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[Contribution of individual structural components to stabilization of the secondary structure of double-helical polynucleotides].

Contributions of individual structural components of the double-helical polynucleotide to the stabilization of its secondary structure have been studied. The energy of intramolecular interactions was calculated by the method of atom-atom potentials. Sections of the energy function were constructed according to the parameters determining mutual location of base pairs with the optimal conformation of ribose-phosphate backbone in the points close to A- and B-forms of DNA. A complicated nature of the contribution of different structural components of the polynucleotide to its stabilization was revealed by means of different parameters. Relationships between the change of conformational parameters corresponding to optimal values of energy for A- and B-families of nucleic acids were found.

DNA↗

Generation of a substructure library for the description and classification of protein secondary structure. I. Overview of the methods and results.

Protein secondary structure has been typically classified into four major classes--alpha-helices, extended strands, reverse turns, and loops. Available methods for secondary structure analysis utilize predefined structure templates to search for structural matches among proteins. By this approach a significant portion of a proteins backbone conformation is assigned to one of a limited number of conformations or, if unassigned, to random coil. To expand our ability to describe protein secondary structure, we have developed an algorithm that operates independently of a predefined structure template. The procedure uses two geometric descriptors, the linear distance and the backbone dihedral angle, to represent the conformation form the alpha-carbon coordinates. The algorithm functions by searching for conformationally equivalent, contiguous fragments without regard to secondary structural classification and is thus independent of the complexity of the backbone fold. The result is a library of conformationally equivalent structure fragments that exhibit some novel characteristics. The library contains features that reproduce the major secondary structure classes as well as defining conformations previously described only as random or undefined conformations. Additionally, the library defines several subclassifications of beta-strands. We present here a validation of this method and a presentation and discussion of the most significant results. In a second study, we report the results of application of this method to spectra-structure correlations in Fourier transform infrared spectroscopy.

Algorithms↗

Secondary structure in the target as a confounding factor in synthetic oligomer microarray design.

BACKGROUND: Secondary structure in the target is a property not usually considered in software applications for design of optimal custom oligonucleotide probes. It is frequently assumed that eliminating self-complementarity, or screening for secondary structure in the probe, is sufficient to avoid interference with hybridization by stable secondary structures in the probe binding site. Prediction and thermodynamic analysis of secondary structure formation in a genome-wide set of transcripts from Brucella suis 1330 demonstrates that the properties of the target molecule have the potential to strongly influence the rate and extent of hybridization between transcript and tethered oligonucleotide probe in a microarray experiment. RESULTS: Despite the relatively high hybridization temperatures and 1M monovalent salt imposed in the modeling process to approximate hybridization conditions used in the laboratory, we find that parts of the target molecules are likely to be inaccessible to intermolecular hybridization due to the formation of stable intramolecular secondary structure. For example, at 65 degrees C, 28 +/- 7% of the average cDNA target sequence is predicted to be inaccessible to hybridization. We also analyzed the specific binding sites of a set of 70mer probes previously designed for Brucella using a freely available oligo design software package. 21 +/- 13% of the nucleotides in each probe binding site are within a double-stranded structure in over half of the folds predicted for the cDNA target at 65 degrees C. The intramolecular structures formed are more stable and extensive when an RNA target is modeled rather than cDNA. When random shearing of the target is modeled for fragments of 200, 100 and 50 nt, an overall destabilization of secondary structure is predicted, but shearing does not eliminate secondary structure. CONCLUSION: Secondary structure in the target is pervasive, and a significant fraction of the target is found in double stranded conformations even at high temperature. Stable structure in the target has the potential to interfere with hybridization and should be a factor in interpretation of microarray results, as well as an explicit criterion in array design. Inclusion of this property in an oligonucleotide design procedure would change the definition of an optimal oligonucleotide significantly.

Bacterial Proteins↗

A periodic pattern of mRNA secondary structure created by the genetic code.

