Members of the caveolin protein family are implicated in the formation of caveolae, play important roles in a number of signaling pathways and in the regulation of various proteins. We employ complementary spectroscopic methods to study the structure of the caveolin scaffolding domain (CSD) in caveolin-1 fragments, while bound to cholesterol-rich membranes. This key domain is thought to be involved in multiple critical functions that include protein recognition, oligomerization, and cholesterol binding. In our membrane-bound peptides, residues within the flanking intramembrane domain (IMD) are found to adopt an α-helical structure, consistent with its commonly believed helical hairpin conformation. Intriguingly, in these same peptides, we observe a β-stranded conformation for residues in the CSD, contrasting with earlier reports, which commonly do not reflect β-structure. Our experimental data based on solid-state NMR, CD, and FTIR are found to be consistent with computational analyses of the secondary structure preference of the primary sequence. We discuss how our structural data of membrane binding Cav fragments may match certain general features of cholesterol-binding domains and could be consistent with the role for CSD in protein recognition and homo-oligomerization.

Salmonella bacteria cause millions of infections and thousands of deaths every year. This pathogen has an unusually broad host range including humans, animals, and even plants. During infection, Salmonella expresses a variety of virulence factors and effectors that are delivered into the host cell triggering cellular responses through protein–protein interactions (PPIs) with host cell proteins which make the pathogen’s invasion and replication possible. To speed up proteomic efforts in elucidating Salmonella–host interactomes, we carried out a survey of the currently published Salmonella–host PPI. Such a list can serve as the gold standard for computational models aimed at predicting Salmonella–host interactomes through integration of large-scale biological data sources. Manual literature and database search of >2200 journal articles and >100 databases resulted in a gold standard list of currently 62 PPI, including primarily interactions of Salmonella proteins with human and mouse proteins. Only six of these interactions were directly retrievable from PPI databases and 16 were highlighted in databases featuring literature extracts. Thus, the literature survey resulted in the most complete interactome available to date for Salmonella. Pathway analysis using Ingenuity and Broad Gene Set Enrichment Analysis (GSEA) software revealed among general pathways such as MAPK signaling in particular those related to cell death as well as cell morphology, turnover, and interactions, in addition to response to not only Salmonella but also other pathogenic – viral and bacterial – infections. The list of interactions is available at http://www.shiprec.org/indicationslist.htm

Cu2CdSnS4 and α/β-Cu2ZnSiS4 meet several criteria for promising nonlinear optical materials for use in the infrared (IR) region. Both are air-stable, crystallize in noncentrosymmetric space groups, and possess high thermal stabilities. Cu2CdSnS4 and α/β-Cu2ZnSiS4 display wide ranges of optical transparency, 1.4-25 and 0.7-25 μm, respectively, and have relatively large second-order nonlinearity as well as phase matchability for wide regions in the IR. The laser-damage threshold (LDT) for Cu2CdSnS4 is 0.2 GW/cm(2), whereas α/β-Cu2ZnSiS4 has a LDT of 2.0 GW/cm(2) for picosecond near-IR excitation. Both compounds also exhibit efficient third-order nonlinearity. Electronic structure calculations provide insight into the variation in properties.

The principal components of the 13 C chemical shift tensors for the ten crystallographically distinct carbon atoms of the active pharmaceutical ingredient cimetidine Form A have been measured using the FIREMAT technique. Density functional theory (DFT) calculations of 13 C and 15 N magnetic shielding tensors are used to assign the 13 C and 15 N peaks. DFT calculations were performed on cimetidine and a training set of organic crystals using both plane-wave and cluster-based approaches. The former set of calculations allowed several structural refinement strategies to be employed, including calculations utilizing a dispersion-corrected force field that was parametrized using 13 C and 15 N magnetic shielding tensors. The latter set of calculations featured the use of resource-intensive hybrid-DFT methods for the calculation of magnetic shielding tensors. Calculations on structures refined using the new force-field correction result in improved values of 15 N magnetic shielding tensors (as gauged by agreement with experimental chemical shift tensors), although little improvement is seen in the prediction of 13 C shielding tensors. Calculations of 13 C and 15 N magnetic shielding tensors using hybrid functionals show better agreement with experimental values in comparison to those using GGA functionals, independent of the method of structural refinement; the shielding of carbon atoms bonded to nitrogen are especially improved using hybrid DFT methods.

In undergraduate physical chemistry, Schrodinger's equation is solved for a variety of cases. In doing so, the energies and wave functions of the system can be interpreted to provide connections with the physical system being studied. Solving this equation by hand for a one-dimensional system is a manageable task, but it becomes time-consuming once students aim to make various changes and investigate the impact of those changes on the results. To address this challenge, numerical methods, such as the shooting and linear finite-difference methods, have been utilized to quickly solve Schrodinger's equation. In this technology report, we use the Python programming environment and the three-point finite-difference numerical method to find the solutions and plot the results (wave functions or probability densities) for a particle in an infinite, finite, double finite, harmonic, Morse, or Kronig− Penney finite potential energy well. We believe that this technology report will educate undergraduates on the basic tools of computer programming, data analysis, and making connections between mathematical models and the physical systems with which they are associated.