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PubMed2001

SOMCD: method for evaluating protein secondary structure from UV circular dichroism spectra.

This article presents SOMCD, an improved method for the evaluation of protein secondary structure from circular dichroism spectra, based on Kohonen's self-organizing maps (SOM). Protein circular dichroism (CD) spectra are used to train a SOM, which arranges the spectra on a two-dimensional map. Location in the map reflects the secondary structure composition of a protein. With SOMCD, the prediction of beta-turn has been included. The number of spectra in the training set has been increased, and it now includes 39 protein spectra and 6 reference spectra. Finally, SOM parameters have been chosen to minimize distortion and make the network produce clusters with known properties. Estimation results show improvements compared with the previous version, K2D, which, in addition, estimated only three secondary structure components; the accuracy of the method is more uniform over the different secondary structures.

Algorithms↗
PubMed1993

Global characterization of protein secondary structures. Analysis of computer-modeled protein unfolding.

Analyses of structural and molecular shape changes undergone by a protein during an unfolding process are presented. The procedure, based on a spherical shape map method, provides a topological description of a three-dimensional macromolecular structure. Local properties of the backbone are used to derive a global characterization of its fold. A spherical shape map of backbone crossings is associated with a given macromolecular conformation. The map is built by classifying each point on the sphere according to the crossing pattern obtained when the backbone is observed along a direction defined by the center of the sphere and the chosen point. The surface of the sphere can be divided in equivalence classes. All the points within a given class correspond to directions from which the backbone has the same overcrossing pattern. Automatic computation and display of these equivalence classes is discussed, as is the implementation of the technique on a computer graphics workstation. The graphical manipulation simplifies the analysis of these maps when following a change in the conformation of the backbone. The procedure is illustrated with the results of a molecular dynamics computer simulation of the unfolding of the bacteriophage T4 glutaredoxin protein (in the form of its polyglycine model). The method gives a novel description of the differential structural stability for the characteristic secondary structural elements (alpha-helices and beta-sheets) present in the protein. Recognition of the persistence of structural elements over the simulation time is performed in an unbiased manner.

Algorithms↗
PubMed2005

siRNA target site secondary structure predictions using local stable substructures.

The crystal structure based model of the catalytic center of Ago2 revealed that the siRNA and the mRNA must be able to form an A-helix for correct positing of the scissile phosphate bond for cleavage in RNAi. This suggests that base pairing of the target mRNA with itself, i.e. secondary structure, must be removed before cleavage. Early on in the siRNA design, GC-rich target sites were avoided because of their potential to be involved in strong secondary structure. It is still unclear how important a factor mRNA secondary structure is in RNAi. However, it has been established that a difference in the thermostability of the ends of an siRNA duplex dictate which strand is loaded into the RNA-induced silencing complex. Here, we use a novel secondary structure prediction method and duplex-end differential calculations to investigate the importance of a secondary structure in the siRNA design. We found that the differential duplex-end stabilities alone account for functional prediction of 60% of the 80 siRNA sites examined, and that secondary structure predictions improve the prediction of site efficacy. A total of 80% of the non-functional sites can be eliminated using secondary structure predictions and duplex-end differential.

Algorithms↗
PubMed1994

Importance of environment in determining secondary structure in proteins.

We report here the effect of bulk solvent environment on the secondary structure of several peptides. In previous work, equivocal peptide sequences that are predicted to be alpha-helical from amino acid preference but are found to be beta-strand in their proteins were shown to be alpha-helical in alcohol solvents and beta-strand in nonmicellar sodium dodecyl sulfate (SDS) by circular dichroism (CD) spectroscopy [Zhong, L., & Johnson, W. C., Jr. (1992) Proc. Natl. Acad. Sci. U.S.A. 89, 4462-4465]. Here we show that equivocal sequences that are predicted to be beta-strand but are found to be alpha-helical follow the same pattern; they are alpha-helical in alcohol solvents and beta-strand in nonmicellar SDS. Furthermore, we investigated a control sequence with only a strong alpha-helical propensity and a control sequence with only a strong beta-strand propensity. Both of these well-behaved sequences followed the same pattern as the equivocal sequences. The exceptionally stable Y(EAAAK)3A is an alpha-helix in all solvents, but analyses of the CD spectra indicate the loss of helix with an increase in beta-strand and other structures on changing solvent from trifluoroethanol (TFE) to SDS, similar to the other peptides. We find that solvent is a very important factor in determining the secondary structure of an amino acid sequence in vitro and can override the propensity for a secondary structure due to sequence.(ABSTRACT TRUNCATED AT 250 WORDS)

Amino Acid Sequence↗
PubMed1993

Secondary structure and temperature behavior of the acetylcholine receptor by Fourier transform infrared spectroscopy.

