BTEVAL: a server for evaluation of beta-turn prediction methods

This paper describes a web server BTEVAL, developed for assessing the performance of newly developed beta-turn prediction method and it's ranking with respect to other existing beta-turn prediction methods. Evaluation of a method can be carried out on a single protein or a number of proteins. It consists of clean data set of 426 non-homologous proteins with seven subsets of these proteins. Users can evaluate their method on any subset or a complete set of data. The method is assessed at amino acid level and performance is evaluated in terms of Qtotal, Qpredicted, Qobserved and MCC measures. The server also compares the performance of the method with other existing beta-turn prediction methods such as Chou-Fasman algorithm, Thornton's algorithm, GORBTURN, 1-4 and 2-3 Correlation model, Sequence coupled model and BTPRED. The server is accessible from http://imtech.res.in/raghava/bteval/     

Protein beta-turn prediction using nearest-neighbor method

MOTIVATION: With the emerging success of protein secondary structure prediction through the applications of various statistical and machine learning techniques, similar techniques have been applied to protein beta-turn prediction. In this study, we perform protein beta-turn prediction using a k-nearest neighbor method, which is combined with a filter that uses predicted protein secondary structure information. Traditional beta-turn prediction from k-nearest neighbor method is modified to account for the unbalanced ratio of the natural occurrence of beta-turns and non-beta-turns. RESULTS: Our prediction scheme is tested on a set of 426 non-homologous protein sequences. The prediction scheme consists of two stages: k-nearest neighbor method stage and filtering stage. Variations of the k-nearest neighbor method were used to take property of beta-turns into consideration. Our filtering method uses beta-turn/non-beta-turn estimates from the k-nearest neighbor method stage and predicted protein secondary structure information from PSI-PRED in order to get new beta-turn/non-beta-turn estimate. Our result is compared with the previously best known beta-turn prediction method on the dataset of 426 non-homologous protein sequences and is shown to give slightly superior performance at significantly lower computational complexity. AVAILABILITY: Contact the author for information on the source code of the programs used.     

Analysis and prediction of the different types of beta-turn in proteins

beta-Turns have been extracted from 59 non-identical proteins (resolution 2 A) using the standard criterion that the distance between C alpha (i) and C alpha (i + 3) is less than 7 A (1 A = 0.1 nm). The beta-turns have been classified, using phi, psi angles, into seven conventional turn types (I, I', II, II', IV, VIa, VIb) and a new class of beta-turn, designated type VIII, in which the central residues (i + 1, i + 2) adopt an alpha R beta conformation. Most beta-turn types are found in various topological environments, with the exception of I' and II' beta-turns, where 83% and 50%, respectively, are found in beta-hairpins. Sufficient data have been gathered to enable, for the first time, the separate statistical analysis of type I and II beta-turns. The two turn types have been shown to be strikingly different in their sequence preferences. Type I turns favour Asp, Asn, Ser and Cys at i; Asp, Ser, Thr and Pro at i + 1; Asp, Ser, Asn and Arg at i + 2; Gly, Trp and Met at i + 3, whilst type II turns prefer Pro at i + 1; Gly and Asn at i + 2; Gln and Arg at i + 3. These preferences have been explained by the specific side-chain interactions observed within the X-ray structures. The positional trends for type I and II beta-turns have been incorporated into the simple empirical predictive algorithm originally developed by P.N. Lewis et al. The program has improved the positional prediction of beta-turns, and has enhanced and extended the method by predicting the type of beta-turn. Since the observed preferences reflect local interactions these predictions are applicable not only to proteins, but also to peptides, many of which are thought to contain beta-turns.     

An evaluation of purification methods for baculoviruses

In Biomphalaria glabrata parasitized by Schistosoma mansoni there was an increase in relative weight of the digestive gland-gonad complex and a decrease in glycogen in that complex and in the remainder of the carcass by day 25. Glycogen levels further decreased close to zero and remained at this low level for the duration of the experiment. Relative weight of the digestive gland-gonad reached a peak at day 30 and decreased toward normal by day 40. Galactogen levels in the albumen gland, although decreased slightly, were not significantly lower than in normal snails. In starved snails, glycogen and galactogen decreased significantly below normal at day 21 and remained at a low level until the experiment ended. This study raises the possibility that starvation of the host by the parasite may play a significant role in the pathology observed in this infection.     

