On the Modularity of the Intrinsic Flexibility of the μ Opioid Receptor: A Computational Study

The µ opioid receptor (µOR), the principal target to control pain, belongs to the G protein-coupled receptors (GPCRs) family, one of the most highlighted protein families due to their importance as therapeutic targets. The conformational flexibility of GPCRs is one of their essential characteristics as they take part in ligand recognition and subsequent activation or inactivation mechanisms. It is assessed that the intrinsic mechanical properties of the µOR, more specifically its particular flexibility behavior, would facilitate the accomplishment of specific biological functions, at least in their first steps, even in the absence of a ligand or any chemical species usually present in its biological environment. The study of the mechanical properties of the µOR would thus bring some indications regarding the highly efficient ability of the µOR to transduce cellular message. We therefore investigate the intrinsic flexibility of the µOR in its apo-form using all-atom Molecular Dynamics simulations at the sub-microsecond time scale. We particularly consider the µOR embedded in a simplified membrane model without specific ions, particular lipids, such as cholesterol moieties, or any other chemical species that could affect the flexibility of the µOR. Our analyses highlighted an important local effect due to the various bendability of the helices resulting in a diversity of shape and volume sizes adopted by the µOR binding site. Such property explains why the µOR can interact with ligands presenting highly diverse structural geometry. By investigating the topology of the µOR binding site, a conformational global effect is depicted: the correlation between the motional modes of the extra- and intracellular parts of µOR on one hand, along with a clear rigidity of the central µOR domain on the other hand. Our results show how the modularity of the µOR flexibility is related to its pre-ability to activate and to present a basal activity.     

Statistical evaluation of sister chromatid exchanges

Summary Log-linear models are fitted to sister chromatid exchange (SCE) scores in order to test the significance of the differences in SCE scores observed between individuals or between experimental treatments. The analysis is performed at the level of chromosome groups. In each single test all measurements from all chromosome groups, both from the control and from the experimental sets, are utilized. By proceeding in this way full use is made of all the available information on the SCE scores at the level of chromosome groups and the shortcomings of the classical Student-t and chi-square tests are avoided.This work was supported by a grant Geconcerteerde Acties from the Belgian Government.     

Characterization of the efficiency of a cell separation process by the extent of elimination of a contaminating cell type

A stepwise approach to the selection of an appropriate technique for a cell separation problem is presented in which the preparative purification of cells is linked to their analytical separation. We have introduced the extent of elimination of a contaminating cell type from the cell type which one chooses to purify, as a separation parameter that characterizes the efficiency of a separation process independently of the relative cell composition of the starting material. In order to compare different separation techniques, a preparative fraction boundary needs to be chosen between the cell types. We defined this boundary in terms of the physical property on which the separation is based such that yield and purity of the isolated cell suspension are optimized simultaneously. With this analytical approach, it was found that a similar elutriation technique separated human and equine mononuclear cells equally well and that the separability of human monocytes and lymphocytes improved when the cells were separated by increasing the limiting sedimentation coefficient value of the elutriation chamber in small increments.     

Interaction of K+ ion with the solvated gramicidin A transmembrane channel.

Using Urry's gramicidin A (GA) atomic coordinates and ab into calculations, the interaction energies of a K+ ion with GA are examined. From these energies the values of the fitting parameters are obtained for 6-12-1 atom-atom pair potentials. The potential of the GA channel as experienced by the ion is analyzed in detail. An energy profile of the K+ ion in the GA channel is obtained by analyzing iso-energy maps. Using Monte Carlo simulations, the energy profiles of the K+ ion with the solvated GA channel are analyzed and the hydration structures in the presence of the K+ ion are studied.     

Evaluating molecular similarity using reduced representations of the electron density

A model system of four benzodiazepine-like ligands for the central benzodiazepine receptors (CBRs) and peripheral benzodiazepine receptors (PBRs)is examined using a genetic algorithm procedure (GAGS) designed for evaluating molecular similarity. The method is based on the alignment of reduced representations generated from the critical points of the electron density computed at medium crystallographic resolution. The results are further characterized by a comparison with alignments produced by MIMIC, a field-based superimposition method that matches both steric and electrostatic molecular fields. The alignments produced by the two methods are generally seen to be consistent. The relationships of the compounds' binding affinities for both CBRs and PBRs to the alignments determined by GAGS yield a set of structural features required for significant binding to benzodiazepine receptors. Benefits of using reduced representations for evaluating molecular similarities and for constructing pharmacophore models are discussed.     

Privacy-preserving logistic regression training

Background

Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appealing idea to outsource this computation to a cloud service. The privacy-sensitive nature of the input data requires appropriate privacy preserving measures before outsourcing it. Homomorphic encryption enables one to compute on encrypted data directly, without decryption and can be used to mitigate the privacy concerns raised by using a cloud service.

Methods

In this paper, we propose an algorithm (and its implementation) to train a logistic regression model on a homomorphically encrypted dataset. The core of our algorithm consists of a new iterative method that can be seen as a simplified form of the fixed Hessian method, but with a much lower multiplicative complexity.

Results

We test the new method on two interesting real life applications: the first application is in medicine and constructs a model to predict the probability for a patient to have cancer, given genomic data as input; the second application is in finance and the model predicts the probability of a credit card transaction to be fraudulent. The method produces accurate results for both applications, comparable to running standard algorithms on plaintext data.

Conclusions

This article introduces a new simple iterative algorithm to train a logistic regression model that is tailored to be applied on a homomorphically encrypted dataset. This algorithm can be used as a privacy-preserving technique to build a binary classification model and can be applied in a wide range of problems that can be modelled with logistic regression. Our implementation results show that our method can handle the large datasets used in logistic regression training.

     

Quinazoline-2,4(1H,3H)-dione as a substitute for thymine in triple-helix forming oligonucleotides: a reassessment.

A major limitation in triple-helix formation arises from the weak energy of interaction between the third strand and the double-stranded target. We tried to increase the stacking interaction contribution within the third strand by extending the aromatic domain of thymine. We report here the use of 2,4-quinazolinedione as a substitute for thymine in the canonical TA*T triplet. The synthesis and the characterization of the quinazoline beta nucleoside Q and of its phosphoramidite derivative is described. Triple-helix- forming oligonucleotides incorporating Q have been prepared and their ability to form triplexes has been evaluated by UV-monitored thermal denaturation measurements. The introduction of one or multiple Q residues, either contiguous or remote from each other, slightly destabilized triple-stranded structures, whatever the nucleic acid base composition (pyrimidine or GT) of the third strand.     

Water structure in the Gramicidin A transmembrane channel

The interaction energy and the structure of water molecules either inside the Gramicidin A transmembrane channel or at its two extremities is examined with the use of iso-energy maps and Monte Carlo simulations. The shape of the channel as experienced by water is analyzed in detail. Variations in the hydration structure due to the presence of a sodium ion placed at several positions along the channel are simulated, analyzed and discussed. Preliminary data on Li+ and K+ interacting with Gramicidin A and the system of water molecules are reported. The Gramicidin A atomic coordinates have been taken from Urry's recent papers (Urry, D.W. (1971) Proc. Natl. Acad. Sci. U.S.A. 68, 672-676 and Urry, D.W., Trapane, T.L. and Prasad, K.U. (1982) Int. J. Quant. Chem. Quant. Biol. Symp. 9, 31-40).