MPK-09, a small molecule inspired from bioactive styryllactone restores the wild-type function of mutant p53

In the search for more efficacious and less toxic cancer drugs, the tumor suppressor p53 protein has long been a desirable therapeutic target. In the recent past, few independent studies have demonstrated that the antitumor activity of wild-type p53 can be restored in cancer cells harboring mutant form of p53 using small molecule activators. In this study, we describe a novel small molecule MPK-09, which is selective and highly potent against allele specific p53 mutations mainly, R175H, R249S, R273H, R273C, and E285K. Except E285K, all other mutations tested are among the six ``hot spot'' p53 mutations reported in majority of human cancer. Furthermore, our study conclusively demonstrates that the apoptotic activity of the small molecule MPK-09 against cancer cells harboring R273C and E285K mutations is due to restoration of the wild-type conformation to the corresponding mutant form of p53.

Role of silica nanoparticles in conductivity enhancement of nanocomposite solid polymer electrolytes: (PEG(x) NaBr): ySiO(2)

Nanocomposite solid polymer electrolytes (NCSPEs) with conducting species other than Li ions are being investigated for solid-state battery applications. Pristine solid polymer electrolytes (SPEs) do not show ionic conductivity suitable for batteries. Addition of inert fillers to SPEs is known to enhance the ionic conductivity. In this paper, we present the role of silica nanoparticles in enhancing the ionic conductivity in NCSPEs with sodium as conducting species. Sodium bromide is complexed with the host polyethylene glycol polymer by solution cast method and silica nanoparticles (SiO2, average particle size 7 nm) are incorporated into the complex in small amounts. The composites are characterized by powder XRD and IR spectroscopy. Conductivity measurements are undertaken as a function of concentration of salt and also as a function of temperature using impedance spectroscopy. Addition of silica nanoparticles shows an enhancement in conductivity by 1-2 orders of magnitude. The results are discussed in terms of interaction of nanoparticles with the nonconducting anions.

Identification and characterization of starvation induced msdgc-1 promoter involved in the c-di-GMP turnover

C-di-GMP Bis-(3'-5')-cyclic-dimeric-guanosine monophosphate], a second messenger is involved in intracellular communication in the bacterial species. As a result several multi-cellular behaviors in both Gram-positive and Gram-negative bacteria are directly linked to the intracellular level of c-di-GMP. The cellular concentration of c-di-GMP is maintained by two opposing activities, diguanylate cyclase (DGC) and phosphodiesterase (PDE-A). In Mycobacterium smegmatis, a single bifunctional protein MSDGC-1 is responsible for the cellular concentration of c-di-GMP. A better understanding of the regulation of c-di-GMP at the genetic level is necessary to control the function of above two activities. In this work, we have characterized the promoter element present in msdgc-1 along with the + 1 transcription start site and identified the sigma factors that regulate the transcription of msdgc-1. Interestingly, msdgc-1 utilizes SigA during the initial phase of growth, whereas near the stationary phase SigB containing RNA polymerase takes over the expression of msdgc-1. We report here that the promoter activity of msdgc-1 increases during starvation or depletion of carbon source like glucose or glycerol. When msdgc-1 is deleted, the numbers of viable cells are similar to 10 times higher in the stationary phase in comparison to that of the wild type. We propose here that msdgc-1 is involved in the regulation of cell population density. (C) 2013 Elsevier B.V. All rights reserved.

Shape-function-relationship (SFR) framework for semantic interoperability of product model

The problem of semantic interoperability arises while integrating applications in different task domains across the product life cycle. A new shape-function-relationship (SFR) framework is proposed as a taxonomy based on which an ontology is developed. Ontology based on the SFR framework, that captures explicit definition of terminology and knowledge relationships in terms of shape, function and relationship descriptors, offers an attractive approach for solving semantic interoperability issue. Since all instances of terms are based on single taxonomy with a formal classification, mapping of terms requires a simple check on the attributes used in the classification. As a preliminary study, the framework is used to develop ontology of terms used in the aero-engine domain and the ontology is used to resolve the semantic interoperability problem in the integration of design and maintenance. Since the framework allows a single term to have multiple classifications, handling context dependent usage of terms becomes possible. Automating the classification of terms and establishing the completeness of the classification scheme are being addressed presently.

