What can light scattering spectroscopy do for membrane-active peptide studies

Highly charged peptides are important components of the immune system and belong to an important family of antibiotics. Although their therapeutic activity is known, most of the molecular level mechanisms are controversial. A wide variety of different approaches are usually applied to understand their mechanisms, but light scattering techniques are frequently overlooked. Yet, light scattering is a noninvasive technique that allows insights both on the peptide mechanism of action as well as on the development of new antibiotics. Dynamic light scattering (DLS) and static light scattering (SLS) are used to measure the aggregation process of lipid vesicles upon addition of peptides and molecular properties (shape, molecular weight). The high charge of these peptides allows electrostatic attraction toward charged lipid vesicles, which is studied by zeta potential (zeta-potential) measurements. Copyright (c) 2008 European Peptide Society and John Wiley & Sons, Ltd.

Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Light scattering on the structural characterization of DMPG vesicles along the bilayer anomalous phase transition

Highly charged vesicles of the saturated anionic lipid dimyristoyl phosphatidylglycerol (DMPG) in low ionic strength medium exhibit a very peculiar thermo-structural behavior. Along a wide gel-fluid transition region, DMPG dispersions display several anomalous characteristics, like low turbidity, high electrical conductivity and viscosity. Here, static and dynamic light scattering (SLS and DLS) were used to characterize DMPG vesicles at different temperatures. Similar experiments were performed with the largely studied zwitterionic lipid dimyristoyl phosphatidylcholine (DMPC). SLS and DLS data yielded similar dimensions for DMPC vesicles at all studied temperatures. However, for DMPG, along the gel-fluid transition region, SLS indicated a threefold increase in the vesicle radius of gyration, whereas the hydrodynamic radius, as obtained from DLS, increased 30% only. Despite the anomalous increase in the radius of gyration, DMPG lipid vesicles maintain isotropy, since no light depolarization was detected. Hence, SLS data are interpreted regarding the presence of isotropic vesicles within the DMPG anomalous transition, but highly perforated vesicles, with large holes. DLS/SLS discrepancy along the DMPG transition region is discussed in terms of the interpretation of the Einstein-Stokes relation for porous vesicles. Therefore, SLS data are shown to be much more appropriate for measuring porous vesicle dimensions than the vesicle diffusion coefficient. The underlying nanoscopic process which leads to the opening of pores in charged DMPG bilayer is very intriguing and deserves further investigation. One could envisage biotechnological applications, with vesicles being produced to enlarge and perforate in a chosen temperature and/or pH value. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Sesquiterpene Lactones with Anti-Hepatitis C Virus Activity Using Molecular Descriptors

Hepatitis C is a worldwide public health problem. The available therapies are limited by their partial effectiveness and with meaningful side-effects. Sesquiterpene lactones (SLs) are a group of natural products with a wide variety of chemical structures and biological activities associated. There are few studies about the influence of the molecular structure of SLs for the anti-hepatitis C virus activity. In the present work, SLs are investigated in a subgenomic RNA replicon assay system and were analyzed using multiple linear regression along with self-organizing maps with DRAGON descriptors in order to identify the structural requirements for their biological activity and to predict the inhibitory potency of SLs. Characteristics such as stereochemistry and electronic effects demonstrated to be important for their anti-HCV activity, and the SOM produced a clear separation betwenn active and inactive compounds. Therefore, it is possible to use this map as a filter for virtual screening to predict the anti-HCV activity of SLs.

Electronic and magnetic properties of SnO2/CrO2 thin superlattices

In this article, using first-principles electronic structure calculations within the spin density functional theory, alternated magnetic and non-magnetic layers of rutile-CrO2 and rutile-SnO2 respectively, in a (CrO2) n (SnO2) n superlattice (SL) configuration, with n being the number of monolayers which are considered equal to 1, 2, ..., 10 are studied. A half-metallic behavior is observed for the (CrO2) n (SnO2) n SLs for all values of n. The ground state is found to be FM with a magnetic moment of 2 μB per chromium atom, and this result does not depend on the number of monolayers n. As the FM rutile-CrO2 is unstable at ambient temperature, and known to be stabilized when on top of SnO2, the authors suggest that (CrO2) n (SnO2) n SLs may be applied to spintronic technologies since they provide efficient spin-polarized carriers.

Study of the vertical transport in p-doped superlattices based on group III-V semiconductors

The electrical conductivity σ has been calculated for p-doped GaAs/Al0.3Ga0.7As and cubic GaN/Al0.3Ga0.7N thin superlattices (SLs). The calculations are done within a self-consistent approach to the k → ⋅ p → theory by means of a full six-band Luttinger-Kohn Hamiltonian, together with the Poisson equation in a plane wave representation, including exchange correlation effects within the local density approximation. It was also assumed that transport in the SL occurs through extended minibands states for each carrier, and the conductivity is calculated at zero temperature and in low-field ohmic limits by the quasi-chemical Boltzmann kinetic equation. It was shown that the particular minibands structure of the p-doped SLs leads to a plateau-like behavior in the conductivity as a function of the donor concentration and/or the Fermi level energy. In addition, it is shown that the Coulomb and exchange-correlation effects play an important role in these systems, since they determine the bending potential.