An estimate of the nearest neighbor base-pair content of 5S RNA using CD and absorption spectroscopy.

We analyzed the CD and uv absorption spectra of 5S RNA from Escherichia coli using the method developed in the preceding paper. The analysis of spectra of 5S RNA at 20 degrees C in 0.1M NaClO4, 2.5 mM Na+ (phosphate), pH 7.0, and 0.5 mM MgSO4 gave 7 +/- 3.6 A.U base pairs, 25 +/- 3.6 G.C base pairs, and 7.5 +/- 3.6 G.U base pairs. Estimates of nearest neighbor base pairs were more consistent with the Pieler-Erdmann and the Gewirth-Moore secondary structure models than with the Fox-Woese or the Burns-Luoma-Marshall models. We also examined the structure of 5S RNA as a function of temperature. The melting profile exhibited two transitions--one at about 35 degrees C and one above 50 degrees C. Our spectral data showed that helices I and II were stable during the first transition, and agreed with other data that helix III was the most likely helix to have melted. The results from this in-depth study of 5S RNA indicate that our method of analysis should be useful for studying the secondary structures of other small, unmodified RNAs.     

Identifying G-protein coupled receptors using weighted Levenshtein distance and the nearest neighbor method

G-protein coupled receptors （GPCRs） are a class of seven-helix transmembrane proteins that have been used in bioinformatics as the targets to facilitate drug discovery for human diseases. Although thousands of GPCR sequences have been collected, the ligand specificity of many GPCRs is still unknown and only one crystal structure of the rhodopsin-like family has been solved. Therefore, identifying GPCR types only from sequence data has become an important research issue. In this study, a novel technique for identifying GPCR types based on the weighted Levenshtein distance between two receptor sequences and the nearest neighbor method （NNM） is introduced, which can deal with receptor sequences with different lengths directly. In our experiments for classifying four classes （acetylcholine, adrenoceptor, dopamine, and serotonin） of the rhodopsin-like family of GPCRs, the error rates from the leave-one-out procedure and the leave-half-out procedure were 0.62% and 1.24%, respectively. These results are prior to those of the covariant discriminant algorithm, the support vector machine method, and the NNM with Euclidean distance.     

A sensitive method for estimating the carbohydrate content of glycoproteins

A spectrophotometric method is described for estimating the carbohydrate content of acid-hydrolyzed glycoproteins. The method is based on the alkaline ferricyanide reaction with reducing sugars and is accurate in the 1–25 nmole range. Using a simple two-step ion-exchange column procedure both the total sugar content and the proportion of neutral and amino sugars can be determined.     

A nearest neighbor approach for automated transporter prediction and categorization from protein sequences

MOTIVATION: Membrane transport proteins play a crucial role in the import and export of ions, small molecules or macromolecules across biological membranes. Currently, there are a limited number of published computational tools which enable the systematic discovery and categorization of transporters prior to costly experimental validation. To approach this problem, we utilized a nearest neighbor method which seamlessly integrates homologous search and topological analysis into a machine-learning framework. RESULTS: Our approach satisfactorily distinguished 484 transporter families in the Transporter Classification Database, a curated and representative database for transporters. A five-fold cross-validation on the database achieved a positive classification rate of 72.3% on average. Furthermore, this method successfully detected transporters in seven model and four non-model organisms, ranging from archaean to mammalian species. A preliminary literature-based validation has cross-validated 65.8% of our predictions on the 11 organisms, including 55.9% of our predictions overlapping with 83.6% of the predicted transporters in TransportDB.     

Properties of the nearest neighbor interchange metric for trees of small size

The crossover or nearest neighbor interchange metric has been proposed for use in numerical taxonomy to obtain a quantitative measure of distance between classifications that are modeled as unrooted binary trees with labeled leaves. This metric seems difficult to compute and its properties are poorly understood. A variant called the closest partition distance measure has also been proposed, but no efficient algorithm for its computation has yet appeared and its relationship to the nearest neighbor interchange metric is incompletely understood. I investigate four conjectures concerning the nearest neighbor interchange and closest partition distance measures and establish their validity for trees with as many as seven labeled vertices. For trees in this size range the two distance measures are identical. If a certain decomposition property holds for the nearest neighbor interchange metric, then the two distance measures are also identical at small distances for trees of any size.     

A set of nearest neighbor parameters for predicting the enthalpy change of RNA secondary structure formation

A complete set of nearest neighbor parameters to predict the enthalpy change of RNA secondary structure formation was derived. These parameters can be used with available free energy nearest neighbor parameters to extend the secondary structure prediction of RNA sequences to temperatures other than 37°C. The parameters were tested by predicting the secondary structures of sequences with known secondary structure that are from organisms with known optimal growth temperatures. Compared with the previous set of enthalpy nearest neighbor parameters, the sensitivity of base pair prediction improved from 65.2 to 68.9% at optimal growth temperatures ranging from 10 to 60°C. Base pair probabilities were predicted with a partition function and the positive predictive value of structure prediction is 90.4% when considering the base pairs in the lowest free energy structure with pairing probability of 0.99 or above. Moreover, a strong correlation is found between the predicted melting temperatures of RNA sequences and the optimal growth temperatures of the host organism. This indicates that organisms that live at higher temperatures have evolved RNA sequences with higher melting temperatures.     