Mechanistic Insights into the Neutralization of Cytotoxic Abrin by the Monoclonal Antibody D6F10

Abrin, an A/B toxin obtained from the Abrus precatorius plant is extremely toxic and a potential bio-warfare agent. Till date there is no antidote or vaccine available against this toxin. The only known neutralizing monoclonal antibody against abrin, namely D6F10, has been shown to rescue the toxicity of abrin in cells as well as in mice. The present study focuses on mapping the epitopic region to understand the mechanism of neutralization of abrin by the antibody D6F10. Truncation and mutational analysis of abrin A chain revealed that the amino acids 74-123 of abrin A chain contain the core epitope and the residues Thr112, Gly114 and Arg118 are crucial for binding of the antibody. In silico analysis of the position of the mapped epitope indicated that it is present close to the active site cleft of abrin A chain. Thus, binding of the antibody near the active site blocks the enzymatic activity of abrin A chain, thereby rescuing inhibition of protein synthesis by the toxin in vitro. At 1: 10 molar concentration of abrin: antibody, the antibody D6F10 rescued cells from abrin-mediated inhibition of protein synthesis but did not prevent cell attachment of abrin. Further, internalization of the antibody bound to abrin was observed in cells by confocal microscopy. This is a novel finding which suggests that the antibody might function intracellularly and possibly explains the rescue of abrin's toxicity by the antibody in whole cells and animals. To our knowledge, this study is the first report on a neutralizing epitope for abrin and provides mechanistic insights into the poorly understood mode of action of anti-A chain antibodies against several toxins including ricin.

Confinement induced stochastic sensing of charged coronene and perylene aggregates in alpha-hemolysin nanochannels

Biological nanopores provide optimum dimensions and an optimal environment to study early aggregation kinetics of charged polyaromatic molecules in the nano-confined regime. It is expected that probing early stages of nucleation will enable us to design a strategy for supramolecular assembly and biocrystallization processes. Specifically, we have studied translocation dynamics of coronene and perylene based salts, through the alpha-hemolysin (alpha-HL) protein nanopore. The characteristic blocking events in the time-series signal are a function of concentration and bias voltage. We argue that different blocking events arise due to different aggregation processes as captured by all atomistic molecular dynamics (MD) simulations. These confinement induced aggregations of polyaromatic chromophores during the different stages of translocation are correlated with the spatial symmetry and charge distribution of the molecules.

The Lovasz θ function, SVMs and finding large dense subgraphs

The Lovasz θ function of a graph, is a fundamental tool in combinatorial optimization and approximation algorithms. Computing θ involves solving a SDP and is extremely expensive even for moderately sized graphs. In this paper we establish that the Lovasz θ function is equivalent to a kernel learning problem related to one class SVM. This interesting connection opens up many opportunities bridging graph theoretic algorithms and machine learning. We show that there exist graphs, which we call SVM−θ graphs, on which the Lovasz θ function can be approximated well by a one-class SVM. This leads to a novel use of SVM techniques to solve algorithmic problems in large graphs e.g. identifying a planted clique of size Θ(n√) in a random graph G(n,12). A classic approach for this problem involves computing the θ function, however it is not scalable due to SDP computation. We show that the random graph with a planted clique is an example of SVM−θ graph, and as a consequence a SVM based approach easily identifies the clique in large graphs and is competitive with the state-of-the-art. Further, we introduce the notion of a ''common orthogonal labeling'' which extends the notion of a ''orthogonal labelling of a single graph (used in defining the θ function) to multiple graphs. The problem of finding the optimal common orthogonal labelling is cast as a Multiple Kernel Learning problem and is used to identify a large common dense region in multiple graphs. The proposed algorithm achieves an order of magnitude scalability compared to the state of the art.