Single-stranded mRNA molecules form secondary structures through complementary self-interactions. Several hypotheses have been proposed on the relationship between the nucleotide sequence, encoded amino acid sequence and mRNA secondary structure. We performed the first transcriptome-wide in silico analysis of the human and mouse mRNA foldings and found a pronounced periodic pattern of nucleotide involvement in mRNA secondary structure. We show that this pattern is created by the structure of the genetic code, and the dinucleotide relative abundances are important for the maintenance of mRNA secondary structure. Although synonymous codon usage contributes to this pattern, it is intrinsic to the structure of the genetic code and manifests itself even in the absence of synonymous codon usage bias at the 4-fold degenerate sites. While all codon sites are important for the maintenance of mRNA secondary structure, degeneracy of the code allows regulation of stability and periodicity of mRNA secondary structure. We demonstrate that the third degenerate codon sites contribute most strongly to mRNA stability. These results convincingly support the hypothesis that redundancies in the genetic code allow transcripts to satisfy requirements for both protein structure and RNA structure. Our data show that selection may be operating on synonymous codons to maintain a more stable and ordered mRNA secondary structure, which is likely to be important for transcript stability and translation. We also demonstrate that functional domains of the mRNA [5'-untranslated region (5'-UTR), CDS and 3'-UTR] preferentially fold onto themselves, while the start codon and stop codon regions are characterized by relaxed secondary structures, which may facilitate initiation and termination of translation.

3' Untranslated Regions↗

Combining protein evolution and secondary structure.

An evolutionary model that combines protein secondary structure and amino acid replacement is introduced. It allows likelihood analysis of aligned protein sequences and does not require the underlying secondary (or tertiary) structures of these sequences to be known. One component of the model describes the organization of secondary structure along a protein sequence and another specifies the evolutionary process for each category of secondary structure. A database of proteins with known secondary structures is used to estimate model parameters representing these two components. Phylogeny, the third component of the model, can be estimated from the data set of interest. As an example, we employ our model to analyze a set of sucrose synthase sequences. For the evolution of sucrose synthase, a parametric bootstrap approach indicates that our model is statistically preferable to one that ignores secondary structure.

Amino Acid Sequence↗

[Characterization of 5S rRNA gene sequence and secondary structure in gymnosperms].

In higher plants the primary and the secondary structures of 5S ribosomal RNA gene are considered highly conservative. Little is known about the 5S rRNA gene structure, organization and variation in gyimnosperms. In this study we analyzed sequence and structure variation of 5S rRNA gene in Pinus through cloning and sequencing multiple copies of 5S rDNA repeats from individual trees of five pines, P. bungeana, P. tabulaeformis, P. yunnanensis, P. massoniana and P. densata. Pinus bungeana is from the subgenus Strobus while the other four are from the subgenus Pinus (diploxylon pines). Our results revealed variations in both primary and secondary structure among copies of 5S rDNA within individual genomes and between species. 5S rRNA gene in Pinus is 120 bp long in most of the 122 clones we sequenced except for one or two deletions in three clones. Among these clones 50 unique sequences were identified and they were shared by different pine species. Our sequences were compared to 13 sequences each representing a different gymnosperm species, and to six sequences representing both angiosperm monocots and dicots. Average sequence similarity was 97.1% among Pinus species and 94.3% between Pinus and other gymnosperms. Between gymnosperms and angiosperms the sequence similarity decreased to 88.1%. Similar to other molecular data, significant sequence divergence was found between the two Pinus subgenera. The 5S gene tree (neighbor-joining tree) grouped the four diploxylon pines together and separated them distinctly from P. bungeana. Comparison of sequence divergence within individuals and between species suggested that concerted evolution has been very weak especially after the divergence of the four diploxylon pines. The phylogenetic information contained in the 5S rRNA gene is limited due to its shorter length and the difficulties in identifying orthologous and paralogous copies of rDNA multigene family further complicate its phylogenetic application. Pinus densata is a diploid hybrid between P. tabulaeformis and P. yunnanensis. Its 5S rDNA composition is consistent with its hybrid origin. 5S rRNA of all gymnosperms published so far could be folded into a general secondary structure. Variation in this secondary structure was detected among species. About 55% of the 120 bp nucleotide positions was variable, in which 68% was on stem regions. Nevertheless, the positions at the end of the stems and those adjacent to loops are conserved. Their stability directly determines the size of the loops. Some mutations such as compensatory base-pair substitutions, and G-U pairing could be regarded as mechanisms for maintaining a stable secondary structure. The loops of the secondary structure are also relatively conserved. It seems that stable helices are necessary for the function of the gene. The conserved nucleotides in the loops are probably involved in the interaction with proteins and/or RNAs or with other nucleotide in the formation of the tertiary structure. However, unlike other reports, Loop E was found quite mutable among pines. These variations together with those on stems might be caused by the presence of pseudogenes among our clones. A preliminary evaluation indicates that only seven of 50 unique sequences are potentially functional genes.

