ExSer: A standalone tool to mine protein data bank (PDB) for secondary structural elements

Detailed structural analysis of protein necessitates investigation at primary, secondary and tertiary levels, respectively. Insight into protein secondary structures pave way for understanding the type of secondary structural elements involved (α-helices, β-strands etc.), the amino acid sequence that encode the secondary structural elements, number of residues, length and, percentage composition of the respective elements in the protein. Here we present a standalone tool entitled "ExSer" which facilitate an automated extraction of the amino acid sequence that encode for the secondary structural regions of a protein from the protein data bank (PDB) file. AVAILABILITY: ExSer is freely downloadable from http://code.google.com/p/tool-exser/     

Enantioselective oxidation of secondary alcohols by quinohaemoprotein alcohol dehydrogenase from Comamonas testosteroni

Purified and reconstituted quinohaemoprotein alcohol dehydrogenase (QH-EDH) from Comamonas testosteroni is shown to oxidize secondary alcohols enantioselectively. The products formed during the oxidation of secondary alcohols were positively identified as the corresponding ketones. In the oxidation of chiral secondary n-alkyl alcohols a preference of the enzyme for the S(+)alcohols was found. The apparent kinetic parameters (K_m and K_max) for a range of n-alkyl alcohols depend on the length of the alcohol chain and the location of the hydroxyl function in the chain. The enzyme is stable up to a temperature of 37 °C. Above this temperature the activity is irreversibly lost. The pH optimum of the enzyme in the conversion of secondary alcohols is 7.7.     

Very-long-chain secondary alcohols and alkanediols in cuticular waxes of Pisum sativum leaves

In cuticular waxes from leaves of Pisum sativum, 19 secondary alcohols, 10 primary/secondary alkanediols and three secondary/secondary alkanediols were identified by various chemical transformations with product assignment employing GC-MS. The homologous series of C29-C33 secondary alcohols (1.1 microg/cm2) was dominated by hentriacontanol isomers (94%). Only octacosanediols and trace amounts of hexacosanediols (< 1%) were detected in the primary/secondary alkanediol faction (0.7 microg/cm2). The secondary/secondary alkanediols (0.12 microg/cm2) contained a single homologue with chain length C31. All three compound classes showed characteristic isomer distributions with secondary functional groups predominantly located between C-14 and C-16. Based on the isomer compositions, the sequence of biosynthetic steps introducing the hydroxyl functions is discussed.     

Increased inpatient mortality in patients hospitalized for atrial fibrillation and atrial flutter with concomitant amyloidosis: Insight from National Inpatient Sample (NIS) 2016-2017

PurposeUsing National Inpatient Database (NIS), comparison of clinical outcomes for patients primarily admitted for atrial fibrillation/flutter with and without a secondary diagnosis of amyloidosis was done. Inpatient mortality was the primary outcome and hospital length of stay (LOS), mean total hospital charges, odds of undergoing cardiac ablation, pharmacologic cardioversion, having a secondary discharge diagnosis of heart block, cardiogenic shock and cardiac arrest were secondary outcomes.MethodsNIS database of 2016, 2017 was used for only adult hospitalizations with atrial fibrillation/flutter as principal diagnosis with and without amyloidosis as secondary diagnosis using ICD-10 codes. Multivariate logistic with linear regression analysis was used to adjust for confounders.Results932,054 hospitalizations were for adult patients with a principal discharge diagnosis of atrial fibrillation/flutter. 830 (0.09%) of these hospitalizations had amyloidosis.Atrial fibrillation/flutter hospitalizations with co-existing amyloidosis have higher inpatient mortality (4.22% vs 0.88%, AOR: 3.92, 95% CI 1.81–8.51, p = 0.001) and likelihood of having a secondary discharge diagnosis of cardiac arrest (2.40% vs 0.51%, AOR: 4.80, 95% CI 1.89–12.20, p = 0.001) compared to those without amyloidosis.ConclusionsHospitalizations of atrial fibrillation/flutter with co-existing amyloidosis have higher inpatient mortality and odds of having a secondary discharge diagnosis of cardiac arrest compared to those without amyloidosis. However, LOS, total hospital charges, likelihood of undergoing cardiac ablation, pharmacologic cardioversion, having a secondary discharge diagnosis of heart block and cardiogenic shock were similar between both groups.     

Diversity and variability of plant secondary metabolism: a mechanistic view

Based upon a brief historical view, the typical features of plant secondary metabolism and its role in chemical interactions between plants and their environment are discussed. Facts and arguments are presented favouring the hypothesis that secondary metabolism evolved under the selection pressure of a competitive environment. The high degree of chemical freedom of secondary metabolism which, in contrast to primary metabolism, allows structural modifications with almost no restrictions, is stressed as mechanistic basis for the generation of chemical diversity. Biochemical and physiological properties of secondary metabolism are in accordance with such a view. It is suggested that the great chemical diversity and intraspecific variability of secondary metabolism is the result of processes of natural selection which act upon highly variable chemical structures. This view is exemplified by the pyrrolizidine alkaloids, a typical class of secondary compounds.     

