Materials and methodsOligonucleotide and Device Preparation. All DNA oligonucleotides were synthesized by Integrated DNA Technologies, Inc. DNA labelling with fluorophore or quencher and subsequent purification were performed by the supplier and the resulting oligomers were used without further purification. DNA stock solutions (40-60 µM) were prepared in TE buffer (pH 8.0) and concentrations were determined at 260 nm using the molecular extinction coefficient supplied by the manufacturer. The track (final concentration = 5 µM) was prepared by mixing the six track strand species in TSE buffer (10 mM Tris, 150 mM NaCl, 1 mM EDTA, pH 7.5), followed by incubation for 3 hr at 37• C. The walker was prepared by the same procedure using the two walker strand species.Non-denaturing PAGE Analysis. Fuel-mediated association of the walker and track was analyzed by non-denaturing PAGE. The reaction volume for the PAGE experiments was 10 µl. Initial anchoring of the walker on branch 1 was achieved by adding equimolar A1 to a reaction mixture of track and walker (1 µM in TSE buffer), followed by 1 hr incubation at 37• C. Subsequent walker movement was carried out by successively adding different fuel species in equimolar amounts. Each addition was followed by 1 hr incubation at 37• C. The whole reaction sample was loaded in a 6.7% non-denaturing gel. Gel electrophoresis was accomplished in 1× TBE buffer at 50 V and 4• C, and the bands were visualized by fluorescent scanning (Molecular Imager FX Pro Plus, Bio-Rad).Multiplexed Real-time Fluorescence Measurement. Fluorescence measurements were carried out with a fluorometer (PTI Co.) at room temperature. Bandwidths for excitation and emission were set to 4 nm and the working volume for measurements was 100 µl. Track (0.5 µM) was preincubated with equimolar walker and A1 in TSE buffer for 4 hr at room temperature. Equimolar amounts of fuel strands were successively added from 100× stocks and the solution was mixed by rapid pipetting. Fluorescence signals from four different dyes were collected during the same run using the multi-dye mode (Felix32 software, PTI Co.) to monitor fluorescence intensities at four excitation/emission wavelengths. Independence of fluorescence signalsTo monitor walker movement, four fluorescent dyes were selected (FAM, HEX, Texas Red, Cy5 in order of increasing excitation/emission wavelengths) from many possible candidates. To minimize FRET between dyes, branches 1-4 on the track were labeled in the order (HEX, Cy5, FAM, Texas Red) to double the distance between dyes with adjacent fluorescence spectra. These concerns were particularly relevant because the equilibrium distance between neighboring dyes (5 nm) is typical of the Förster radius for many dye pairs. Excitation and emission wavelengths for each dye were chosen so as to minimize the response of the other three dyes. Columns 2-5 of Table S1 list fluorescence intensities of the four dye-labled T strands at the four excitation/emission wavelengths employed for multiplexed fluorescence measurements. ...

We provide an open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we con-ducted two BCI experiments (left vs. right hand motor imagery; mental arithmetic vs. resting state). The dataset was validated using baseline signal analysis methods, with which classification performance was evaluated for each modality and a combination of both modalities. As already shown in previous literature, the capability of discriminating different mental states can be en-hanced by using a hybrid approach, when comparing to single modality analyses. This makes the provided data highly suitable for hybrid BCI investigations. Since our open access dataset also comprises motion artifacts and physiological data, we expect that it can be used in a wide range of future validation approaches in multimodal BCI research.

Chiral amines in enantiopure forms are important chemical building blocks, which are most well recognized in the pharmaceutical industries for imparting desirable biological activity to chemical entities. A number of synthetic strategies to produce chiral amines via biocatalytic as well as chemical transformation have been developed. Recently, ω-transaminase (ω-TA) has attracted growing attention as a promising catalyst which provides an environment-friendly access to production of chiral amines with exquisite stereoselectivity and excellent catalytic turnover. To obtain enantiopure amines using ω-TAs, either kinetic resolution of racemic amines or asymmetric amination of achiral ketones is employed. The latter is usually preferred because of twofold higher yield and no requirement of conversion of a ketone product back to racemic amine. However, the choice of a production process depends on several factors such as reaction equilibrium, substrate reactivity, enzyme inhibition, and commercial availability of substrates. This review summarizes the biochemical features of ω-TA, including reaction chemistry, substrate specificity, and active site structure, and then introduces recent advances in expanding the scope of ω-TA reaction by protein engineering and public database searching. We also address crucial factors to be considered for the development of efficient ω-TA processes.

An active site model of the amine:pyruvate aminotransferase (APA) from Vibrio fluvialis JS17 was constructed on the basis of the relationship between substrate structure and reactivity. Due to the broad substrate specificity of the APA, various amino donors (chiral and achiral amine, amino acid, and amino acid derivative) and amino acceptors (keto acid, keto ester, aldehyde, and ketone) were used to explore the active site structure. The result suggested a two-binding site model consisting of two pockets, one large (L) and the other small (S). The difference in the size of each binding pocket and strong repulsion for a carboxylate in the S pocket were key determinants to control its substrate specificity and stereoselectivity. The L pocket showed dual recognition mode for both hydrophobic and carboxyl groups as observed in the side-chain pockets of aspartate aminotransferase and aromatic aminotransferase. Comparison of the model with those of other aminotransferases revealed that the L and S pockets corresponded to carboxylate trap and side-chain pocket, respectively. The active site model successfully explains the observed substrate specificity as well as the stereoselectivity of the APA.