A Potentially Versatile Enzyme Sensor Platform: Enzyme-Loaded, Tagged, Porous Polymeric Nanocapsules.

Enzymes are essential to life and indispensable in a wide range of industries (food, pharmaceutical, medical, biosensing, etc.); however, a significant shortcoming of these fragile biological catalysts is their poor stability. To address this challenge, a variety of immobilization methods have been described to enhance the enzyme's stability.

Multilayer and Surface Immobilization of EDOT-Decorated Nanocapsules.

To assess the feasibility of utilizing reagent-loaded, porous polymeric nanocapsules (NCs) for chemical and biochemical sensor design, the surfaces of the NCs were decorated with 3,4-ethylenedioxythiophene (EDOT) moieties. The pores in the capsule wall allow unhindered bidirectional diffusion of molecules smaller than the programmed pore sizes, while larger molecules are either entrapped inside or blocked from entering the interior of the nanocapsules. Here, we investigate two electrochemical deposition methods to covalently attach acrylate-based porous nanocapsules with 3,4-ethylenedioxythiophene moieties on the nanocapsule surface, i.

Benchmarking GPCR homology model template selection in combination with de novo loop generation.

G protein-coupled receptors (GPCR) comprise the largest family of membrane proteins and are of considerable interest as targets for drug development. However, many GPCR structures remain unsolved. To address the structural ambiguity of these receptors, computational tools such as homology modeling and loop modeling are often employed to generate predictive receptor structures.

GPCR homology model template selection benchmarking: Global versus local similarity measures.

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development. GPCR ligand interaction studies often have a starting point with either crystal structures or comparative models. The majority of GPCR do not have experimentally-characterized 3-dimensional structures, so comparative modeling, also called homology modeling, is a good structure-based starting point.