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.     

Rotational isomerism involving an acetylenic carbon. Part 5: Restricted rotation about acetylenic axis in sterically crowded bis(1-phenyl-9-anthryl)ethynes

The title sterically crowded di-9-anthrylethyne derivative with 3,5-ⁱPr₂-phenyl groups at 1-position showed a barrier to rotation about the acetylenic axis of 18.0 kcal mol⁻¹ based on a dynamic NMR study, which is an extremely high value for acyclic diarylethynes. The mechanism of the dynamic stereochemistry and the substituent effect on the rotational barrier are discussed.     

Isoperichoric focusing field-flow fractionation and thin layer isoperichoric focusing based on coupling of gradient generated by primary field with secondary field action: general principles and performances

The primary field forces can generate spatially oriented gradient of the effective property of a continuum or pseudo-continuum fluid (carrier liquid). When this gradient is coupled with the action of a secondary field of identical or different nature the isoperichoric focused zones of the dispersed species can appear. Consequently, they can be separated according to differences responding to the property gradient of the carrier liquid. This concept can be applied under static (non-flow) conditions in thin layer focusing as well as under dynamic conditions with the elution due to the carrier liquid flow in focusing field-flow fractionation. The gradient established by the action of the primary field and the concentration distribution of the isoperichoric focused zone formed by the coupled effect of the gradient and of the primary or secondary field are described theoretically. The rigorous relationship describing the shape of the focused zone is compared with the approximate solutions. The performances of the proposed principle were evaluated by model calculations. Potential experimental configurations considering the implementation of the static and dynamic conditions are discussed. The generalized isoperichoric focusing theory can be applied to describe the particular processes operating in analytical and preparative focusing separations of the particles of various, but especially of biological origin.     

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.     

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.     

A new method for predicting conduction anesthesia

A new method for predicting conduction anesthesia has been suggested. The method is based on calculation of theP matrix probabilities of interatomic contacts for each molecule of the compounds considered. TheP matrix enables one to evaluate the main tendencies of atoms and atomic groups to interact in biochemical sorption on the nerve fiber surface. The minimum effective concentrations calculated for 25 compounds are in good agreement with the experimental data. The correlation coefficient between the experimental and calculated values is 0.98 when the standard deviation is 0.1 mmol L⁻¹. Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 10, pp. 1781–1784, October, 1997.     

Properties of a genetic algorithm extended by a random self-learning operator and asymmetric mutations: A convergence study for a task of powder-pattern indexing

Genetic algorithms represent a powerful global-optimisation tool applicable in solving tasks of high complexity in science, technology, medicine, communication, etc. The usual genetic-algorithm calculation scheme is extended here by introduction of a quadratic self-learning operator, which performs a partial local search for randomly selected representatives of the population. This operator is aimed as a minor deterministic contribution to the (stochastic) genetic search. The population representing the trial solutions is split into two equal subpopulations allowed to exhibit different mutation rates (so called asymmetric mutation). The convergence is studied in detail exploiting a crystallographic-test example of indexing of powder diffraction data of orthorhombic lithium copper oxide, varying such parameters as mutation rates and the learning rate. It is shown through the averaged (over the subpopulation) fitness behaviour, how the genetic diversity in the population depends on the mutation rate of the given subpopulation. Conditions and algorithm parameter values favourable for convergence in the framework of proposed approach are discussed using the results for the mentioned example. Further data are studied with a somewhat modified algorithm using periodically varying mutation rates and a problem-specific operator. The chance of finding the global optimum and the convergence speed are observed to be strongly influenced by the effective mutation level and on the self-learning level. The optimal values of these two parameters are about 6 and 5%, respectively. The periodic changes of mutation rate are found to improve the explorative abilities of the algorithm. The results of the study confirm that the applied methodology leads to improvement of the classical genetic algorithm and, therefore, it is expected to be helpful in constructing of algorithms permitting to solve similar tasks of higher complexity.