Stellacyanin. Studies of the metal-binding site using x-ray absorption spectroscopy.

Stellacyanin is a mucoprotein of molecular weight approximately 20,000 containing one copper atom in a blue or type I site. The metal ion can exist in both the Cu(II) and Cu(I) redox states. The metal binding site in plastocyanin, another blue copper protein, contains one cysteinyl, one methionyl, and two imidazoyl residues (Colman et al. 1978. Nature [Lond.]. 272:319-324.), but an exactly analogous site cannot exist in stellacyanin as it lacks methionine. The copper coordination in stellacyanin has been studied by x-ray edge absorption and extended x-ray absorption fine structure (EXAFS) analysis. A new, very conservative data analysis procedure has been introduced, which suggests that the there are two nitrogen atoms in the first coordination shell of the oxidized [Cu(II)] protein and one in the reduced [Cu(I)] protein; these N atoms have normal Cu--N distances: 1.95-2.05 A. In both redox states there are either one or two sulfur atoms coordinating the copper, the exact number being indeterminable from the present data. In the oxidized state the Cu--S distance is intermediate between the short bond found in plastocyanin and those found in near tetragonal copper model compounds. Above -140 degree C, radiation damage of the protein occurs. At room temperature the oxidized proteins is modified in the x-ray beam at a rate of 0.25%/s.     

Terminal contributions for duplex oligonucleotide thermodynamic properties in the context of nearest neighbor models

Additive physical properties of DNA polymer duplexes have been expanded in terms of eight irreducible parameters that ultimately lead to consistency relations among the corresponding 10 duplex dimer contributions. End parameters are often added to allow for oligomer analysis which would add four extra degrees of freedom to the aforementioned parameters. Analysis of sufficient experimental data on oligomer duplexes allows for the unambiguous recovery of irreducible parameters. Values for free energy, enthalpy, and entropy are thus obtained, in terms of either irreducible or dimer decomposition sets. Here, a better adjust for the entropic (and enthalpic) irreducible parameters are obtained as we consider the more precise melting temperature data for the sequences of a given dataset. However, still large error estimates, and no clear distinction between the orientations of the terminal base pairs could yet be found. Finally, statistical mechanics approaches are applied for to connect the nearest neighbor approach to the two states model. Ad hoc end effects can be thus correlated to nucleation phenomena, leading to a critique for its role in nearest neighbor modeling.     

Prediction of oligonucleotide frequencies based upon dinucleotide frequencies obtained from the nearest neighbor analysis.

A statistical method of predicting hexanucleotide frequencies is presented. The method requires dinucleotide frequencies which can be readily obtained by nearest neighbor analysis. The frequencies of 64 hexanucleotides of E. coli were estimated and compared well with those predicted by a third order Markov chain.     

Minimalist representations and the importance of nearest neighbor effects in protein folding simulations

In order to investigate the level of representation required to simulate folding and predict structure, we test the ability of a variety of reduced representations to identify native states in decoy libraries and to recover the native structure given the advanced knowledge of the very broad native Ramachandran basin assignments. Simplifications include the removal of the entire side-chain or the retention of only the Cbeta atoms. Scoring functions are derived from an all-atom statistical potential that distinguishes between atoms and different residue types. Structures are obtained by minimizing the scoring function with a computationally rapid simulated annealing algorithm. Results are compared for simulations in which backbone conformations are sampled from a Protein Data Bank-based backbone rotamer library generated by either ignoring or including a dependence on the identity and conformation of the neighboring residues. Only when the Cbeta atoms and nearest neighbor effects are included do the lowest energy structures generally fall within 4 A of the native backbone root-mean square deviation (RMSD), despite the initial configuration being highly expanded with an average RMSD > or = 10 A. The side-chains are reinserted into the Cbeta models with minimal steric clash. Therefore, the detailed, all-atom information lost in descending to a Cbeta-level representation is recaptured to a large measure using backbone dihedral angle sampling that includes nearest neighbor effects and an appropriate scoring function.     

Calculation of nucleation free energy for duplex oligomers in the context of nearest neighbor models

Additive physical properties of DNA double strand polymers have been expanded in terms of 8 irreducible parameters. This provided consistency relations among the corresponding 10 duplex dimer contributions. To allow for oligomer analysis, end parameters were often added, and this would add extra degrees of freedom to the fore mentioned parameters. Statistical mechanics approaches were then connected to the nearest neighbor (NN) approach in the framework of the two‐states model. Ad hoc end effects were thus (wrongly) correlated to nucleation phenomena and this lead to a critique for its role in NN modeling. With this motivation, a new NN model is proposed that accommodates the nucleation free energies. The model relates the nucleation free energy to the mean composition of the chain and permits to obtain a good estimate for the free energy associated only to the Watson–Crick base pairings. © 2013 Wiley Periodicals, Inc. Biopolymers 99: 538–547, 2013.     

