Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Secondary structure”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources
PubMed1996

Incorporation of non-local interactions in protein secondary structure prediction from the amino acid sequence.

Existing approaches to protein secondary structure prediction from the amino acid sequence usually rely on the statistics of local residue interactions within a sliding window and the secondary structural state of the central residue. The practically achieved accuracy limit of such single residue and single sequence prediction methods is 65% in three structural stages (alpha-helix, beta-strand and coil). Further improvement in the prediction quality is likely to require exploitation of various aspects of three-dimensional protein architecture. Here we make such an attempt and present an accurate algorithm for secondary structure prediction based on recognition of potentially hydrogen-bonded residues in a single amino acid sequence. The unique feature of our approach involves database-derived statistics on residue type occurrences in different classes of beta-bridges to delineate interacting beta-strands. The alpha-helical structures are also recognized on the basis of amino acid occurrences in hydrogen-bonded pairs (i,i + 4). The algorithm has a prediction accuracy of 68% in three structural stages, relies only on a single protein sequence as input and has the potential to be improved by 5-7% if homologous aligned sequences are also considered.

Algorithms↗
PubMed2002

Importance of secondary structural specificity determinants in protein folding: insertion of a native beta-sheet sequence into an alpha-helical coiled-coil.

To examine how a short secondary structural element derived from a native protein folds when in a different protein environment, we inserted an 11-residue beta-sheet segment (cassette) from human immunoglobulin fold, Fab new, into an alpha-helical coiled-coil host protein (cassette holder). This de novo design protein model, the structural cassette mutagenesis (SCM) model, allows us to study protein folding principles involving both short- and long-range interactions that affect secondary structure stability and conformation. In this study, we address whether the insertion of this beta-sheet cassette into the alpha-helical coiled-coil protein would result in conformational change nucleated by the long-range tertiary stabilization of the coiled-coil, therefore overriding the local propensity of the cassette to form beta-sheet, observed in its native immunoglobulin fold. The results showed that not only did the nucleating helices of the coiled-coil on either end of the cassette fail to nucleate the beta-sheet cassette to fold with an alpha-helical conformation, but also the entire chimeric protein became a random coil. We identified two determinants in this cassette that prevented coiled-coil formation: (1) a tandem dipeptide NN motif at the N-terminal of the beta-sheet cassette, and (2) the hydrophilic Ser residue, which would be buried in the hydrophobic core if the coiled-coil structure were to fold. By amino acid substitution of these helix disruptive residues, that is, either the replacement of the NN motif with high helical propensity Ala residues or the substitution of Ser with Leu to enhance hydrophobicity, we were able to convert the random coil chimeric protein into a fully folded alpha-helical coiled-coil. We hypothesized that this NN motif is a "secondary structural specificity determinant" which is very selective for one type of secondary structure and may prevent neighboring residues from adopting an alternate protein fold. These sequences with secondary structural specificity determinants have very strong local propensity to fold into a specific secondary structure and may affect overall protein folding by acting as a folding initiation site.

Amino Acid Motifs↗
PubMed1987

Secondary structure of the autoregulatory mRNA binding site of ribosomal protein L1.

The secondary structure of the autoregulatory mRNA binding site of Escherichia coli ribosomal protein L1 has been studied using enzymatic methods. The control region of the E. coli L11 operon was cloned into a vector under control of the Salmonella phage SP6 promoter, and RNA transcribed using SP6 RNA polymerase. The secondary structure of this RNA was probed using structure-specific nucleases, and by comparison of the data with computer predictions of RNA folding, secondary structural features were deduced. The proposed model is consistent with elements of some previously proposed models, but differs in other features. Finally, secondary structure information was obtained from two mutant mRNAs and the structural features correlated with observed phenotypes of the mutants.

Bacterial Proteins↗
PubMed1987

The secondary structure of human 28S rRNA: the structure and evolution of a mosaic rRNA gene.

