A theoretical investigation of the characteristics of hydrogen/halogen bonding interactions in dibromo-nitroaniline

In this work, computations of density functional theory (DFT) were carried out to investigate the nature of interactions in solid 2,6-dibromo-4-nitroaniline (DBNA). This system was selected to mimic the hydrogen/halogen bonding found within crystal structures as well as within biological molecules. DFT (M06-2X/6-311++G**) calculations indicated that the binding energies for different of interactions lie in the range between ?1.66 and ?9.77 kcal mol^?1. The quantum theory of atoms in molecules (QTAIM) was applied to provide more insight into the nature of these interactions. Symmetry-adapted perturbation theory (SAPT) analysis indicated that stability of the Br···Br halogen bonds is predicted to be attributable mainly to dispersion, while electrostatic forces, which have been widely believed to be responsible for these types of interactions, play a smaller role. Our results indicate that, for those nuclei participating in hydrogen/halogen bonding interactions, nuclear quadrupole resonance parameters exhibit considerable changes on going from the isolated molecule model to crystalline DBNA.

The effect of tissue-engineered cartilage biomechanical and biochemical properties on its post-implantation mechanical behavior

The insufficient load-bearing capacity of today’s tissue-engineered (TE) cartilage limits its clinical application. Focus has been on engineering cartilage with enhanced mechanical stiffness by reproducing native biochemical compositions. More recently, depth dependency of the biochemical content and the collagen network architecture has gained interest. However, it is unknown whether the mechanical performance of TE cartilage would benefit more from higher content of biochemical compositions or from achieving an appropriate collagen organization. Furthermore, the relative synthesis rate of collagen and proteoglycans during the TE process may affect implant performance. Such insights would assist tissue engineers to focus on those aspects that are most important. The aim of the present study is therefore to elucidate the relative importance of implant ground substance stiffness, collagen content, and collagen architecture of the implant, as well as the synthesis rate of the biochemical constituents for the post-implantation mechanical behavior of the implant. We approach this by computing the post-implantation mechanical conditions using a composition-based fibril-reinforced poro-viscoelastic swelling model of the medial tibia plateau. Results show that adverse implant composition and ultrastructure may lead to post-implantation excessive mechanical loads, with collagen orientation being the most critical variable. In addition, we predict that a faster synthesis rate of proteoglycans compared to that of collagen during TE culture may result in excessive loads on collagen fibers post-implantation. This indicates that even with similar final contents, constructs may behave differently depending on their development. Considering these aspects may help to engineer TE cartilage implants with improved survival rates.     

A Hybrid Likelihood Model for Sequence-Based Disease Association Studies

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.     

Evolutionarily conserved motifs and modules in mitochondrial protein–protein interaction networks

Advances in organelle interactomics have led to new insights into organelle functions. In this study, we considered the common mitochondrial PIN of four evolutionarily distant eukaryotic species, namely Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans. By comparative interactomics analysis of mitochondrial PINs in these organisms, five conserved modules were identified. Modules comprise the main mitochondrial tasks, including proteins involved in translation process, mitochondrial import inner membrane proteins, TCA cycle enzymes, mitochondrial electron transport chain, and metabolic enzymes. Furthermore, we reemphasize that subgraphs of network, i.e., motifs and themes, may represent evolutionarily conserved topological units which are biologically significant.     

Bovine serum albumin/gold nanoparticles as a drug delivery system for Curcumin: experimental and computational studies

Abstract

Communicated by Ramaswamy H. Sarma     

Simultaneous impact of atorvastatin and mesenchymal stem cells for glioblastoma multiform suppression in rat glioblastoma multiform model

Glioblastoma multiform (GBM) is known as an aggressive glial neoplasm. Recently incorporation of mesenchymal stem cells with anti-tumor drugs have been used due to lack of immunological responses and their easy accessibility. In this study, we have investigated the anti-proliferative and apoptotic activity of atorvastatin (Ator) in combination of mesenchymal stem cells (MSCs) on GBM cells in vitro and in vivo. The MSCs isolated from rats and characterized for their multi-potency features. The anti-proliferative and migration inhibition of Ator and MSCs were evaluated by MTT and scratch migration assays. The annexin/PI percentage and cell cycle arrest of treated C6 cells were evaluated until 72 h incubation. The animal model was established via injection of C6 cells in the brain of rats and subsequent injection of Ator each 3 days and single injection of MSCs until 12 days. The growth rate, migrational phenotype and cell cycle progression of C6 cells decreased and inhibited by the interplay of different factors in the presence of Ator and MSCs. The effect of Ator and MSCs on animal models displayed a significant reduction in tumor size and weight. Furthermore, histopathology evaluation proved low hypercellularity and mitosis index as well as mild invasive tumor cells for perivascular cuffing without pseudopalisading necrosis and small delicate vessels in Ator?+?MSCs condition. In summary, Ator and MSCs delivery to GBM model provides an effective strategy for targeted therapy of brain tumor.

     

Rational MD simulations for improvement the affinity of nanobody against PlGF (placenta growth factor): mutagenesis based on electrostatic interactions

Abbreviations COM center of mass distance

MD molecular dynamics

MM-PBSA Molecular Mechanics Poisson–Boltzmann Surface Area

Nb nanobody

PlGF placenta growth factor

Rg radius of gyration

RMSD root mean-square deviation

SASA solvent-accessible surface area

VEGF vascular endothelial growth factor