Fourier transform infrared spectroscopy (FT-IR) was used to test the secondary structure of purified acetylcholine receptor membranes from Torpedo californica. The secondary structure was estimated using the spectral features observed in the structure sensitive region of amide I and amide I' (between 1600 and 1700 cm-1), taking advantage of Fourier self-deconvolution and second-derivative techniques along with least-squares band fitting procedures. At least six different amide I' band components could be resolved in D2O and were tentatively assigned to beta-structures (1680 and 1636 cm-1), alpha-helices (1657 cm-1), aperiodic structures and/or distorted helices (1646-1648 cm-1), and turns (1690 and 1668 cm-1), respectively. The beta-band around 1637 cm-1, in particular, turned out to be complex since it reproducibly exhibited weak features near 1630 and 1627 cm-1, thereby suggesting the presence of different chain interacting beta-structures. The band near 1657 cm-1 was assigned to alpha-helices which transverse the membrane bilayers, while 1646-1648-cm-1 component was tentatively attributed to aperiodic structures and alpha-helices localized within the "globular head" of the receptor protein protruding from the membrane surface into the surrounding water. Least-squares band fitting procedures were applied in order to estimate relative amounts of secondary structures. The results suggest 36-43%, 32-33%, 14-24%, and 18-19% for beta-, alpha-helical, turn, and "rest" structures, respectively. Additionally, the temperature- and time-dependent variations of the secondary structure was tested by evaluating the changes of amide I and amide II band components of receptor membranes dispersed in H2O and D2O.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1990

Molecular dynamics study of secondary structure motions in proteins: application to myohemerythrin.

The concept of secondary structure motions is examined in a molecular dynamics simulation of the protein myohemerythrin. We extracted from the simulation a corresponding trajectory of helices and demonstrated that the fluctuations of the protein are dominated by a rigid shift of these secondary structure elements. The relative motions of the helices are irregular, with no clear periodicity. They are bounded by approximately 2 A for the center of mass motions and by 20 degrees for the relative orientations. The potential of mean force for the interactions of the helices was calculated, and the correlations between the different extended motions were investigated. It is shown that the one-dimensional mean force potentials are close to quadratic for most of the helices coordinates. The anharmonicity is reflected by changes in the direction of the normal modes as a function of the energy and by the existence of multiple free energy minima for the helices packing. The multiple conformations are associated with a single type of secondary structure coordinate: the angle that describes the relative orientation of the helices in a plane perpendicular to the line connecting their center of mass.

Binding Sites↗
PubMed2004

The robustness of naturally and artificially selected nucleic acid secondary structures.

Thermodynamic stability and mutational robustness of secondary structure are critical to the function and evolutionary longevity of RNA molecules. We hypothesize that natural and artificial selection for functional molecules favors the formation of structures that are stable to both thermal and mutational perturbation. There is little direct evidence, however, that functional RNA molecules have been selected for their stability. Here we use thermodynamic secondary structure prediction algorithms to compare the thermal and mutational robustness of over 1000 naturally and artificially evolved molecules. Although we find evidence for the evolution of both types of stability in both sets of molecules, the naturally evolved functional RNA molecules were significantly more stable than those selected in vitro, and artificially evolved catalysts (ribozymes) were more stable than artificially evolved binding species (aptamers). The thermostability of RNA molecules bred in the laboratory is probably not constrained by a lack of suitable variation in the sequence pool but, rather, by intrinsic biases in the selection process.

Base Composition↗
PubMed1997

Protein topology recognition from secondary structure sequences: application of the hidden Markov models to the alpha class proteins.