We have determined the secondary structure of the human 28S rRNA molecule based on comparative analysis of available eukaryotic cytoplasmic and prokaryotic large-rRNA gene sequences. Examination of large-rRNA sequences of both distantly and closely related species has enabled us to derive a structure that accounts both for highly conserved sequence tracts and for previously unanalyzed variable-sequence tracts that account for the evolutionary differences in size among the large rRNAs. Human 28S rRNA is composed of two different types of sequence tracts: conserved and variable. They differ in composition, degree of conservation, and evolution. The conserved regions demonstrate a striking constancy of size and sequence. We have confirmed that the conserved regions of large-rRNA molecules are capable of forming structures that are superimposable on one another. The variable regions contain the sequences responsible for the 83% increase in size of the human large-rRNA molecule over that of Escherichia coli. Their locations in the gene are maintained during evolution. They are G + C rich and largely nonhomologous, contain simple repetitive sequences, appear to evolve by frequent recombinational events, and are capable of forming large, stable hairpins. The secondary-structure model presented here is in close agreement with existing prokaryotic 23S rRNA secondary-structure models. The introduction of this model helps resolve differences between previously proposed prokaryotic and eukaryotic large-rRNA secondary-structure models.

Animals↗
PubMed2004

MSARI: multiple sequence alignments for statistical detection of RNA secondary structure.

We present a highly accurate method for identifying genes with conserved RNA secondary structure by searching multiple sequence alignments of a large set of candidate orthologs for correlated arrangements of reverse-complementary regions. This approach is growing increasingly feasible as the genomes of ever more organisms are sequenced. A program called msari implements this method and is significantly more accurate than existing methods in the context of automatically generated alignments, making it particularly applicable to high-throughput scans. In our tests, it discerned clustalw-generated multiple sequence alignments of signal recognition particle or RNaseP orthologs from controls with 89.1% sensitivity at 97.5% specificity and with 74.4% sensitivity with no false positives in 494 controls. We used msari to conduct a comprehensive scan for secondary structure in mRNAs of coding genes, and we found many genes with known mRNA secondary structure and compelling evidence for secondary structure in other genes. msari uses a method for coping with sequence redundancy that is likely to have applications in a large set of other comparison-based search methods. The program is available for download from http://theory.csail.mit.edu/MSARi.

Algorithms↗
PubMed2004

The SSEA server for protein secondary structure alignment.

SUMMARY: We present a web server that computes alignments of protein secondary structures. The server supports both performing pairwise alignments and searching a secondary structure against a library of domain folds. It can calculate global and local secondary structure element alignments. A combination of local and global alignment steps can be used to search for domains inside the query sequence or help in the discrimination of novel folds. Both the SCOP and PDB fold libraries, clustered at 95 and 40% sequence identity, are available for alignment. AVAILABILITY: The web server interface is freely accessible to academic users at http://protein.cribi.unipd.it/ssea/. The executable version and benchmarking data are available from the same web page.

Algorithms↗
PubMed1993

A self-consistent method for the analysis of protein secondary structure from circular dichroism.

A self-consistent procedure for estimating the secondary structure content from circular dichroism spectra of proteins is presented. In this method the spectrum of the protein to be analyzed is included in the basis set and an initial guess is made for the unknown structure as a first approximation. The resulting matrix equation is solved using the singular value decomposition algorithm and the initial guess is replaced by the solution. The process is repeated until self-consistency is attained. The best features of the variable selection and the locally linearized methods are incorporated in this procedure. We have applied this method to examine the inconsistencies in the CD data, to compare the predictions with different ranges and resolutions of the CD data, and to compare different assignments of secondary structures from X-ray structure analyses in the context of secondary structure predictions. The results are compared using the root mean square differences and correlation coefficients. The results obtained are as good as or better than the previous analyses. For most of the proteins considered the self-consistent solutions obtained with different initial guesses were similar. We find the Kabsch and Sander protein crystal structure analysis to be most suitable for our prediction method.

Circular Dichroism↗
PubMed1997

A 3D-1D substitution matrix for protein fold recognition that includes predicted secondary structure of the sequence.

