mechanism by which N-type cells die in response to specific cytotoxic agents (such as cisplatin and doxorubicin) commonly used to treat this disease. We found that N-type cells were equally sensitive to cisplatin and doxorubicin. Yet death induced by cisplatin was inhibited by the nonselective caspase inhibitor z-Val-Ala-Asp-fluoromethylketone or the specific caspase-9 inhibitor N-acetyl-LeuGlu-His-Asp-aldehyde, whereas in contrast, caspase inhibition did not prevent doxorubicin-induced death. Neither the reactive oxygen species nor the mitochondrial permeability transition appears to play an important role in this process. Doxorubicin induced NF-B transcriptional activation in association with I-B␣ degradation prior to loss of cell viability. Surprisingly, the antioxidant and NF-B inhibitor pyrrolidine dithiocarbamate blocked doxorubicin-induced NF-B transcriptional activation and provided profound protection against doxorubicin killing. Moreover, SH-SY5Y cells expressing a super-repressor form of I-B were completely resistant to doxorubicin killing. Together these findings show that NF-B activation mediates doxorubicin-induced cell death without evidence of caspase function and suggest that cisplatin and doxorubicin engage different death pathways to kill neuroblastoma cells.

We present a bottom-up coarse-graining procedure to construct mesoscopic force fields directly from microscopic dynamics. By grouping many bonded atoms in the molecular dynamics (MD) system into a single cluster, we compute both the conservative and non-conservative interactions between neighboring clusters. In particular, we perform MD simulations of polymer melts to provide microscopic trajectories for evaluating coarse-grained (CG) interactions. Subsequently, dissipative particle dynamics (DPD) is considered as the effective dynamics resulting from the Mori-Zwanzig (MZ) projection of the underlying atomistic dynamics. The forces between finite-size clusters have, in general, both radial and transverse components and hence we employ four different DPD models to account differently for such interactions. Quantitative comparisons between these DPD models indicate that the DPD models with MZ-guided force fields yield much better static and dynamics properties, which are consistent with the underlying MD system, compared to standard DPD with empirical formulae. When the rotational motion of the particle is properly taken into account, the entire velocity autocorrelation function of the MD system as well as the pair correlation function can be accurately reproduced by the MD-informed DPD model. Since this coarse-graining procedure is performed on an unconstrained MD system, our framework is general and can be used in other soft matter systems in which the clusters can be faithfully defined as CG particles.

We apply smoothed dissipative particle dynamics (SDPD) [Español and Revenga, Phys. Rev. E 67, 026705 (2003)] to model solid particles in suspension. SDPD is a thermodynamically consistent version of smoothed particle hydrodynamics (SPH) and can be interpreted as a multiscale particle framework linking the macroscopic SPH to the mesoscopic dissipative particle dynamics (DPD) method. Rigid structures of arbitrary shape embedded in the fluid are modeled by frozen particles on which artificial velocities are assigned in order to satisfy exactly the no-slip boundary condition on the solid-liquid interface. The dynamics of the rigid structures is decoupled from the solvent by solving extra equations for the rigid body translational/angular velocities derived from the total drag/torque exerted by the surrounding liquid. The correct scaling of the SDPD thermal fluctuations with the fluid-particle size allows us to describe the behavior of the particle suspension on spatial scales ranging continuously from the diffusion-dominated regime typical of sub-micron-sized objects towards the non-Brownian regime characterizing macro-continuum flow conditions. Extensive tests of the method are performed for the case of two/three dimensional bulk particle-system both in Brownian/non-Brownian environment showing numerical convergence and excellent agreement with analytical theories. Finally, to illustrate the ability of the model to couple with external boundary geometries, the effect of confinement on the diffusional properties of a single sphere within a micro-channel is considered, and the dependence of the diffusion coefficient on the wall-separation distance is evaluated and compared with available analytical results.

We preset a computational study of bending models for the curvature elasticity of lipid bilayer membranes that are relevant for simulations of vesicles and red blood cells. We compute bending energy and forces on triangulated meshes and evaluate and extend four well established schemes for their approximation: Kantor and Nelson [1], Jülicher [2], Gompper and Kroll [3] and Meyer et. al. [4], termed A, B, C, D. We present a comparative study of these four schemes on the minimal bending model and propose extensions for schemes B, C and D. These extensions incorporate the reference state and non-local energy to account for the spontaneous curvature, bilayer coupling, and area-difference elasticity models. Our results indicate that the proposed extensions enhance the models to account for shape transformation including budding/vesiculation as well as for non-axisymmetric shapes. We find that the extended scheme B is superior to the rest in terms of accuracy, and robustness as well as simplicity of implementation. We demonstrate the capabilities of this scheme on several benchmark problems including the budding-vesiculating process and the reproduction of the phase diagram of vesicles.

No abstract