Benchmarking the accuracy of coverage-dependent models: adsorption and desorption of benzene on Pt (1 1 1) and Pt3Sn (1 1 1) from first principles

Bimetallic catalysts have demonstrated properties favorable for upgrading biofuel through catalytic hydrodeoxygenation. However, the design and optimization of such bimetallic catalysts requires the ability to construct accurate, predictive models of these systems. To generate a model that predicts the kinetic behavior of benzene adsorbed on Pt (1 1 1) and a Pt₃Sn (1 1 1) surface alloy (Pt₃Sn (1 1 1)), the adsorption of benzene was studied for a wide range of benzene coverages on both surfaces using density functional theory (DFT) calculations. The adsorption energy of benzene was found to correlate linearly with benzene coverage on Pt (1 1 1) and Pt₃Sn (1 1 1); both surfaces exhibited net repulsive lateral interactions. Through an analysis of the d-band properties of the metal surface, it was determined that the coverage dependence is a consequence of the electronic interactions between benzene and the surface. The linear coverage dependence of the adsorption energy allowed us to quantify the influence of the lateral interactions on the heat of adsorption and temperature programmed desorption (TPD) spectra using a mean-field model. A comparison of our simulated TPD to experiment showed that this mean-field model adequately reproduces the desorption behavior of benzene on Pt (1 1 1) and Pt₃Sn (1 1 1). In particular, the TPD correctly exhibits a broadening desorption peak as the initial coverage of benzene increases on Pt (1 1 1) and a low temperature desorption peak on Pt₃Sn (1 1 1). However, due to the sensitivity of the TPD peak temperature to the desorption energy, precise alignment of experimental and theoretical TPD spectra demands an accurate calculation of the adsorption energy. Therefore, an analysis of the effect of the exchange-correlation functional on TPD modeling is presented. Through this work, we show the necessity of incorporating lateral interactions into theoretical models in order to correctly predict experimental behavior.     

To fold or to assemble?

We introduce a new class of foldable oligomers consisting of alternating rigid and flexible regions. The rigid segments overlap to give pi-stacked folded conformers whose formation is driven mostly by pi-pi molecular orbital overlaps. As the oligomer concentration increases, the folded molecular structures further self-assemble into larger nanostructures. The dynamic processes of folding and self-organization are monitored with absorption, fluorescence, and NMR spectroscopies. Our results show that folding dominates at low concentrations (< approximately 1 mM) and precedes self-assembly, which occurs over the initial concentration range of approximately 1-100 mM.     

Correlated atomic force microscopy and fluorescence lifetime imaging of live bacterial cells

We report on imaging living bacterial cells by using a correlated tapping-mode atomic force microscopy (AFM) and confocal fluorescence lifetime imaging microscopy (FLIM). For optimal imaging of Gram-negative Shewanella oneidensis MR-1 cells, we explored different methods of bacterial sample preparation, such as spreading the cells on poly-L-lysine coated surfaces or agarose gel coated surfaces. We have found that the agarose gel containing 99% ammonium acetate buffer can provide sufficient local aqueous environment for single bacterial cells. Furthermore, the cell surface topography can be characterized by tapping-mode in-air AFM imaging for the single bacterial cells that are partially embedded. Using in-air rather than under-water AFM imaging of the living cells significantly enhanced the contrast and signal-to-noise ratio of the AFM images. Near-field AFM-tip-enhanced fluorescence lifetime imaging (AFM-FLIM) holds high promise on obtaining fluorescence images beyond optical diffraction limited spatial resolution. We have previously demonstrated near-field AFM-FLIM imaging of polymer beads beyond diffraction limited spatial resolution. Here, as the first step of applying AFM-FLIM on imaging bacterial living cells, we demonstrated a correlated and consecutive AFM topographic imaging, fluorescence intensity imaging, and FLIM imaging of living bacterial cells to characterize cell polarity.     

2D SMARTCyp reactivity-based site of metabolism prediction for major drug-metabolizing cytochrome P450 enzymes

Cytochrome P450 (CYP) 3A4, 2D6, 2C9, 2C19, and 1A2 are the most important drug-metabolizing enzymes in the human liver. Knowledge of which parts of a drug molecule are subject to metabolic reactions catalyzed by these enzymes is crucial for rational drug design to mitigate ADME/toxicity issues. SMARTCyp, a recently developed 2D ligand structure-based method, is able to predict site-specific metabolic reactivity of CYP3A4 and CYP2D6 substrates with an accuracy that rivals the best and more computationally demanding 3D structure-based methods. In this article, the SMARTCyp approach was extended to predict the metabolic hotspots for CYP2C9, CYP2C19, and CYP1A2 substrates. This was accomplished by taking into account the impact of a key substrate-receptor recognition feature of each enzyme as a correction term to the SMARTCyp reactivity. The corrected reactivity was then used to rank order the likely sites of CYP-mediated metabolic reactions. For 60 CYP1A2 substrates, the observed major sites of CYP1A2 catalyzed metabolic reactions were among the top-ranked 1, 2, and 3 positions in 67%, 80%, and 83% of the cases, respectively. The results were similar to those obtained by MetaSite and the reactivity + docking approach. For 70 CYP2C9 substrates, the observed sites of CYP2C9 metabolism were among the top-ranked 1, 2, and 3 positions in 66%, 86%, and 87% of the cases, respectively. These results were better than the corresponding results of StarDrop version 5.0, which were 61%, 73%, and 77%, respectively. For 36 compounds metabolized by CYP2C19, the observed sites of metabolism were found to be among the top-ranked 1, 2, and 3 sites in 78%, 89%, and 94% of the cases, respectively. The computational procedure was implemented as an extension to the program SMARTCyp 2.0. With the extension, the program can now predict the site of metabolism for all five major drug-metabolizing enzymes with an accuracy similar to or better than that achieved by the best 3D structure-based methods. Both the Java source code and the binary executable of the program are freely available to interested users.     

Biochemical and Structural Studies of Conserved Maf Proteins Revealed Nucleotide Pyrophosphatases with a Preference for Modified Nucleotides

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Front-End Electron Transfer Dissociation Coupled to a 21 Tesla FT-ICR Mass Spectrometer for Intact Protein Sequence Analysis

High resolution mass spectrometry is a key technology for in-depth protein characterization. High-field Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) enables high-level interrogation of intact proteins in the most detail to date. However, an appropriate complement of fragmentation technologies must be paired with FTMS to provide comprehensive sequence coverage, as well as characterization of sequence variants, and post-translational modifications. Here we describe the integration of front-end electron transfer dissociation (FETD) with a custom-built 21 tesla FT-ICR mass spectrometer, which yields unprecedented sequence coverage for proteins ranging from 2.8 to 29 kDa, without the need for extensive spectral averaging (e.g., ~60% sequence coverage for apo-myoglobin with four averaged acquisitions). The system is equipped with a multipole storage device separate from the ETD reaction device, which allows accumulation of multiple ETD fragment ion fills. Consequently, an optimally large product ion population is accumulated prior to transfer to the ICR cell for mass analysis, which improves mass spectral signal-to-noise ratio, dynamic range, and scan rate. We find a linear relationship between protein molecular weight and minimum number of ETD reaction fills to achieve optimum sequence coverage, thereby enabling more efficient use of instrument data acquisition time. Finally, real-time scaling of the number of ETD reactions fills during method-based acquisition is shown, and the implications for LC-MS/MS top-down analysis are discussed.

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