Ab-initio and modeling study of some amino acid-tRNA: NMR shielding and thermodynamic of solvent effect (Poster Presentation)

The tRNA molecule takes suitable amino acid to the ribosome for the formation of peptide bonds. In starting the peptide chain, the first amino acid which is taken to the ribosome is methionine. We have simulated methionine-amino acid bonding and amino acid-tRNA bonding, using a mixed study of quantum mechanics ab-initio and molecular mechanics. NMR shielding tensors and thermodynamic parameters and total energies are also calculated. It is important to understand the physical properties and the environmental conditions in which the dipeptides cause the tRNA to attach to a wrong amino acid. One of the properties studied is the dielectric environment of in which the bonding occurs. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Efficient Threshold Selection for Multivariate Total Variation Denoising

Total variation (TV) denoising is still attracting attention with theoretical and computational motivations, for its conceptual simplicity of solving a lasso-like convex problem and its good properties for preserving sharp edges and contours in objects with spatial structures like natural images, although more modern and recent techniques specifically tailored to image processing have been developed. TV induces variation-sparsity in the sense that the reconstruction is piecewise constant with a small number of jumps. A threshold parameter λ controls the number of jumps and the quality of the estimation. Since calculation of the TV estimate in high dimension is computationally intensive for a given λ, we propose to calculate the TV estimate for only two sequential λ’s. Our adaptive procedure is based on large deviation of stochastic processes and extreme value theory. We also show that TV can perform exact segmentation in dimension one, under an alternating sign condition for some prescribed threshold. We apply our procedure to denoise a collection of 1D and 2D test signals verifying empirically the effectiveness of our approach. Codes are given to reproduce our results in a provided PURL.     

NMR shielding and a thermodynamic study of the effect of environmental exposure to petrochemical solvent on DPPC,an important component of lung surfactant

The chemical and petrochemical industries are the major air polluters. Millions of workers are exposed to toxic chemicals on the job, and it is becoming more toxic, causing much damage to respiratory system, today. One of the main components of lung alveoli is a surfactant. DPPC (Dipalmitolphosphatidylcholine) is the predominant lipid component in the lung surfactant, which is responsible for lowering surface tension in alveoli. In this article, we used an approximate model and ab initio computations to describe interactions between DPPC and some chemical solvents, such as benzene, toluene, heptane, acetone, chloroform, ether, and ethanol, which cause lung injuries and lead to respiratory distress such as ARDS. The effect of these solvents on the conformation and disordering of the DPPC head group was investigated by calculations at the Hatree-Fock level using the 6–31G basis set with the Onsager continuum solvation, GAIO, and frequency models. The simulation model was confirmed by accurate NMR measurements as concerns conformational energy. Water can be the most suitable solvent for DPPC. Furthermore, this study shows that ethanol has the most destructive effect on the conformation and lipid disorder of the DPPC head group of the lung surfactant in our model. Our finding will be useful for detecting the dysfunction of DPPC in the lung surfactant caused by acute or chronic exposures to air toxics from petrochemical organic solvent emission source and chronic alcohol consumption, which may lead to ARDS. The article is published in the original.