In protein fold recognition, a probe amino acid sequence is compared to a library of representative folds of known structure to identify a structural homolog. In cases where the probe and its homolog have clear sequence similarity, traditional residue substitution matrices have been used to predict the structural similarity. In cases where the probe is sequentially distant from its homolog, we have developed a (7 x 3 x 2 x 7 x 3) 3D-1D substitution matrix (called H3P2), calculated from a database of 119 structural pairs. Members of each pair share a similar fold, but have sequence identity less than 30%. Each probe sequence position is defined by one of seven residue classes and three secondary structure classes. Each homologous fold position is defined by one of seven residue classes, three secondary structure classes, and two burial classes. Thus the matrix is five-dimensional and contains 7 x 3 x 2 x 7 x 3 = 882 elements or 3D-1D scores. The first step in assigning a probe sequence to its homologous fold is the prediction of the three-state (helix, strand, coil) secondary structure of the probe; here we use the profile based neural network prediction of secondary structure (PHD) program. Then a dynamic programming algorithm uses the H3P2 matrix to align the probe sequence with structures in a representative fold library. To test the effectiveness of the H3P2 matrix a challenging, fold class diverse, and cross-validated benchmark assessment is used to compare the H3P2 matrix to the GONNET, PAM250, BLOSUM62 and a secondary structure only substitution matrix. For distantly related sequences the H3P2 matrix detects more homologous structures at higher reliabilities than do these other substitution matrices, based on sensitivity versus specificity plots (or SENS-SPEC plots). The added efficacy of the H3P2 matrix arises from its information on the statistical preferences for various sequence-structure environment combinations from very distantly related proteins. It introduces the predicted secondary structure information from a sequence into fold recognition in a statistical way that normalizes the inherent correlations between residue type, secondary structure and solvent accessibility.

Algorithms↗
PubMed2002

Poly(L-lysine) as a model drug macromolecule with which to investigate secondary structure and membrane transport, part I: Physicochemical and stability studies.

Low oral bioavailability of therapeutic peptides and proteins generally results from their poor permeability through biological membranes and enzymatic degradation in the gastrointestinal tract. Since different secondary structures exhibit different physicochemical properties such as hydrophobicity, size and shape, changing the secondary structure of a therapeutic polypeptide may be another approach to increasing its membrane permeation. Poly(L-lysine) was used as a model polypeptide. The objectives of this study were to induce secondary structural changes in poly(L-lysine) and to determine the time course over which a given conformer was retained. In addition, the hydrophobicity of each secondary structure of poly(L-lysine) was assessed. The circular dichroism (CD) studies demonstrated that the conditions employed could successfully induce the desired secondary structural changes in poly(L-lysine). The alpha-helix conformer appeared to be more stable at 25 degrees C whereas the beta-sheet conformer could be preserved at 37 degrees C. On the other hand, the random coil conformer was retained at both temperatures. Significant losses of the alpha-helix and the beta-sheet conformers were observed when the pH was reduced. The change in ionic strength did not affect any of the conformers. The octanol/buffer partitioning studies indicated that the alpha-helix and the beta-sheet conformers exhibited significantly different (P < 0.05) hydrophobicities. In conclusion, variation of pH and temperature conditions can be used to induce secondary structural changes in poly(L-lysine). These changes are reversible when the stimuli are removed. The alpha-helix and the beta-sheet conformers of poly(L-lysine) are more lipophilic than the native random coil conformer. Thus, poly(L-lysine) may represent an ideal model polypeptide with which to further investigate the effects of secondary structure on membrane diffusion or permeation.

Cell Membrane Permeability↗
PubMed1993

Induction of changes in the secondary structure of globular proteins by a hydrophobic surface.

Circular dichroism, ellipsometry and radiolabeling techniques were employed to study the induction of changes in the secondary structure of BSA, myoglobin and cytochrome C by a hydrophobic surface. The results showed that adsorbed protein molecules lose their ordered native structure in the initial stage of adsorption and the structure appears to be a random or disordered conformation. Protein molecules adsorbed in later stages adopt a more ordered secondary structure (alpha helix and beta structure). The changes of secondary structure of globular proteins induced by a hydrophobic surface can be explained by the steric interaction between adsorbed proteins as well as by hydrophobic interactions during the adsorption process. In addition, there is obviously an intermediate stage in which the protein molecules are mainly in the beta structure, indicating that for certain proteins, the beta structure may be a more stable secondary structure than alpha helix on the hydrophobic surface.