A quantitative diffraction-based sandwich immunoassay

It is shown that diffraction-based sensing can be enhanced for diagnostic purposes through the use of a secondary label. The limit of detection for anti-rabbit IgG was reduced more than 40-fold by using a gold-conjugated secondary antibody. The response to secondary antibody binding was linear for concentrations from 25 to 500 ng/ml of anti-rabbit IgG, suggesting that quantitative determinations can be readily done. Moreover, the binding of the secondary antibody was observed as soon as 1 min after its introduction to the surface-bound primary complex.     

Combinatorics of saturated secondary structures of RNA.

Following Zuker (1986), a saturated secondary structure for a given RNA sequence is a secondary structure such that no base pair can be added without violating the definition of secondary structure, e.g., without introducing a pseudoknot. In the Nussinov-Jacobson energy model (Nussinov and Jacobson, 1980), where the energy of a secondary structure is -1 times the number of base pairs, saturated secondary structures are local minima in the energy landscape, hence form kinetic traps during the folding process. Here we present recurrence relations and closed form asymptotic limits for combinatorial problems related to the number of saturated secondary structures. In addition, Python source code to compute the number of saturated secondary structures having k base pairs can be found at the web servers link of bioinformatics.bc.edu/clotelab/.     

On the Relation Between the Predicted Secondary Structure and the Protein Size

Accurately predicted protein secondary structure provides useful information for target selection, to analyze protein function and to predict higher dimensional structure. Existing research shows that more data + refined search = better prediction. We analyze relation between the prediction accuracy and another crucial factor, the protein size. Empirical tests performed with two secondary structure predictors on a large set of high-resolution, non-redundant proteins show that the average accuracies for small proteins (<100 residues) equal 73% and 54% for alpha-helices and beta-strands, respectively. The alpha-helix/beta-strand accuracies for very large proteins (>300 residues) equal 77%/68%, respectively. Similarly, the tests with three secondary structure content predictors show that the prediction errors for the small/very large proteins equal 0.13/0.09 and 0.09/0.06 for alpha-helix and beta-strand content, respectively. Our tests confirm that the secondary structure/content predictions for the very large proteins are characterized statistically significantly better quality than prediction for the small proteins. This is in contrast with the tertiary structure predictions in which higher accuracy is obtained for smaller proteins.     

Predicting RNA secondary structures with arbitrary pseudoknots by maximizing the number of stacking pairs.

The paper investigates the computational problem of predicting RNA secondary structures. The general belief is that allowing pseudoknots makes the problem hard. Existing polynomial-time algorithms are heuristic algorithms with no performance guarantee and can handle only limited types of pseudoknots. In this paper, we initiate the study of predicting RNA secondary structures with a maximum number of stacking pairs while allowing arbitrary pseudoknots. We obtain two approximation algorithms with worst-case approximation ratios of 1/2 and 1/3 for planar and general secondary structures, respectively. For an RNA sequence of n bases, the approximation algorithm for planar secondary structures runs in O(n(3)) time while that for the general case runs in linear time. Furthermore, we prove that allowing pseudoknots makes it NP-hard to maximize the number of stacking pairs in a planar secondary structure. This result is in contrast with the recent NP-hard results on psuedoknots which are based on optimizing some general and complicated energy functions.     

Proton,carbon, and nitrogen chemical shifts accurately delineate differences and similarities in secondary structure between the homologous proteins IRAP and IL-1β

Summary ¹H,¹³C, and¹⁵N secondary chemical shifts, defined as the difference between the observed value and the random coil value, have been calculated for interleukin-1 receptor antagonist protein and interleukin-1. Averaging of the secondary chemical shifts with those of adjacent residues was used to smooth out local effects and to obtain a correlation dependent on secondary structure. Differences and similarities in the placement of secondary structure elements in the primary segdences of these structurally homologous proteins are manifested in the smoothed secondary chemical shifts of all three types of nuclei. The close correlation observed between the secondary chemical shifts and the previously defined locations of secondary structure, as defined by traditional methods, exemplifies the advantage of chemical shifts to delineate regions of secondary structure.     

An infrared and circular dichroism combined approach to the analysis of protein secondary structure.

Selected regions of infarred (ir) and circular dichroism (CD) spectral data from 10 proteins were combined and analyzed by a factor analysis method. The regions consisted of the area normalized amide I region from 1700 to 1600 cm-1 for the ir spectra and from 178 to 240 nm for the CD spectra. Each CD spectrum was scaled by a factor of 0.5 before appending the data to the ir spectral data. The scaling factor was deemed necessary to account for relative intensity differences between the ir and CD data and provided nearly optimum agreement between secondary structure estimated by the combined approach to secondary structure determined by X-ray crystallography. The ir/CD combined approach to estimation of helix, beta-sheet, beta-turn, and other or undefined secondary structure agreed with X-ray crystallographic determined structure better than estimation using data from either method alone. Correlation coefficients between X-ray and ir/CD combined secondary structure determinations were 0.99 for helix, 0.90 for beta-sheet, 0.70 for beta-turn, and 0.78 for other structure. The four most significant eigenvectors or basis spectra from eigenanalysis of the ir/CD data are presented as well as generalized inverse spectra for four secondary structures.     

