螺旋结构与旋光性——2.脂族链状化合物的螺旋结构和旋光性

利用弯曲键理论,详细讨论了旋光性的脂肪族链状化合物分子内存在的螺旋结构,同样是右螺是右旋的,左螺旋是左旋的。从螺旋方向可以推断旋光方向,知道旋光方向也可以推断构型。     

Structure-property modelling of complex formation of strontium with organic ligands in water

The method of substructural molecular fragments based on representation of the molecular graph by ensembles of fragments and involving calculations of those contributions to the given property is applied to the modelling of stability constants of the complexes of strontium(II) with organic ligands in water. Reliability of predictions of developed structure-property models was examined using three different test sets of structurally diverse ligands. The obtained models have been used for generation and screening of combinatorial library of virtual ligands. Some hypothetical efficient Sr(II) binders were suggested.     

What to Learn from a Comparative Genomic Sequence Analysis of <Emphasis Type="Italic">L</Emphasis>-Carnitine Dehydrogenase

Summary. In contrast to eukaryotic cells certain eubacterial strains have acquired the ability to utilize L-carnitine (R-(–)-3-hydroxy-4-(trimethylamino)butyrate) as sole source of energy, carbon and nitrogen. The first step of the L-carnitine degradation to glycine betaine is catalysed by L-carnitine dehydrogenase (L-CDH, EC 1.1.1.108) and results in the formation of the dehydrocarnitine. During the oxidation of L-carnitine a simultaneous conversion of the cofactor NAD⁺ to NADH takes place. This catabolic reaction has always been of keen interest, because it can be exploited for spectroscopic L-carnitine determination in biological fluids – a quantification method, which is developed in our lab – as well as L-carnitine production.Based on a cloned L-CDH sequence an expedition through the currently available prokaryotic genomic sequence space began to mine relevant information about bacterial L-carnitine metabolism hidden in the enormous amount of data stored in public sequence databases. Thus by means of homology-based and context-based protein function prediction is revealed that L-CDH exists in certain eubacterial genomes either as a protein of approximately 35 kDa or as a homologous fusion protein of approximately 54 kDa with an additional putative domain, which is predicted to possess a thioesterase activity. These two variants of the enzyme are found on one hand in the genome sequence of bacterial species, which were previously reported to decompose L-carnitine, and on the other hand in gram-positive bacteria, which were not known to express L-CDH. Furthermore we could not only discover that L-CDH is located in a conserved genetic entity, which genes are very likely involved in this L-carnitine catabolic pathway, but also pinpoint the exact genomic sequence position of several other enzymes, which play an essential role in the bacterial metabolism of L-carnitine precursors.     

Quantitative surface analysis by Auger and x-ray photoelectron spectroscopy

Recent developments in quantitative surface analysis by Auger (AES) and x-ray photoelectron (XPS) spectroscopies are reviewed and problems relating to a more accurate quantitative interpretation of AES/XPS experimental data are discussed. Special attention is paid to consideration of elementary physical processes involved and influence of multiple scattering effects on signal line intensities. In particular, the major features of core-shell ionization by electron impact, Auger transitions and photoionization are considered qualitatively and rigorous approaches used to calculate the respective transition probabilities are analysed. It is shown that, in amorphous and polycrystalline targets, incoherent scattering of primary and signal Auger and photoelectrons can be described by solving analytically a kinetic equation with appropriate boundary conditions. The analytical results for the angular and energy distribution, the mean escape depth, and the escape probability as a function of depth of origin of signal electrons as well as that for the backscattering factor in AES are in good agreement with the corresponding Mote Carlo simulation data. Methods for inelastic background subtraction, surface composition determination and depth-profile reconstructions by angle-resolved AES/XPS are discussed. Examples of novel techniques based on x-ray induced photoemission are considered.     