Base Sequence↗

An algebraic representation of RNA secondary structures.

This paper develops mathematical methods for describing and analyzing RNA secondary structures. It was motivated by the need to develop rigorous yet efficient methods to treat transitions from one secondary structure to another, which we propose here may occur as motions of loops within RNAs having appropriate sequences. In this approach a molecular sequence is described as a vector of the appropriate length. The concept of symmetries between nucleic acid sequences is developed, and the 48 possible different types of symmetries are described. Each secondary structure possible for a particular nucleotide sequence determines a symmetric, signed permutation matrix. The collection of all possible secondary structures is comprised of all matrices of this type whose left multiplication with the sequence vector leaves that vector unchanged. A transition between two secondary structures is given by the product of the two corresponding structure matrices. This formalism provides an efficient method for describing nucleic acid sequences that allows questions relating to secondary structures and transitions to be addressed using the powerful methods of abstract algebra. In particular, it facilitates the determination of possible secondary structures, including those containing pseudoknots. Although this paper concentrates on RNA structure, this formalism also can be applied to DNA.

Base Sequence↗

Effects of DNA secondary structure on oligonucleotide probe binding efficiency.

Secondary structure motifs in nucleic acid probes generally impair intended hybridization reactions and so efforts to predict and avoid such structures are commonly employed in probe design schemes. Another key facet of probe design that has received much less attention, however, is that secondary structure at targeted probe binding site regions may also impair hybridization. Thus, evaluation of both probe and target site secondary structures together should improve hybridization prediction and design effectiveness. Several challenges confound this goal, including imperfect empirical rules and parameters underlying predictions and the fact that folding algorithms scale poorly with respect to sequence length. Here, we attempt to quantify the consequences of target site structure on predicted hybridization using sequences sampled from the human genome. We also provide a methodology for choosing a reasonable "window size" around target sites that is as small as possible without compromising folding algorithm prediction accuracy.

Algorithms↗

Prediction of super-secondary structure in proteins.

Various methods for the prediction of secondary structure from amino acid sequence can consistently achieve on average 60% accuracy when tested for several proteins. Improvement on this value has proved difficult, despite increasing the size of the data set and refining predictive techniques. The difficulty almost certainly derives from the influence of long-range interactions and the restrictions required to attain favourable protein topologies. We describe here a novel approach to structure prediction from amino acid sequence based on the recognition of super-secondary structure. The structure we initially consider is the beta alpha beta unit, which consists of two parallel beta-strands connected by an alpha-helix. From an analysis of all known beta alpha beta units, an ideal secondary structure sequence was derived. This was used as a template to locate probable beta alpha beta sequences in a standard secondary structure prediction. The method correctly predicted the location of 70% of the beta alpha beta units in 16 beta/alpha type proteins. This led to a 7.5% average improvement over the original secondary structure prediction.