A neural network method for prediction of beta-turn types in proteins using evolutionary information

MOTIVATION: The prediction of beta-turns is an important element of protein secondary structure prediction. Recently, a highly accurate neural network based method Betatpred2 has been developed for predicting beta-turns in proteins using position-specific scoring matrices (PSSM) generated by PSI-BLAST and secondary structure information predicted by PSIPRED. However, the major limitation of Betatpred2 is that it predicts only beta-turn and non-beta-turn residues and does not provide any information of different beta-turn types. Thus, there is a need to predict beta-turn types using an approach based on multiple sequence alignment, which will be useful in overall tertiary structure prediction. RESULTS: In the present work, a method has been developed for the prediction of beta-turn types I, II, IV and VIII. For each turn type, two consecutive feed-forward back-propagation networks with a single hidden layer have been used where the first sequence-to-structure network has been trained on single sequences as well as on PSI-BLAST PSSM. The output from the first network along with PSIPRED predicted secondary structure has been used as input for the second-level structure-to-structure network. The networks have been trained and tested on a non-homologous dataset of 426 proteins chains by 7-fold cross-validation. It has been observed that the prediction performance for each turn type is improved significantly by using multiple sequence alignment. The performance has been further improved by using a second level structure-to-structure network and PSIPRED predicted secondary structure information. It has been observed that Type I and II beta-turns have better prediction performance than Type IV and VIII beta-turns. The final network yields an overall accuracy of 74.5, 93.5, 67.9 and 96.5% with MCC values of 0.29, 0.29, 0.23 and 0.02 for Type I, II, IV and VIII beta-turns, respectively, and is better than random prediction. AVAILABILITY: A web server for prediction of beta-turn types I, II, IV and VIII based on above approach is available at http://www.imtech.res.in/raghava/betaturns/ and http://bioinformatics.uams.edu/mirror/betaturns/ (mirror site).     

An evaluation protocol for subtype-specific breast cancer event prediction

In recent years increasing evidence appeared that breast cancer may not constitute a single disease at the molecular level, but comprises a heterogeneous set of subtypes. This suggests that instead of building a single monolithic predictor, better predictors might be constructed that solely target samples of a designated subtype, which are believed to represent more homogeneous sets of samples. An unavoidable drawback of developing subtype-specific predictors, however, is that a stratification by subtype drastically reduces the number of samples available for their construction. As numerous studies have indicated sample size to be an important factor in predictor construction, it is therefore questionable whether the potential benefit of subtyping can outweigh the drawback of a severe loss in sample size. Factors like unequal class distributions and differences in the number of samples per subtype, further complicate comparisons. We present a novel experimental protocol that facilitates a comprehensive comparison between subtype-specific predictors and predictors that do not take subtype information into account. Emphasis lies on careful control of sample size as well as class and subtype distributions. The methodology is applied to a large breast cancer compendium involving over 1500 arrays, using a state-of-the-art subtyping scheme. We show that the resulting subtype-specific predictors outperform those that do not take subtype information into account, especially when taking sample size considerations into account.     

Protein beta-turn assignments

A classical way to analyze protein 3D structures or models is to investigate their secondary structures. Their predictions are also widely used as a help to build new 3D models. Thus, hundreds of prediction methods have been proposed. Nonetheless before predicting, secondary structure assignment is required even if not trivial. Therefore numerous but diverging assignment methods have been developed. Beta-turns constitute the third most important secondary structures. However, no analysis to compare the beta-turn distributions according to different secondary structure assignment methods has ever been done. We propose in this paper to analyze and evaluate the results of such a comparison. We highlight some important divergence that could have important consequence for the analysis and prediction of beta-turns.     

An evaluation of detection methods for large lariat RNAs

Ty1 elements are long terminal repeat (LTR) retrotransposons that reside within the genome of Saccharomyces cerevisiae. It has been known for many years that the 2'-5' phosphodiesterase Dbr1p, which debranches intron lariats, is required for efficient Ty1 transposition. A recent report suggested the intriguing possibility that Ty1 RNA forms a lariat as a transposition intermediate. We set out to further investigate the nature of the proposed Ty1 lariat branchpoint. However, using a wide range of techniques we were unable to find any evidence for the proposed lariat structure. Furthermore, we demonstrate that some of the techniques used in the initial study describing the lariat are capable of incorrectly reporting a lariat structure. Thus, the role of the Dbr1 protein in Ty1 retrotransposition remains elusive.     

Membrane protein prediction methods

We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. In general, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling.     

Cerebrospinal fluid cell preparation methods. An evaluation.

Although the cells from cerebrospinal fluid are widely used for diagnostic purposes, the cell yield on the microscopic slide is only rarely considered and mostly unsatisfactory. A reevaluation of several preparatory methods showed a very low yield with the Sayk-type chamber, a modest yield with the cytocentrifuge and the best yield with a simple, self-adhering chamber on slides coated with a polycation.     