无脂链磺化酞菁铜多层膜体系：电子非弹性平均自由程的研究

磺化酞菁铜多层膜体系是利用Langmuir-Blodgett技术制备的有序有机分子膜,它对于XPS测试有很好的稳定性,本文在固定电子出射角的条件下利用XPS方法研究了不同厚度的膜样品中Cu_((2(?))_(3/2))、Ni_(1(?))、S_(2p)峰强度的变化规律,讨论了膜内分子有序排列引起的散射效应对电子平均自由程的影响。     

疏水分配常数用于反相液相色谱保留值的预测

在反相液相色谱保留值基本方程log k_′=a+_cC_B的基础上,描述了采用疏水分配常数及氢键作用能来预测a、c参数的方法,并系统讨论了疏水分配常数对参数a、c的影响,借此对反相液相色谱宽浓度范围内的保留值进行了预测。     

Partial least-squares regression and fuzzy clustering — A joint approach

Chemical and physical analyses of malt, the main ingredient of beer, have been used to predict the concentration of certain volatile compounds in the finished beer.The prediction was done by means of the partial least squares regression (PLS2) in SIMCA. The total data set as well as individual malt clusters were submitted to PLS analysis. Best prediction was obtained by separating the total object matrix in classes according to similarity found by fuzzy pattern recognition (FCV). FCV was also used to separate the beer variables in classes and to select the subset of variables to be predicted.A joint approach of fuzzy pattern recognition to identify groups of samples and SIMCA-PLS2 to predict several dependent variables is suggested as a powerful tool in process-analytical chemistry.     

The de novo design of median molecules within a property range of interest

Summary In this paper an application is presented of the median molecule workflow to the de novo design of novel molecular entities with a property profile of interest. Median molecules are structures that are optimised to be similar to a set of existing molecules of interest as an approach for lead exploration and hopping. An overview of this workflow is provided together with an example of an instance using the similarity to camphor and menthol as objectives. The methodology of the experiments is defined and the workflow is applied to designing novel molecules for two physical property datasets: mean molecular polarisability and aqueous solubility. This paper concludes with a discussion of the characteristics of this method.     

predForm-Site: Formylation site prediction by incorporating multiple features and resolving data imbalance

Formylation is one of the newly discovered post-translational modifications in lysine residue which is responsible for different kinds of diseases. In this work, a novel predictor, named predForm-Site, has been developed to predict formylation sites with higher accuracy. We have integrated multiple sequence features for developing a more informative representation of formylation sites. Moreover, decision function of the underlying classifier have been optimized on skewed formylation dataset during prediction model training for prediction quality improvement. On the dataset used by LFPred and Formator predictor, predForm-Site achieved 99.5% sensitivity, 99.8% specificity and 99.8% overall accuracy with AUC of 0.999 in the jackknife test. In the independent test, it has also achieved more than 97% sensitivity and 99% specificity. Similarly, in benchmarking with recent method CKSAAP_FormSite, the proposed predictor significantly outperformed in all the measures, particularly sensitivity by around 20%, specificity by nearly 30% and overall accuracy by more than 22%. These experimental results show that the proposed predForm-Site can be used as a complementary tool for the fast exploration of formylation sites. For convenience of the scientific community, predForm-Site has been deployed as an online tool, accessible at http://103.99.176.239:8080/predForm-Site.     

Protein fold recognition

Summary An important, yet seemingly unattainable, goal in structural molecular biology is to be able to predict the native three-dimensional structure of a protein entirely from its amino acid sequence. Prediction methods based on rigorous energy calculations have not yet been successful, and best results have been obtained from homology modelling and statistical secondary structure prediction. Homology modelling is limited to cases where significant sequence similarity is shared between a protein of known structure and the unknown. Secondary structure prediction methods are not only unreliable, but also do not offer any obvious route to the full tertiary structure. Recently, methods have been developed whereby entire protein folds are recognized from sequence, even where little or no sequence similarity is shared between the proteins under consideration. In this paper we review the current methods, including our own, and in particular offer a historical background to their development. In addition, we also discuss the future of these methods and outline the developments under investigation in our laboratory.