Amino Acid Sequence↗

P-SEA: a new efficient assignment of secondary structure from C alpha trace of proteins.

MOTIVATION: The secondary structure is a key element of architectural organization in proteins. Accurate assignment of the secondary structure elements (SSE) (helix, strand, coil) is an essential step for the analysis and modelling of protein structure. Various methods have been proposed to assign secondary structure. Comparative studies of their results have shown some of their drawbacks, pointing out the difficulties in the task of SSE assignment. RESULTS: We have designed a new automatic method, named P-SEA, to assign efficiently secondary structure from the sole C alpha position. Some advantages of the new algorithm are discussed. AVAILABILITY: The program P-SEA is available by anonymous ftp: ftp.lmcp.jussieu.fr directory: pub/.

Algorithms↗

Primary structure, sequence-specific 1H-NMR assignments and secondary structure in solution of bromelain inhibitor VI from pineapple stem.

One of the bromelain inhibitors, isoinhibitor VI (BI-VI), was purified from pineapple stem powder and its complete amino acid sequence was determined by conventional protein sequencing. These results revealed that the protein consists of an 11-residue light chain and a 41-residue heavy chain, cross-linked to each other by disulfide bonds to form the native inhibitor of 52 residues (M(r) = 5888). The secondary structure of BI-VI was analyzed based on the sequence-specific 1H resonance assignment of its two-dimensional NMR spectra. BI-VI was shown to be composed of two domains (A and B) which are formed by antiparallel beta-sheets, but has no alpha-helix. These results were consistent with the CD spectra of BI-VI. Residues Lys27-Ile29 (heavy chain) form a triple-stranded antiparallel beta-sheet with residues Asp9-Tyr11 and Lys22-Glu24 (heavy chain) in the A domain and residues Cys5-Cys7 (heavy chain) form another triple-stranded beta-sheet with residues Cys6-Cys8 (light chain) and Asp32-Ile34 (heavy chain) in the B domain. The secondary structure as well as the primary structure of BI-VI was distinctly different from that of the other cysteine protease inhibitor, cystatin, and from that of basic pancreatic trypsin inhibitor.

Amino Acid Sequence↗

Protein secondary structure prediction using local alignments.

The accuracy of secondary structure prediction methods has been improved significantly by the use of aligned protein sequences. The PHD method and the NNSSP method reach 71 to 72% of sustained overall three-state accuracy when multiple sequence alignments are with neural networks and nearest-neighbor algorithms, respectively. We introduce a variant of the nearest-neighbor approach that can achieve similar accuracy using a single sequence as the query input. We compute the 50 best non-intersecting local alignments of the query sequence with each sequence from a set of proteins with known 3D structures. Each position of the query sequence is aligned with the database amino acids in alpha-helical, beta-strand or coil states. The prediction type of secondary structure is selected as the type of aligned position with the maximal total score. On the dataset of 124 non-membrane non-homologous proteins, used earlier as a benchmark for secondary structure predictions, our method reaches an overall three-state accuracy of 71.2%. The performance accuracy is verified by an additional test on 461 non-homologous proteins giving an accuracy of 71.0%. The main strength of the method is the high level of prediction accuracy for proteins without any known homolog. Using multiple sequence alignments as input the method has a prediction accuracy of 73.5%. Prediction of secondary structure by the SSPAL method is available via Baylor College of Medicine World Wide Web server.

Algorithms↗

Protein secondary structure: entropy, correlations and prediction.

MOTIVATION: Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone or by non-local tertiary interactions? To answer this question, we measure the entropy densities of primary and secondary structure sequences, and the local inter-sequence mutual information density. RESULTS: We find that the important inter-sequence interactions are short ranged, that correlations between neighboring amino acids are essentially uninformative and that only one-fourth of the total information needed to determine the secondary structure is available from local inter-sequence correlations. These observations support the view that the majority of most proteins fold via a cooperative process where secondary and tertiary structure form concurrently. Moreover, existing single-sequence secondary structure prediction algorithms are almost optimal, and we should not expect a dramatic improvement in prediction accuracy. AVAILABILITY: Both the data sets and analysis code are freely available from our Web site at http://compbio.berkeley.edu/

Algorithms↗

Test of circular dichroism (CD) methods for crambin and CD-assisted secondary structure prediction of its homologous toxins.

