Thin-film morphology of inkjet-printed single-droplet organic transistors using polarized Raman spectroscopy: effect of blending TIPS-pentacene with insulating polymer.

We report thin-film morphology studies of inkjet-printed single-droplet organic thin-film transistors (OTFTs) using angle-dependent polarized Raman spectroscopy. We show this to be an effective technique to determine the degree of molecular order as well as to spatially resolve the orientation of the conjugated backbones of the 6,13-bis(triisopropylsilylethynyl)pentacene (TIPS-Pentacene) molecules. The addition of an insulating polymer, polystyrene (PS), does not disrupt the π-π stacking of the TIPS-Pentacene molecules.

Controlled deposition of highly ordered soluble acene thin films: effect of morphology and crystal orientation on transistor performance.

Controlling the morphology of soluble small molecule organic semiconductors is crucial for the application of such materials in electronic devices. Using a simple dip-coating process we systematically vary the film drying speed to produce a range of morphologies, including oriented needle-like crystals. Structural characterization as well as electrical transistor measurements show that intermediate drying velocities produce the most uniformly aligned films.

Exploration of enzyme-ligand interactions in CYP2D6 & 3A4 homology models and crystal structures using a novel computational approach.

New crystal structures of human CYP2D6 and CYP3A4 have recently been reported, and in this study, we wanted to compare them with previously used homology models with respect to predictions of site of metabolism and ligand-enzyme interactions. The data set consisted of a family of synthetic opioid analgesics with the aim to cover both CYP2D6 and CYP3A4, as most of these compounds are metabolized by both isoforms. The program MetaSite was used for the site of metabolism predictions, and the results were validated by experimental assessment of the major metabolites formed with recombinant CYP450s.

State-of-the-art tools for computational site of metabolism predictions: comparative analysis, mechanistical insights, and future applications.

In drug design, it is crucial to have reliable information on how a chemical entity behaves in the presence of metabolizing enzymes. This requires substantial experimental efforts. Consequently, being able to predict the likely site/s of metabolism in any compound, synthesized or virtual, would be highly beneficial and time efficient.