A method for estimating rates of nucleotide substitution using DNA sequence data

An estimate of the average number of evolutionarily acceptable substitutions per nucleotide since the most recent common ancestor of a pair of homologous sequences is found which uses nucleotide sequence data. The estimate is derived assuming a Poisson-like model for the evolutionary process. A method is also suggested for analyzing nucleotide sequence data in M homologous sequences (M 3). A simulation study is reported showing that the estimates are satisfactory providing there is sufficient homology between the sequences. To demonstrate the methods a numerical example using some β-globin data is presented.     

A method for estimating torque-vector directions of shoulder muscles using surface EMGs

In this study, a new method is proposed to estimate the torque-vector directions of each shoulder muscle. The method is based on a multiple regression model that reconstructs shoulder torque, which is calculated from the hand force and posture, from the surface EMG of many muscles recorded simultaneously. The torque-vector directions of eleven shoulder muscles of four subjects were obtained at up to 30 different arm postures with this method. The mean confidence interval (p < 0.05) of the estimated torque-vector direction of each subject was 7.7-10.6 degrees. The correlation coefficient between the measured shoulder torque and reconstructed shoulder torque was between 0.76-0.84. The results for majority of the muscles were in accordance with previous studies, and reasonable from the viewpoint of anatomy. The torque-vector directions of a muscle, which are estimated with this method, have more of a functional meaning than a pure anatomical or mechanical one. These indicate the direction of the shoulder torque accompanying the muscle activation for a normal shoulder action that involves the cooperative contraction of many muscles.     

A method for estimating torque-vector directions of shoulder muscles using surface EMGs

In this study, a new method is proposed to estimate the torque-vector directions of each shoulder muscle. The method is based on a multiple regression model that reconstructs shoulder torque, which is calculated from the hand force and posture, from the surface EMG of many muscles recorded simultaneously. The torque-vector directions of eleven shoulder muscles of four subjects were obtained at up to 30 different arm postures with this method. The mean confidence interval ( p< 0.05) of the estimated torque-vector direction of each subject was 7.7-10.6 degrees. The correlation coefficient between the measured shoulder torque and reconstructed shoulder torque was between 0.76-0.84. The results for majority of the muscles were in accordance with previous studies, and reasonable from the viewpoint of anatomy. The torque-vector directions of a muscle, which are estimated with this method, have more of a functional meaning than a pure anatomical or mechanical one. These indicate the direction of the shoulder torque accompanying the muscle activation for a normal shoulder action that involves the cooperative contraction of many muscles.     

A convenient sequencing method for 5'' protein-linked RNAs.

A convenient nucleotide sequencing method for 5' end protein-linked RNAs was developed. Genome of LSc, 2ab poliovirus, which has a protein (VPg) covalently linked to the 5' terminus, was labelled with 125I Bolton and Hunter reagent after proteinase K treatment. No sign of labelling of nucleotide moiety in the genome with the reagent was detected. A labelled oligo peptide-linked ribonuclease T1 fragment was obtained from the 5' end of the genome. Analysis of the complex by two dimensional gel electrophoresis after partial alkali digestion or by the nucleotide sequencing method of Donis-Keller et al. (1) revealed that LSc, 2ab strain genome had an identical 5' end structure to that of Mahoney strain genome, that is, VPg-pUpUpApApApApCpApGp. Our results have shown that this labelling method is useful for analysis of 5' end sequence of RNAs linked to protein at the 5' termini.     

Conformational studies of alanine-rich peptide using CD and FTIR spectroscopy.

The circular dichroism (CD) and Fourier transform infrared (FTIR) methods were applied to the conformational studies of alanine-rich peptide Ac-K-[A]11-KGGY-NH2 (where K is lysine, A is alanine, G is glycine and Y is tyrozyne) in water, methanol (MeOH) and trifluoroethanol (TFE). The analysis of CD-spectra of the peptide in water at different concentrations revealed that the secondary structure content depends on the peptide concentration and pH of the solution. The increase of the peptide concentration causes a decrease of alpha-helix content and, simultaneously, an increase of beta-sheet structure, while the unordered structure is the predominant one. Additional elements are discovered in MeOH and TFE but alpha-helix and beta-turns predominate. Moreover, in these solutions the percentage content of the secondary structure does not depend on the temperature. FTIR measurements, carried out at higher peptide concentration (about one order of magnitude) than these CD measurements mentioned above, revealed that in water solution the solid state beta-sheet, and aggregated structures, dominate. However, in TFE the most abundant are alpha-helix and beta-turns structures. The thioflavine T assay showed the tendency of the studied peptide for aggregate.