Secondary structural wobble: the limits of protein prediction accuracy

At present, accuracies of secondary structural prediction scarcely go beyond 70-75%. Secondary structural comparison is carried out among sequence-identified proteins. The results show natural wobble between different secondary structural types is possible in homologous families, and the best prediction accuracy will rarely be 100%. Besides shortcoming of the prediction approaches, secondary structural wobble is found to be responsible for nearly all secondary structural prediction limits. Only average 73.2% of amino acid residue is conserved in secondary structural types. The wobble allows alpha-class/coil and beta-class/coil transitions but not direct alpha-class/beta-class transition. Propensity values representing the statistical occurrence of 20 amino acid residues in secondary structural wobbles are given.     

Disparity in the kinetics of onset of hypermutation in immunoglobulin heavy and light chains

The present paper describes a comparative analysis of light chains associated with primary and secondary IgM, as well as with secondary IgG antibodies to fluorescein, undertaken in order to explore the relationship between light chain somatic hypermutation and the isotype switch. The data reveal a disparity in the frequency of somatic hypermutation of secondary IgM heavy versus light chains. Among 20 secondary IgM light chains, a mutation frequency of 1/777 nucleotides was defined. In contrast, our previous analysis of the heavy chains of these molecules had identified a mutation frequency of 1/129. Among 17 IgG-derived light chains, obtained from animals killed at the same time point as those from which the secondary IgM antibodies were obtained, we measured a mutation frequency of 1/77. Finally, analysis of 20 light chains derived from primary IgM antibodies revealed a mutation frequency of only 1/1192 nucleotides. These data demonstrate that, prior to the class switch, light chain mutation occurs at a frequency considerably lower than that measured for the associated heavy chain gene. Six additional apparent mutations in the secondary IgM antibody 95B3 were all shared with a set of IgG antifluorescein antibodies belonging to the Vkappa 34 family. It is suggested that these light chains represent the products of a previously uncharacterized germ line gene.     

海南岛热带低地雨林刀耕火种弃耕地自然恢复过程中的群落构建

研究群落构建机制是群落生态学的一个重要目标, 群落动态过程中的构建规律对于了解群落演替机理有重要的作用。该文以海南岛刀耕火种干扰后自然恢复的10 hm ²热带低地雨林为研究对象, 通过比较不同恢复阶段的次生林(15年、30年和60年)和老龄林在幼苗、幼树和成年树群落的物种组成, 揭示次生演替过程中的群落构建规律。研究结果表明, 老龄林中不同径级群落的物种多样性及不同径级间的物种相似度显著高于各恢复阶段的次生林, 但优势种在群落中的比例低于各恢复阶段的次生林。随着自然恢复过程的进行, 次生林群落物种组成与老龄林的相似性也逐渐增大, 支持演替平衡理论。所有恢复阶段样地中幼苗的个体、物种丰富度和基于多度涵盖估计量(ACE)都低于幼树和成年树群落, 幼苗层物种组成与幼树、成年树也有较大差异, 说明新增到幼苗群落可能是一个难于预测的过程。研究结果说明了确定过程和随机过程共同决定了次生演替的群落构建。     

ITS2, 18S, 16S or any other RNA — simply aligning sequences and their individual secondary structures simultaneously by an automatic approach

Secondary structures of RNA sequences are increasingly being used as additional information in reconstructing phylogenies and/or in distinguishing species by compensatory base change (CBC) analyses. However, in most cases just one secondary structure is used in manually correcting an automatically generated multiple sequence alignment and/or just one secondary structure is used in guiding a sequence alignment still completely generated by hand. With the advent of databases and tools offering individual RNA secondary structures, here we re-introduce a twelve letter code already implemented in 4SALE – a tool for synchronous sequence and secondary structure alignment and editing – that enables one to align RNA sequences and their individual secondary structures synchronously and fully automatic, while dramatically increasing the phylogenetic information content. We further introduce a scaled down non-GUI version of 4SALE particularly designed for big data analysis, and available at: http://4sale.bioapps.biozentrum.uni-wuerzburg.de.     

Pfold: RNA secondary structure prediction using stochastic context-free grammars

RNA secondary structures are important in many biological processes and efficient structure prediction can give vital directions for experimental investigations. Many available programs for RNA secondary structure prediction only use a single sequence at a time. This may be sufficient in some applications, but often it is possible to obtain related RNA sequences with conserved secondary structure. These should be included in structural analyses to give improved results. This work presents a practical way of predicting RNA secondary structure that is especially useful when related sequences can be obtained. The method improves a previous algorithm based on an explicit evolutionary model and a probabilistic model of structures. Predictions can be done on a web server at http://www.daimi.au.dk/~compbio/pfold.