An approach to computer-aided inhibitor design: Application to cathepsin L

Summary We have developed an approach to search for molecules that can be used as lead compounds in designing an inhibitor for a given proteolytic enzyme when the 3D structure of a homologous protein is known. This approach is based on taking the cast of the binding pocket of the protease and comparing its dimensions with that of the dimensions of small molecules. Herein the 3D structure of papain is used to model cathepsin L using the comparative modeling technique. The cast of the binding pocket is computed using the crystal structure of papain because the structures of papain and the model of cathepsin L are found to be similar at the binding site. The dimensions of the cast of the binding site of papain are used to screen for molecules from the Cambridge Structural Database (CSD) of small molecules. Twenty molecules out of the 80 000 small molecules in the CSD are found to have dimensions that are accommodated by the papain binding pocket. Visual comparison of the shapes of the cast and the 20 screened molecules resulted in identifying brevotoxin b, a toxin isolated from the red tide dinoflagellate Ptycho brevis (previously classified as Gymonodium breve), as the structure that best fits the binding pocket of papain. We tested the proteolytic activity of papain and cathepsin L in the presence of brevotoxin b and found inhibition of papain and cathepsin L with K_is of 25 M and 0.6 M, respectively. We also compare our method with a more elaborate method in the literature, by presenting our results on the computer search for inhibitors of the HIV-1 protease.     

Mathematical Models of Death Signaling Networks

This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We define the cell death network as a comprehensive decision-making mechanism that controls multiple death execution molecular circuits. This network involves multiple feedback and feed-forward loops and crosstalk among different cell death-regulating pathways. While substantial progress has been made in characterizing individual cell death execution pathways, the cell death decision network is poorly defined and understood. Certainly, understanding the dynamic behavior of such complex regulatory mechanisms can be only achieved by applying mathematical modeling and system-oriented approaches. Here, we provide an overview of mathematical models that have been developed to characterize different cell death mechanisms and intend to identify future research directions in this field.     

Sulfonated rGO from waste dry cell graphite rod and its hybrid with PANI as electrode for supercapacitor

Journal of Solid State Electrochemistry - Development of high-performance energy storage devices is a vital research area to meet the present-day energy demand. In the work carried toward the...     

Stuffed Tridymite Structures: Synthesis,Structure, Second Harmonic Generation,Optical, and Multiferroic Properties

The stuffed tridymite structure Ba(Zn/Co)_1−xSi_1−xM_2xO₄ (M=Al³⁺ and Fe³⁺) is explored for the possible multiferroic behavior and to develop new inorganic colored materials. The compounds were synthesized by employing conventional solid-state chemistry methods in the temperature range 1100–1175 °C for 24 h. The powder X-ray diffraction (PXRD) and Rietveld refinement studies indicate that the compounds stabilize in the P63 space group (no. 173). The refinement results were also rationalized by employing Raman spectroscopic studies. The compounds were found to be second harmonic generation (SHG) active and show weak ferroelectric behavior. The co-substitution of Co²⁺ and Fe³⁺ in the structure gives rise to a weak ferromagnetic behavior to the compound, BaCo_0.75Si_0.75Fe_0.5O₄, making it a multiferroic material. The optical studies on the prepared compounds exhibited blue color (Co²⁺ in T_d geometry), purple color (Ni²⁺ in T_d geometry), and simultaneous substitution of Co²⁺ and Fe³⁺ gives rise to blue-green color owing to metal-to-metal charge transfer (MMCT) effect.     

On the existence of ‘glycine barium nitrate potassium nitrate’ crystal

It is proved that a so called novel nonlinear optical glycine barium nitrate potassium nitrate single crystal grown by slow evaporation solution growth technique by Ravishankar et al. (Optik, 2013) is actually the well-known γ-glycine crystal.     

Simulation of local ion transport in lamellar block copolymer electrolytes based on electron micrographs

A method is presented to relate local morphology and ionic conductivity in a solid, lamellar block copolymer electrolyte for lithium batteries, by simulating conductivity through transmission electron micrographs. The electrolyte consists of polystyrene‐block‐poly(ethylene oxide) mixed with lithium bis(trifluoromethanesulfonyl) imide salt (SEO/LiTFSI), where the polystyrene phase is structural phase and the poly(ethylene oxide)/LiTFSI phase is ionically conductive. The electric potential distribution is simulated in binarized micrographs by solving the Laplace equation with constant potential boundary conditions. A morphology factor, f, is reported for each image by calculating the effective conductivity relative to a homogenous conductor. Images from two samples are examined, one annealed with large lamellar grains and one unannealed with small grains. The average value of f is 0.45 ± 0.04 for the annealed sample, and 0.37 ± 0.03 for the unannealed sample, both close to the value predicted by effective medium theory, 1/2. Simulated conductivities are compared to published experimental conductivities. The value of f_Unannealed/f_Annealed is 0.82 for simulations and 6.2 for experiments. Simulation results correspond well to predictions by effective medium theory but do not explain the experimental measurements. Observation of nanoscale morphology over length scales greater than the size of the micrographs (～1 μm) may be required to explain the experimental results. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017 , 55, 266–274