QSAR classification of metabolic activation of chemicals into covalently reactive species

Metabolic activation of chemicals into covalently reactive species might lead to toxicological consequences such as tissue necrosis, carcinogenicity, teratogenicity, or immune-mediated toxicities. Early prediction of this undesirable outcome can help in selecting candidates with increased chance of success, thus, reducing attrition at all stages of drug development. The ensemble modelling of mixed features was used for the development of a model to classify the metabolic activation of chemicals into covalently reactive species. The effects of the quality of base classifiers and performance measure for sorting were examined. An ensemble model of 13 naive Bayes classifiers was built from a diverse set of 1,479 compounds. The ensemble model was validated internally with five-fold cross validation and it has achieved sensitivity of 67.4% and specificity of 93.4% when tested on the training set. The final ensemble model was made available for public use.     

Characterization of Zn‐Containing Metal–Organic Frameworks by Solid‐State 67Zn NMR Spectroscopy and Computational Modeling

Metal–organic frameworks (MOFs) are an extremely important class of porous materials with many applications. The metal centers in many important MOFs are zinc cations. However, their Zn environments have not been characterized directly by ⁶⁷Zn solid‐state NMR (SSNMR) spectroscopy. This is because ⁶⁷Zn (I=5/2) is unreceptive with many unfavorable NMR characteristics, leading to very low sensitivity. In this work, we report, for the first time, a ⁶⁷Zn natural abundance SSNMR spectroscopic study of several representative zeolitic imidazolate frameworks (ZIFs) and MOFs at an ultrahigh magnetic field of 21.1 T. Our work demonstrates that ⁶⁷Zn magic‐angle spinning (MAS) NMR spectra are highly sensitive to the local Zn environment and can differentiate non‐equivalent Zn sites. The ⁶⁷Zn NMR parameters can be predicted by theoretical calculations. Through the study of MOF‐5 desolvation, we show that with the aid of computational modeling, ⁶⁷Zn NMR spectroscopy can provide valuable structural information on the MOF systems with structures that are not well described. Using ZIF‐8 as an example, we further demonstrate that ⁶⁷Zn NMR spectroscopy is highly sensitive to the guest molecules present inside the cavities. Our work also shows that a combination of ⁶⁷Zn NMR data and molecular dynamics simulation can reveal detailed information on the distribution and the dynamics of the guest species. The present work establishes ⁶⁷Zn SSNMR spectroscopy as a new tool complementary to X‐ray diffraction for solving outstanding structural problems and for determining the structures of many new MOFs yet to come.     

Energy Fluctuations Shape Free Energy of Nonspecific Biomolecular Interactions

Understanding design principles of biomolecular recognition is a key question of molecular biology. Yet the enormous complexity and diversity of biological molecules hamper the efforts to gain a predictive ability for the free energy of protein-protein, protein-DNA, and protein-RNA binding. Here, using a variant of the Derrida model, we predict that for a large class of biomolecular interactions, it is possible to accurately estimate the relative free energy of binding based on the fluctuation properties of their energy spectra, even if a finite number of the energy levels is known. We show that the free energy of the system possessing a wider binding energy spectrum is almost surely lower compared with the system possessing a narrower energy spectrum. Our predictions imply that low-affinity binding scores, usually wasted in protein-protein and protein-DNA docking algorithms, can be efficiently utilized to compute the free energy. Using the results of Rosetta docking simulations of protein-protein interactions from Andre et al. (Proc. Natl. Acad. Sci. USA 105:16148, 2008), we demonstrate the power of our predictions.     

A performance study of radio-opaque personal protective fabrics for the reduction of transmittance of gamma-rays and neutrons

Commercial radio-opaque combat (CRC) fabrics, for incorporation into personal protective equipment used by first responders and armed forces, are marketed as having the ability to provide a level of protection against specific types of radiation. For a CRC material, a standard combat uniform and a multi-layered chemical, biological, radiological, nuclear (CBRN) protective material, the present work examines chemical composition and radiation protection against gamma-rays and neutron fluxes. Significant reduction in gamma-ray transmittance occurs only for the CRC fabric (46–514 keV) with gamma-ray attenuation coefficients of 3.10 to <0.10 cm² g⁻¹. Reduction in neutron transmittance, for all three fabrics, could not be assessed with certainty as the measured transmittance was obscured by large statistical uncertainties.     