The three-dimensional fold of a protein is described by the organization of its secondary structure elements in 3D space, i.e. its "topology". We find that the protein topology can be recognized from the ID sequence of secondary structure states of the residues alone. Automated recognition is facilitated by use of hidden Markov models (HMMs) to represent topology families of proteins. Such models can be trained on the experimentally observed secondary structure sequences of family members using well established algorithms. Here, we model various topology groups in the alpha class of proteins and identify, from a large database, those proteins having the topology described by each model. The correct topology family for protein secondary structure sequences could be recognized 12 out of 14 times. When the observed secondary structure sequences are replaced with predicted sequences recognition is still achievable 8 out of 14 times. The success rate for observed sequences indicates that our approach will become increasingly useful as the accuracy of secondary prediction algorithms is improved. Our study indicates that the HMMs are useful for protein topology recognition even when no detectable primary amino acid sequence similarity is present. To illustrate the potential utility of our method, protein topology recognition is attempted on leptin, the obese gene product, and the human interleukin-6 sequence, for which fold predictions have been previously published.

Algorithms↗
PubMed2000

Calculating nucleic acid secondary structure.

New results for calculating nucleic acid secondary structure by free energy minimization and phylogenetic comparisons have recently been reported. A complete set of DNA energy parameters is now available and the RNA parameters have been improved. Although databases of RNA secondary structures are still derived and expanded using computer-assisted, ad hoc comparative analysis, a number of new computer algorithms combine covariation analysis with energy methods.

Algorithms↗
PubMed2006

4SALE--a tool for synchronous RNA sequence and secondary structure alignment and editing.

BACKGROUND: In sequence analysis the multiple alignment builds the fundament of all proceeding analyses. Errors in an alignment could strongly influence all succeeding analyses and therefore could lead to wrong predictions. Hand-crafted and hand-improved alignments are necessary and meanwhile good common practice. For RNA sequences often the primary sequence as well as a secondary structure consensus is well known, e.g., the cloverleaf structure of the t-RNA. Recently, some alignment editors are proposed that are able to include and model both kinds of information. However, with the advent of a large amount of reliable RNA sequences together with their solved secondary structures (available from e.g. the ITS2 Database), we are faced with the problem to handle sequences and their associated secondary structures synchronously. RESULTS: 4SALE fills this gap. The application allows a fast sequence and synchronous secondary structure alignment for large data sets and for the first time synchronous manual editing of aligned sequences and their secondary structures. This study describes an algorithm for the synchronous alignment of sequences and their associated secondary structures as well as the main features of 4SALE used for further analyses and editing. 4SALE builds an optimal and unique starting point for every RNA sequence and structure analysis. CONCLUSION: 4SALE, which provides an user-friendly and intuitive interface, is a comprehensive toolbox for RNA analysis based on sequence and secondary structure information. The program connects sequence and structure databases like the ITS2 Database to phylogeny programs as for example the CBCAnalyzer. 4SALE is written in JAVA and therefore platform independent. The software is freely available and distributed from the website at http://4sale.bioapps.biozentrum.uni-wuerzburg.de.

Algorithms↗
PubMed2004

A simple and fast secondary structure prediction method using hidden neural networks.

MOTIVATION: In this paper, we present a secondary structure prediction method YASPIN that unlike the current state-of-the-art methods utilizes a single neural network for predicting the secondary structure elements in a 7-state local structure scheme and then optimizes the output using a hidden Markov model, which results in providing more information for the prediction. RESULTS: YASPIN was compared with the current top-performing secondary structure prediction methods, such as PHDpsi, PROFsec, SSPro2, JNET and PSIPRED. The overall prediction accuracy on the independent EVA5 sequence set is comparable with that of the top performers, according to the Q3, SOV and Matthew's correlations accuracy measures. YASPIN shows the highest accuracy in terms of Q3 and SOV scores for strand prediction. AVAILABILITY: YASPIN is available on-line at the Centre for Integrative Bioinformatics website (http://ibivu.cs.vu.nl/programs/yaspinwww/) at the Vrije University in Amsterdam and will soon be mirrored on the Mathematical Biology website (http://www.mathbio.nimr.mrc.ac.uk) at the NIMR in London. CONTACT: kxlin@nimr.mrc.ac.uk

Algorithms↗
PubMed1989

[Effect of aflatoxin B1 on DNA enzymatic methylation and secondary structures of the rat liver].

Methylation and secondary structure of DNA in rat liver versus time of aflatoxin B1 (AfB1) treatment were studied. A 50% drop in 5-methylcytosine level in liver DNA as compared with control was observed long before tumor development. Also, certain changes in DNA secondary structure were seen. The DNA changes were more pronounced in the F1 progeny of rats inoculated with AfB1 at the terminal stage of gestation.

