X-ray dynamical diffraction by quasi-monolayer graphene.

We study the processes of dynamical diffraction of the plane X-ray waves on the graphene film/SiC substrate system in the case of the Bragg diffraction geometry. The statistical dynamical theory of X-ray diffraction in imperfect crystals is applied to the case of real quasi-two-dimensional systems. The necessity of the taking into account of the variability of the lattice parameter of multilayer graphene, as well as the influence of thickness on the thermal Debye-Waller factor at the calculation of the complex structural factors and Fourier components of polarizability, is demonstrated.

Straintronics in phosphorene via tensile vs shear strains and their combinations for manipulating the band gap.

We study the effects of the uniaxial tensile strain and shear deformation as well as their combinations on the electronic properties of single-layer black phosphorene. The evolutions of the strain-dependent band gap are obtained using the numerical calculations within the tight-binding (TB) model as well as the first-principles (DFT) simulations and compared with previous findings. The TB-model-based findings show that the band gap of the strain-free phosphorene agrees with the experimental value and linearly depends on both stretching and shearing: increases (decreases) as the stretching increases (decreases), whereas gradually decreases with increasing the shear.

Metabolite identification using an ion mobility enhanced data-independent acquisition strategy and automated data processing.

Rationale: Liquid chromatography/mass spectrometry is an essential tool for efficient and reliable quantitative and qualitative analysis and underpins much of contemporary drug metabolism and pharmacokinetics. Data-independent acquisition methods such as MS have reduced the potential to miss metabolites, but do not formally generate quadrupole-resolved product ion spectra. The addition of ion mobility separation to these approaches, for example, in High-Definition MS (HDMS ) has the potential to reduce the time needed to set up an experiment and maximize the chance that all metabolites present can be resolved and characterized.

Software-aided workflow for predicting protease-specific cleavage sites using physicochemical properties of the natural and unnatural amino acids in peptide-based drug discovery.

Peptide drugs have been used in the treatment of multiple pathologies. During peptide discovery, it is crucially important to be able to map the potential sites of cleavages of the proteases. This knowledge is used to later chemically modify the peptide drug to adapt it for the therapeutic use, making peptide stable against individual proteases or in complex medias.

WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source.

Summary: More than 150 peptide therapeutics are globally in clinical development. Many enzymatic barriers should be crossed by a successful drug to be prosperous in such a process. Therefore, the new peptide drugs must be designed preventing the potential protease cleavage to make the compound less susceptible to protease reaction.