Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

High Resolution Proton NMR Spectroscopy of Multiple Sclerosis Lesions

Abstract: Tissue from postmortem multiple sclerosis and normal control brains was extracted with perchloric acid and analysed using proton NMR spectroscopy. The content of N -acetyl-derived groups (the sum of N -acetylaspartate, acetate, and N -acetylaspartylglutamate) was decreased in multiple sclerosis plaques compared with normal control white matter (mean, 4.36 vs. 6.64 µmol/g wet weight). In normal appearing white matter adjacent to plaques a corresponding decrease was seen, with no change in white matter distant from plaques. A decrease in the content of total creatine was observed in multiple sclerosis plaques in comparison with normal control white matter (mean, 4.64 vs. 6.56 µmol/g wet weight), which correlated strongly with the decrease in N -acetyl-derived groups. No changes in other metabolites such as total choline or myo -inositol were seen. The decreases in content of N -acetyl-derived groups are in agreement with observations from in vivo proton NMR spectroscopy in multiple sclerosis patients. The decrease in total creatine is in contrast to most of the observations made in vivo where total creatine is assumed to be unchanged and metabolite levels are often expressed as a total creatine ratio. The use of a total creatine ratio in vivo could lead to an underestimation of reductions in N -acetylaspartate and an apparent increase in other metabolites in the multiple sclerosis lesion.     

Capturing pair-wise epistatic effects associated with three agronomic traits in barley

Genetic association mapping has been widely applied to determine genetic markers favorably associated with a trait of interest and provide information for marker-assisted selection. Many association mapping studies commonly focus on main effects due to intolerable computing intensity. This study aims to select several sets of DNA markers with potential epistasis to maximize genetic variations of some key agronomic traits in barley. By doing so, we integrated a MDR (multifactor dimensionality reduction) method with a forward variable selection approach. This integrated approach was used to determine single nucleotide polymorphism pairs with epistasis effects associated with three agronomic traits: heading date, plant height, and grain yield in barley from the barley Coordinated Agricultural Project. Our results showed that four, seven, and five SNP pairs accounted for 51.06, 45.66 and 40.42% for heading date, plant height, and grain yield, respectively with epistasis being considered, while corresponding contributions to these three traits were 45.32, 31.39, 31.31%, respectively without epistasis being included. The results suggested that epistasis model was more effective than non-epistasis model in this study and can be more preferred for other applications.