Methods that analyze protein circular dichroism (CD) spectra for fractions of secondary structure are evaluated for the plant protein crambin, which has a known high-resolution crystal structure. In addition, a two-step secondary structure prediction scheme is presented and used for the toxins homologous to crambin, shown by others to have secondary structures similar to crambin. The test of CD spectral analysis methods with the protein crambin employed two computer programs and several CD basis sets. Crambin's crystal structure, known to 0.945A resolution (Hendrickson, W.A., Teeter, M.M. Nature 290:107-113, 1981), allows accurate evaluation of results. Analysis with the protein spectra basis sets (Provencher, S.W., Glöckner, J. Biochemistry 20:33-37, 1981) as modified (Manavalan, P., Johnson, W.C., Jr. Anal. Biochem. 167:76-85, 1987) agreed most closely with crambin's crystal structure. This method was then applied to the CD spectra of the membrane-active toxins homologous to crambin (alpha 1- and beta-purothionin, phoratoxin A and B, and viscotoxin A3 and B). The new program SEQ (pronounced "seek") was developed to assign the secondary structure along the protein chain in a hierarchical fashion and applied to the plant toxins. The method constrained the secondary structure fractions to those from CD analysis and combined standard statistical methods with amphipathic helix location. Both CD-arrived secondary structure percentages and sequence assignment indicate that the viscotoxins are structurally most similar to crambin. Purothionin's secondary structure was predicted to be fundamentally similar to crambin's with a difference at the start of the first helix. This assignment agreed with Raman and NMR analyses of purothionin and lends validity to the method presented here. Differences from the NMR in the CD secondary structure fraction analysis for phoratoxin suggest interference in the CD from tryptophan residues.

Amino Acid Sequence↗

Water penetration into protein secondary structure revealed by hydrogen-deuterium exchange two-dimensional infrared spectroscopy.

Two-dimensional infrared spectroscopy in conjunction with hydrogen-deuterium exchange experiments provides detailed information about solvent penetration into protein structure. Correlating the secondary-structure sensitivity of the amide I vibration and the solvent-exposure sensitivity of amide II provides a direct probe of solvent-inaccessible residues of proteins embedded in the hydrophobic core or those involved in strong hydrogen bonds in secondary structures. Distinct spectral signatures of the cross-peak region arising from the coupling of the amide I and II modes imply a significant degree of structural stability of hydrogen-bonded contacts in alpha-helices and beta-sheets in a series of proteins. Ubiquitin, an alpha/beta-protein, exhibits strong alpha-helical signatures and lacks those of the beta-sheet in the cross-peak region, demonstrating that ubiquitin's beta-sheet exchanges protons with the surrounding solvent and is conformationally unstable.

Amides↗

A new protein folding algorithm based on hydrophobic compactness: Rigid Unconnected Secondary Structure Iterative Assembly (RUSSIA). II: Applications.

