Editing of Chemical Exchange-Relayed NOEs in NMR Experiments for the Observation of Protein–Water Interactions

An experimental approach for the editing of exchange-relayed NOEs in water-selective NOE experiments is presented. The proposed pulse sequence is based on the application during the NOE mixing time of continuous wave irradiation, which saturates resonances of relaying labile protons in slow chemical exchange with water. The technique can efficiently reduce the contributions of exchange-relayed NOE peaks that often crowd the water-selective NOE spectra and hide direct intermolecular NOEs between water and protein protons. The present approach opens new opportunities for the characterization of hydration by NMR, even in the proximity of polar labile groups.     

Hydrophilic sensor membrane based on cation-selective protic chromoionophore

The first potassium optode based on a protic chromoionophore immobilized in a hydrogel matrix is presented. The highly selective protic chromoionophore consists of a cryptohemispherand moiety and a trinitroanilino chromophore part. The acidifying power of potassium ions over sodium ions is 0.6 pH units. This correlates with the findings in solution. In contrast to several crown and aza-crown based chromophores the highly pre-organized moiety allows ion detection even in aqueous environment. The detection limit for potassium ions at ¶pH 7.7 is 5 μM.     

Computation and physics: Wheeler's meaning circuit?

Computation is a physical process, inevitably utilizing physical degrees of freedom. Computation, therefore, is restricted by the laws of physics and also by the construction materials and operating environments available in our actual universe. These restrictions have been investigated for a quarter century. A discussion of this field is provided, too concise to be a review, but only intended as a guide to the literature. Physical law, in turn, consists of algorithms for information processing. Therefore, the ultimate form of physical laws must be consistent with the restrictions on the physical executability of algorithms, which is in turn dependent on physical law.     

Multivariate design

In multivariate data analysis such as principal components analysis (PCA) and projections to latent structures (PLS), it is essential that the training set systems (objects) are selected to provide data with substantial information for model parametrization, and to represent properly any future situations where the multilvariate model is used for predictions. In the framework of multivariate projections (PCA, SIMCA and PLS), elementary concepts of statistical design (fractional factorials and composite designs) can be used with the latent variables (PC or PLS scores) as design variables. The plan of action thus becomes: (1) problem formulation (specify aim and model, make a conceptual division of the investigated system into subsystems); (2) collection of multivariate data for each type of subsystems; (3) estimation of the practical dimensionality of the data for each type of subsystems by PC or PLS analysis; (4) use of the PC or PLS scores (t) as design variables in the combination of subsystems to systems in the training set; (5) measurement of responses (Y); (6) analysis of data by PCA or PLS; (7) interpretation of results with possible feedback to steps 1, 2 or 3. The procedures are illustrated by two problems: a structure/activity relationship for a family of peptides, and optimization of an organic synthesis with respect to system variables (solvent, substrate, co-reactant_) and process variables (temperature, reactant concentrations).