Perfluoroalkyl compounds are known to exhibit a hydrophobic character on the surface of the material, although the CF bond has a large dipole, which should make the molecular surface polar and hydrophilic. This inconsistency has long been a chemical matter to be solved. Herein, a stratified dipole‐arrays model is proposed: the molecular polar surface can be fully hidden by forming a two‐dimensional aggregate of perfluoroalkyl (Rf) groups; this aggregate is spontaneously induced by dipole–dipole interaction arrays owing to the helical structure of the Rf group. In this model, a ‘short’ Rf group should play the role of a single Rf group with a hydrophilic character, whereas a ‘long’ Rf group should spontaneously form a hexagonal aggregate. To examine this model, Rf‐containing myristic acids with various Rf lengths have been synthesized and their aggregation properties are analyzed by using the Langmuir monolayer technique aided by precise IR spectroscopic analysis.

Abstract:A predictive software system, SOSUI-GramN, was developed for assessing the subcellular localization of proteins in Gramnegative bacteria. The system does not require the sequence homology data of any known sequences; instead, it uses only physicochemical parameters of the N-and C-terminal signal sequences, and the total sequence. The precision of the prediction system for subcellular localization to extracellular, outer membrane, periplasm, inner membrane and cytoplasmic medium was 92.3%, 89.4%, 86.4%, 97.5% and 93.5%, respectively, 000with corresponding recall rates of 70.3%, 87.5%, 76.0%, 97.5% and 88.4%, respectively. The overall performance for precision and recall obtained using this method was 92.9% and 86.7%, respectively. The comparison of performance of SOSUI-GramN with that of other methods showed the performance of prediction for extracellular proteins, as well as inner and outer membrane proteins, was either superior or equivalent to that obtained with other systems. SOSUI-GramN particularly improved the accuracy for predictions of extracellular proteins which is an area of weakness common to the other methods.Keywords: subcellular localization of proteins; Gram-negative bacteria; physicochemical parameters; amino acids Background:Subcellular localization is one of the most important characteristics of proteins and is central to understanding their function and the constitution of biological systems. In bacteria, information related to the subcellular location of pathogen proteins can facilitate the development of drugs and vaccines for treatment. We previously developed a system called SOSUI for predicting inner membrane proteins from amino acid sequences [1, 2]. Because of its high accuracy, this system can be used to improve the performance of the prediction of subcellular localization. An advantage of SOSUI is that all of the parameters used for the prediction [1, 2] are the physicochemical properties of amino acids. By adopting a similar approach, we developed in this work a novel method for predicting subcellular localization in Gram-negative bacteria for proteins in the extracellular, the outer membrane, the periplasm, and the medium cytoplasm, which are less hydrophobic than the proteins in the inner membrane. The physicochemical properties of the N-and C-terminal signal regions, as well as a whole sequences were also used for predicting protein localization. By combining this method with the SOSUI membrane prediction system, we constructed a unified system, referred to as SOSUI-GramN, for the complete characterization of subcellular protein localization in the five compartments of Gram-negative bacteria.

We describe a novel method for predicting a signal peptide of which three-domain (tripartite) structure is recognized by three modules of the software system. The first module numerates hydrophobic segment in N-terminal 100 residues, the second predicts signal sequences including both signal peptides and signal anchors, and the third discriminates signal peptides. Two novel indexes, SS-and SP-indexes, were developed for the discrimination of signal sequences and signal peptides, respectively, by calculating the relative propensities of amino acids at the carboxyl-terminal end of the hydrophobic region. The number of adjustable parameters in the whole system was only five. When three groups of data (917 signal peptides, 103 signal anchors and 544 non-signal sequences) were analyzed, signal peptides of eukaryotes could be discriminated with the Matthews correlation coefficient of 0.89. The signal peptide predictor SOSUIsignal is available at the web site: http://bp.nuap.nagoya-u.ac.jp/sosui/sosuisignal/sosuisignal_submit.html. This system has the advantage of very fast calculation.

We examine accuracy of θ 23 determination in future long-baseline (LBL) ν µ disappearance experiments in the three-flavor mixing scheme of neutrinos. Despite that the error of sin 2 2θ 23 is indeed a few% level at around the maximal mixing, we show that the error of physics variable s 2 23 is large, δ(s 2 23 )/s 2 23 ≃ 10-20%, depending upon regions of θ 23 . The errors are severely affected by the octant degeneracy of θ 23 , and δ(s 2 23 ) is largely amplified by the Jacobian factor relating these two variables in a region near to the maximal mixing. The errors are also affected by the uncertainty due to unknown value of θ 13 ; δ(s 2 23 ) is doubled at off maximal in the second octant of θ 23 where the effect is largest. To overcome this problem, we discuss combined analysis with ν e appearance measurement in LBL experiments, or with reactor measurement of θ 13 . For possible relevance of sub-leading effects even in the next-generation LBL experiments, we give a self-contained derivation of the survival probability to the next to leading order in s 2 13 and ∆m 2 21 /∆m 2 31 .

The 13 C CP/MAS NMR, X-ray diffraction, and Raman spectroscopies were used for monitoring the structural transition of Samia cynthia ricini (S. c. ricini) silk fibroin induced by stretching. Here the silk fibroin was obtained from the aqueous solution stored in the silk gland. All of these spectroscopic data indicate that the structural transition from R-helix to β-sheet occurs with increasing the stretching ratio, especially between the stretching ratios, ×4 and ×6. The 13 C chemical shifts of Ala Cβ peak in the 13 C CP/MAS NMR spectrum change significantly depending on R-helix, random coil, and two kinds of β-sheet structure, which make it possible to clarify the local structure and structural transition. Actually, the fraction of individual structure in the silk fibroin samples was determined from decomposition of the Ala Cβ peak by assuming a Gaussian line shape. To examine the conformational change of Ala residues of the polyalanine region in S. c. ricini silk fibroin observed with these spectroscopic methods, MD simulations for four peptide molecules, AGGAGG(A) 12GGAGAG, with R-helix conformation were performed in the presence of water molecules under different tensile strengths, and then additional MM calculations were performed after removal of water molecules. The change in the conformational character of Ala residues induced by stretching is explicable by these calculations.