Dynamic pressure based prediction of spray cooling heat transfer coefficients

An important goal of spray cooling research is the ability to predict local heat transfer from the spray hydrodynamics. It is postulated that the local normal pressure exerted by the spray onto the heated surface can be used to obtain the local heat transfer coefficient. This hypothesis was tested using data obtained from hollow cone, full cone, and linear sprays at four nozzle pressures and three stand-off distances. A correlation between the pressure and heat transfer coefficient was determined from the data, then used to “predict” the heat transfer coefficient to verify the accuracy of the correlation. The area averaged heat transfer coefficient could be predicted within 25%, indicating that pressure can be used to predict the local heat transfer coefficient in the single-phase regime.     

Was wissen Calamari über Sarin? Enzymatische Dekontamination von Nervenkampfstoffen

Together with detection and use of protective clothing, decontamination is the third important part in NBC defence and NBC protection. Enzymes play an important role in the research field of new and environmentally friendly decontaminants. In 1946, organophosphate cleaving enzymes were first mentioned, and in the next decades further enzymes (i.e., DFPase) against G‐type nerve agents were discovered. After the cloning of the DFPase gene sequence in the 90s, the potential of DFPase as an environmentally friendly decontaminant was shown. In technical decontamination experiments, it was shown that the conditions for an enzyme‐based decontamination concept could be met for one class of chemical agents. However, the success of a general enzyme decontamination concept depends on the discovery of new enzymes against other classes of chemical agents, i.e., mustard and VX.     

Unique continuation for the magnetic Schrödinger equation

The unique-continuation property from sets of positive measure is here proven for the many-body magnetic Schrödinger equation. This property guarantees that if a solution of the Schrödinger equation vanishes on a set of positive measure, then it is identically zero. We explicitly consider potentials written as sums of either one-body or two-body functions, typical for Hamiltonians in many-body quantum mechanics. As a special case, we are able to treat atomic and molecular Hamiltonians. The unique-continuation property plays an important role in density-functional theories, which underpins its relevance in quantum chemistry.     

Improvements in lipid suppression for 1H NMR-based metabolomics: Applications to solution-state and HR-MAS NMR in natural and in vivo samples

Proton nuclear magnetic resonance (NMR) spectra of intact biological samples often show strong contributions from lipids, which overlap with signals of interest from small metabolites. Pioneering work by Diserens et al. demonstrated that the relative differences in diffusivity and relaxation of lipids versus small metabolites could be exploited to suppress lipid signals, in high-resolution magic angle spinning (HR-MAS) NMR spectroscopy. In solution-state NMR, suspended samples can exhibit very broad water signals, which are challenging to suppress. Here, improved water suppression is incorporated into the sequence, and the Carr-Purcell-Meiboom-Gill sequence (CPMG) train is replaced with a low-power adiabatic spinlock that reduces heating and spectral artefacts seen with longer CPMG filters. The result is a robust sequence that works well in both HR-MAS as well as static solution-state samples. Applications are also extended to include in vivo organisms. For solution-state NMR, samples containing significant amount of fats such as milk and hemp hearts seeds are used to demonstrate the technique. For HR-MAS, living earthworms (Eisenia fetida) and freshwater shrimp (Hyalella azteca) are used for in vivo applications. Lipid suppression techniques are essential for non-invasive NMR-based analysis of biological samples with a high-lipid content and adds to the suite of experiments advantageous for in vivo environmental metabolomics.     

The role of rebound spikes in the maintenance of self-sustained neural spiking activity

Nonlinear Dynamics - In general, the mechanisms that maintain the activity of neural systems after a triggering stimulus has been removed are not well understood. Different mechanisms involving at...