Aflatoxin B1↗
PubMed1997

Improved method for prediction of protein backbone U-turn positions and major secondary structural elements between U-turns.

A new and more accurate method has been developed for predicting the backbone U-turn positions (where the chain reverses global direction) and the dominant secondary structure elements between U-turns in globular proteins. The current approach uses sequence-specific secondary structure propensities and multiple sequence information. The latter plays an important role in the enhanced success of this approach. Application to two sets (total 108) of small to medium-sized, single-domain proteins indicates that approximately 94% of the U-turn locations are correctly predicted within three residues, as are 88% of dominant secondary structure elements. These results are significantly better than our previous method (Kolinski et al., Proteins 27:290-308, 1997). The current study strongly suggests that the U-turn locations are primarily determined by local interactions. Furthermore, both global length constraints and local interactions contribute significantly to the determination of the secondary structure types between U-turns. Accurate U-turn predictions are crucial for accurate secondary structure predictions in the current method. Protein structure modeling, tertiary structure predictions, and possibly, fold recognition should benefit from the predicted structural data provided by this new method.

Amino Acid Sequence↗
PubMed1998

A protein conformational search space defined by secondary structure contacts.

A conformational search space describing the relative position and orientation of protein secondary structure elements in three-dimensions was defined. These spatial relations were encoded by homogeneous transformation matrices between pairs of residues "in contact" in two different secondary structure elements. A database of all occurrences of spatial relations for five hydrophobic residues was built. The use of one residue contact per pair of secondary structure elements, which were approximated by standard (phi, psi) assignments, was sufficient to reproduce accurately the core structure of proteins with known three-dimensional structures.

Amino Acid Sequence↗
PubMed1989

RNA secondary structures: comparison and determination of frequently recurring substructures by consensus.

A method for assessing the preserved stem-loops of RNA secondary structures is presented. Frequently recurring helical stems in a set of secondary structures resulting from the simulated folding process of a given RNA are assessed and consensus structural motifs can then be selected to construct a secondary structure of the RNA. Alternatively, it can be applied to a series of 'optimal' and 'suboptimal' secondary structures computed using the dynamic program developed by Williams and Tinoco. To demonstrate the power and the usefulness of the program we give examples of this procedure.

Algorithms↗
PubMedDate not supplied

[An analysis of the secondary structure of spider spidroins I and II belonging to different species].

We have analyzed the secondary structure of spidroin proteins of I and II types, related to spiders of different species. We used standard methods of secondary structure prediction NNPREDICT and JPRED and also analyzed the occurrences of oligopeptides with a preferred secondary structure with the help of the OLIGON program. We have demonstrated that local segments of the polypeptide chain can adopt alpha- and beta-conformations as well as the left-handed helix of polyproline II type. Periodical patterns found in the amino acid distribution indicate that there is a possibility of development of a macroscopic order accompanied by local conformational transitions.

Amino Acid Sequence↗
PubMed1992

The secondary structure of the regulatory region of the transferrin receptor mRNA deduced by enzymatic cleavage.

The secondary structure of the portion of the transferrin receptor mRNA responsible for the regulation of the transcript's half-life has been deduced by ribonuclease H cleavage directed by antisense oligodeoxyribonucleotides as well as with other ribonucleases sensitive to RNA secondary structure. The data indicate that both a synthetic 252-nucleotide RNA and the comparable portion of a 2.7-kb cellular mRNA contain three stem-loops referred to as iron-responsive elements (IREs). This secondary structure appears to be relatively static, with little interconversion with another possible structure having a similar calculated free energy but involving longer-range base pairing. Deletion of a selected cytosine residue from each of the IRE loops has been shown to yield an unregulated, unstable mRNA. This altered RNA has a secondary structure similar, if not identical, to that of the RNA that is competent in regulation.

Animals↗
PubMed1982

Raman spectroscopic determination of the secondary structure of crystalline nerve growth factor.

The secondary structure of crystalline nerve growth factor (NGF) has been measured with 90% confidence to contain between 0 and 11% helix and between 53 and 67% antiparallel beta-strand using the intensity distribution of the amide I region of the Raman spectrum. A comparison of spectra collected from crystals and solutions confirms that the secondary structure of NGF is the same in these two states. The helical content of NGF as determined by Raman differs substantially from predictions based on sequence. The amide I band of NGF is substantially different from that of insulin, indicating that no structural hemology is likely to exist between these two proteins.

Amino Acid Sequence↗