The RUSSIA procedure (Rigid Unconnected Secondary Structure Iterative Assembly) produces structural models of cores of small- and medium-sized proteins. Loops are omitted from this treatment and regular secondary structures are reduced to points, the centers of their hydrophobic faces. This methodology relies on the maximum compactness of the hydrophobic residues, as described in detail in Part I. Starting data are the sequence and the predicted limits and natures of regular secondary structures (alpha or beta). Helices are treated as rigid cylinders, whereas beta-strands are collectively taken into account within beta-sheets modeled by helicoid surfaces. Strands are allowed to shift along their mean axis to allow some flexibility and the alpha-helices can be placed on either side of beta-sheets. Numerous initial conformations are produced by discrete rotations of the helices and sheets around the direction going from the center of their hydrophobic face to the global center of the protein. Selection of proposed models is based upon a criterion lying on the minimization of distances separating hydrophobic residues belonging to different regular secondary structures. The procedure is rapid and appears to be robust relative to the quality of starting data (nature and length of regular secondary structures). This dependence of the quality of the model on secondary structure prediction and in particular the beta-sheet topology, is one of the limits of the present algorithm. We present here some results for a set of 12 proteins (alpha, beta and alpha/beta classes) of lengths 40-166 amino acids. The r.m.s. deviations for core models with respect to the native proteins are in the range 1.4-3.7 A.

Algorithms↗

Base-pair probability profiles of RNA secondary structures.

Dynamic programming algorithms are able to predict optimal and suboptimal secondary structures of RNA. These suboptimal or alternative secondary structures are important for the biological function of RNA. The distribution of secondary structures present in solution is governed by the thermodynamic equilibrium between the different structures. An algorithm is presented which approximates the total partition function by a Boltzmann-weighted summation of optimal and suboptimal secondary structures at several temperatures. A clear representation of the equilibrium distribution of secondary structures is derived from a two-dimensional bonding matrix with base-pairing probability as the third dimension. The temperature dependence of the equilibrium distribution gives the denaturation behavior of the nucleic acid, which may be compared to experimental optical denaturation curves after correction for the hypochromicities of the different base-pairs. Similarly, temperature-induced mobility changes detected in temperature-gradient gel electrophoresis of nucleic acids may be interpreted on the basis of the temperature dependence of the equilibrium distribution. Results are illustrated for natural circular and synthetic linear potato spindle tuber viroid RNA respectively, and are compared to experimental data.

Algorithms↗

Conformational analysis and clustering of short and medium size loops connecting regular secondary structures: a database for modeling and prediction.

Loops are regions of nonrepetitive conformation connecting regular secondary structures. We identified 2,024 loops of one to eight residues in length, with acceptable main-chain bond lengths and peptide bond angles, from a database of 223 protein and protein-domain structures. Each loop is characterized by its sequence, main-chain conformation, and relative disposition of its bounding secondary structures as described by the separation between the tips of their axes and the angle between them. Loops, grouped according to their length and type of their bounding secondary structures, were superposed and clustered into 161 conformational classes, corresponding to 63% of all loops. Of these, 109 (51% of the loops) were populated by at least four nonhomologous loops or four loops sharing a low sequence identity. Another 52 classes, including 12% of the loops, were populated by at least three loops of low sequence similarity from three or fewer nonhomologous groups. Loop class suprafamilies resulting from variations in the termini of secondary structures are discussed in this article. Most previously described loop conformations were found among the classes. New classes included a 2:4 type IV hairpin, a helix-capping loop, and a loop that mediates dinucleotide-binding. The relative disposition of bounding secondary structures varies among loop classes, with some classes such as beta-hairpins being very restrictive. For each class, sequence preferences as key residues were identified; those most frequently at these conserved positions than in proteins were Gly, Asp, Pro, Phe, and Cys. Most of these residues are involved in stabilizing loop conformation, often through a positive phi conformation or secondary structure capping. Identification of helix-capping residues and beta-breakers among the highly conserved positions supported our decision to group loops according to their bounding secondary structures. Several of the identified loop classes were associated with specific functions, and all of the member loops had the same function; key residues were conserved for this purpose, as is the case for the parvalbumin-like calcium-binding loops. A significant number, but not all, of the member loops of other loop classes had the same function, as is the case for the helix-turn-helix DNA-binding loops. This article provides a systematic and coherent conformational classification of loops, covering a broad range of lengths and all four combinations of bounding secondary structure types, and supplies a useful basis for modelling of loop conformations where the bounding secondary structures are known or reliably predicted.

Databases, Factual↗