An evaluation of non-destructive methods to estimate total chlorophyll content

The portable chlorophyll (Chl) meter (CL-01, Hansatech) has been successfully used for a rapid and direct estimation of total Chl content in the leaves of some crops. We compared CL-01 meter readings (Chl value) and Chl contents in leaves of Zea mays, Cucumis sativus, Raphanus sativus, and Ceiba speciosa. Chl index was linearly and positively correlated to Chl content in all the species.     

An NMR conformational analysis of cyclic bradykinin mimics. Evidence for a beta-turn

A detailed NMR study is carried out in acetonitrile/water solutions on three novel cyclic bradykinin antagonist analogues, BKM-824, BKM-870, and BKM-872, to examine their solution structures, and to correlate the structures with bradykinin antagonist and anti-cancer activities. The solution structures of the cyclic peptides are correlated with the structural data for known linear bradykinin antagonists. The sequences are: BKM-824 c[Ava-Ig1-Ser-DF5F-Oic-Arg] where Ava is 5-aminovaleric acid, Ig1 is alpha-(2-indanyl)glycine, F5F is pentafluorophenylalanine, and Oic is (2S,3aS,7aS)-octahydroindole-2-carboxylic acid; BKM-870; c[DArg-Arg-Add-DF5F-Oic-Arg] where Add is 12-aminododecanoic acid; and BKM-872; c[DArg-Arg-Eac-Ser-DF5F-Oic-Arg] where Eac is 6-aminocaproic acid. BKM-824 was the only peptide within this series that possessed a discernable solution structure. The NMR data indicate the presence of a type I beta-turn between residues F5F4 and Ava1, a C-terminal-like end. Molecular dynamics calculations show that a type I beta-turn from DF5F4 to Ava1 does exist although the turn was somewhat distorted. This result differs from the structures seen in linear bradykinin antagonists, which usually possess a type II'beta-turn at the C-terminal end and the presence of a defined turn is correlated with bradykinin antagonist activity. There is no solution structure for BKM-870 and BKM-872 but a correlation between the primary sequence Arg(terminal)-DArg1-Arg2-long chain aliphatic amino acid and anti-cancer activity is evident.     

An evaluation of some complexing methods for the histochemistry of calcium

Summary A selection of reagents capable of complexing with calcium in various ways was compared by applying them to tissue sections known to contain calcium in a variety of physiochemical states. Their histochemical potential was evaluated according to their sensitivity, specificity, accuracy of localisation and intensity of staining. Murexide, for light microscopy, and 8-hydroxyquinoline, for fluorescence microscopy proved to be the best overall reagents. They failed to demonstrate calcium oxalate, which was well shown by naphthalhydroxamic acid.     

Comparative analysis of coiled-coil prediction methods

In this study we compare commonly used coiled-coil prediction methods against a database derived from proteins of known structure. We find that the two older programs COILS and PairCoil/MultiCoil are significantly outperformed by two recent developments: Marcoil, a program built on hidden Markov models, and PCOILS, a new COILS version that uses profiles as inputs; and to a lesser extent by a PairCoil update, PairCoil2. Overall Marcoil provides a slightly better performance over the reference database than PCOILS and is considerably faster, but it is sensitive to highly charged false positives, whereas the weighting option of PCOILS allows the identification of such sequences.     

Periphyton on nymphaeids: An evaluation of methods and separation techniques

The use of certain methods and techniques of periphyton research has been evaluated in connection with the study of periphyton on nymphaeid aquatic plants. Separation techniques explored are based on a combination of mechanical and chemical forces, on enzymatic action and on the chelating activity of EDTA. Mechanical separation by the application of superficial film is treated apart, because it is the only technique conserving the original pattern of periphyton. The means used to examine periphyton in situ consist of bleaching, epifluorescence and scanning electron microscopy.In the end, it is concluded that not one of the techniques is fully satisfactory. However, a combination of techniques may provide sufficient data to obtain an overall picture of species composition, microdistribution and architecture of a periphyton community.Contribution no. 30 of the nymphaeid project.Contribution no. 30 of the nymphaeid project.     

An evaluation of possible alternative methods to the Howard Mould Count

The Direct Epifluorescent Filter Technique (DEFT) could be used as an alternative to the Howard Mould Count (HMC) to enumerate mould, bacteria and yeast in tomato concentrate. The DEFT counts of micro-organisms before and after thermal treatment were similar. ATP and chitin assays were also examined as possible alternatives.