Two-Dimensional Infrared Spectroscopy of Antiparallel β-Sheet Secondary Structure

We investigate the sensitivity of femtosecond Fourier transform two-dimensional infrared spectroscopy to protein secondary structure with a study of antiparallel β-sheets. The results show that 2D IR spectroscopy is more sensitive to structural differences between proteins than traditional infrared spectroscopy, providing an observable that allows comparison to quantitative models of protein vibrational spectroscopy. 2D IR correlation spectra of the amide I region of poly-L-lysine, concanavalin A, ribonuclease A, and lysozyme show cross-peaks between the IR-active transitions that are characteristic of amide I couplings for polypeptides in antiparallel hydrogen-bonding registry. For poly-L-lysine, the 2D IR spectrum contains the eight-peak structure expected for two dominant vibrations of an extended, ordered antiparallel β-sheet. In the proteins with antiparallel β-sheets, interference effects between the diagonal and cross-peaks arising from the sheets, combined with diagonally elongated resonances from additional amide transitions, lead to a characteristic “Z”-shaped pattern for the amide I region in the 2D IR spectrum. We discuss in detail how the number of strands in the sheet, the local configurational disorder in the sheet, the delocalization of the vibrational excitation, and the angle between transition dipole moments affect the position, splitting, amplitude, and line shape of the cross-peaks and diagonal peaks.

Ab initio study of alanine polypeptide chains twisting

We have investigated the potential energy surfaces for alanine chains consisting of three and six amino acids. For these molecules we have calculated potential energy surfaces as a function of the Ramachandran angles Phi and Psi, which are widely used for the characterization of the polypeptide chains. These particular degrees of freedom are essential for the characterization of proteins folding process. Calculations have been carried out within ab initio theoretical framework based on the density functional theory and accounting for all the electrons in the system. We have determined stable conformations and calculated the energy barriers for transitions between them. Using a thermodynamic approach, we have estimated the times of characteristic transitions between these conformations. The results of our calculations have been compared with those obtained by other theoretical methods and with the available experimental data extracted from the Protein Data Base. This comparison demonstrates a reasonable correspondence of the most prominent minima on the calculated potential energy surfaces to the experimentally measured angles Phi and Psi for alanine chains appearing in native proteins. We have also investigated the influence of the secondary structure of polypeptide chains on the formation of the potential energy landscape. This analysis has been performed for the sheet and the helix conformations of chains of six amino acids.Comment: 24 pages, 10 figure

Combining Two Consistent Estimators

This chapter shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited information maximum likelihood (LIML)) were introduced by Hausman, Newey, Woutersen, Chao, and Swanson (2012), but without derivation. Combining consistent estimators is a theme that is associated with Jerry Hausman and, therefore, we present this derivation in this volume. Additionally, and in order to further understand and interpret HFUL and HLIM in the context of jackknife type variance ratio estimators, we show that a new variant of HLIM, under specific grouped data settings with dummy instruments, simplifies to the Bekker and van der Ploeg (2005) MM (method of moments) estimator

An Expository Note on the Existence of Moments of Fuller and HFUL Estimators

In a recent paper, Hausman, Newey, Woutersen, Chao, and Swanson (2012) propose a new estimator, HFUL (Heteroscedasticity robust Fuller), for the linear model with endogeneity. This estimator is consistent and asymptotically normally distributed in the many instruments and many weak instruments asymptotics. Moreover, this estimator has moments, just like the estimator by Fuller (1977). The purpose of this note is to discuss at greater length the existence of moments result given in Hausman et al. (2012). In particular, we intend to answer the following questions: Why does LIML not have moments? Why does the Fuller modification lead to estimators with moments? Is normality required for the Fuller estimator to have moments? Why do we need a condition such as Hausman et al. (2012), Assumption 9? Why do we have the adjustment formula

Infrared Diffusion-Ordered Spectroscopy Reveals Molecular Size and Structure

Inspired by ideas from NMR, we have developed Infrared Diffusion-Ordered Spectroscopy (IR-DOSY), which simultaneously characterizes molecular structure and size. We rely on the fact that the diffusion coefficient of a molecule is determined by its size through the Stokes-Einstein relation, and achieve sensitivity to the diffusion coefficient by creating a concentration gradient and tracking its equilibration in an IR-frequency resolved manner. Analogous to NMR-DOSY, a two-dimensional IR-DOSY spectrum has IR frequency along one axis and diffusion coefficient (or equivalently, size) along the other, so the chemical structure and the size of a compound are characterized simultaneously. In an IR-DOSY spectrum of a mixture, molecules with different sizes are nicely separated into distinct sets of IR peaks. Extending this idea to higher dimensions, we also perform 3D-IR-DOSY, in which we combine the conformation sensitivity of femtosecond multi-dimensional IR spectroscopy with size sensitivity

Epidermal growth factor receptor expression in pancreatic lesions induced in the rat by azaserine.

In the present study, the expression of the epidermal growth factor receptor (EGFR) was investigated in putative preneoplastic and neoplastic acinar cell lesions induced in the rat pancreas by azaserine, using Northern blotting, in situ hybridisation (ISH) and immunohistochemistry. EGFR protein levels were decreased in putative preneoplastic eosinophilic acinar cell lesions (atypical acinar cell nodules, AACN) in comparison with normal acinar cells of the pancreas. However, EGFR mRNA expression correlated positively with the volume of AACN in pancreatic homogenates and ISH showed equal or stronger EGFR mRNA expression in AACN than in the surrounding normal acinar cells. Neither EGFR protein nor EGFR mRNA was detected in more advanced lesions such as acinar adenocarcinomas (in situ). Moreover, EGFR protein expression showed an inverse relationship with the mitotic rate of the acinar cells. These findings suggest that down-regulation of EGFR at the protein level may abrogate negative constraints on cell growth, which may stimulate the development of putative preneoplastic AACN to more advanced lesions and, ultimately, acinar adenocarcinomas

Role of cholecystokinin in dietary fat-promoted azaserine-induced pancreatic carcinogenesis in rats.

The role of cholecystokinin in dietary fat-promoted pancreatic carcinogenesis was investigated in azaserine-treated rats, using lorglumide, a highly specific cholecystokinin-receptor antagonist. The animals were killed 8 months after the start of treatment. Cholecystokinin, but not dietary unsaturated fat, increased pancreatic weight. Rats treated with cholecystokinin developed more acidophilic atypical acinar cell nodules, adenomas and adenocarcinomas than control animals. Rats maintained on the high-fat diet developed significantly more adenomas and adenocarcinomas than controls given a diet low in unsaturated fat. Lorglumide largely inhibited the enhancing effect of cholecystokinin, but not of dietary fat, on pancreatic carcinogenesis indicating that it is unlikely that the promoting effect of dietary unsaturated fat on pancreatic carcinogenesis is mediated via cholecystokinin