Adsorption↗
PubMed2000

The role of 5'-leader length, secondary structure and PABP concentration on cap and poly(A) tail function during translation in Xenopus oocytes.

The 5'-cap structure and poly(A) tail of eukaryotic mRNAs function synergistically to promote translation initiation through a physical interaction between the proteins that bind to these regulatory elements. In this study, we have examined the effect of leader length and the presence of secondary structure on the translational competence and the function of the cap and poly(A) tail for mRNAs microinjected into Xenopus oocytes. Increasing the length of the 5'-leader from 17 to 144 nt resulted in a 2- to 4-fold increase in expression from an mRNA containing an unstructured leader but increased expression up to 20-fold for an mRNA containing 5'-proximal structure. Consequently, the presence of secondary structure was less inhibitory for those mRNAs with a longer 5'-leader. Co-injection of poly(A)-binding protein (PABP) mRNA increased the function of the cap and poly(A) tail in promoting translation from poly(A)(+) but not poly(A)(-) mRNAs, particularly for mRNAs containing secondary structure. In the absence of an internal ribosome entry site, expression from the distal cistron of a dicistronic mRNA increased as a function of the length of the intercistronic region and the concentration of PABP. The inhibitory effect of intercistronic located secondary structure on translation was position-dependent. Indeed, the effect of secondary structure was abolished if positioned 134 nt upstream of the distal cistron. These data suggest that the length of a leader, the presence of secondary structure and the concentration of PABP determine the extent to which the cap and poly(A) tail regulate translation.

5' Untranslated Regions↗
PubMed2006

Prediction of protein secondary structure content using amino acid composition and evolutionary information.

Knowing protein structure and inferring its function from the structure are one of the main issues of computational structural biology, and often the first step is studying protein secondary structure. There have been many attempts to predict protein secondary structure contents. Previous attempts assumed that the content of protein secondary structure can be predicted successfully using the information on the amino acid composition of a protein. Recent methods achieved remarkable prediction accuracy by using the expanded composition information. The overall average error of the most successful method is 3.4%. Here, we demonstrate that even if we only use the simple amino acid composition information alone, it is possible to improve the prediction accuracy significantly if the evolutionary information is included. The idea is motivated by the observation that evolutionarily related proteins share the similar structure. After calculating the homolog-averaged amino acid composition of a protein, which can be easily obtained from the multiple sequence alignment by running PSI-BLAST, those 20 numbers are learned by a multiple linear regression, an artificial neural network and a support vector regression. The overall average error of method by a support vector regression is 3.3%. It is remarkable that we obtain the comparable accuracy without utilizing the expanded composition information such as pair-coupled amino acid composition. This work again demonstrates that the amino acid composition is a fundamental characteristic of a protein. It is anticipated that our novel idea can be applied to many areas of protein bioinformatics where the amino acid composition information is utilized, such as subcellular localization prediction, enzyme subclass prediction, domain boundary prediction, signal sequence prediction, and prediction of unfolded segment in a protein sequence, to name a few.

Amino Acid Sequence↗
PubMed2001

Identification of related proteins with weak sequence identity using secondary structure information.

Molecular modeling of proteins is confronted with the problem of finding homologous proteins, especially when few identities remain after the process of molecular evolution. Using even the most recent methods based on sequence identity detection, structural relationships are still difficult to establish with high reliability. As protein structures are more conserved than sequences, we investigated the possibility of using protein secondary structure comparison (observed or predicted structures) to discriminate between related and unrelated proteins sequences in the range of 10%-30% sequence identity. Pairwise comparison of secondary structures have been measured using the structural overlap (Sov) parameter. In this article, we show that if the secondary structures likeness is >50%, most of the pairs are structurally related. Taking into account the secondary structures of proteins that have been detected by BLAST, FASTA, or SSEARCH in the noisy region (with high E: value), we show that distantly related protein sequences (even with <20% identity) can be still identified. This strategy can be used to identify three-dimensional templates in homology modeling by finding unexpected related proteins and to select proteins for experimental investigation in a structural genomic approach, as well as for genome annotation.

Algorithms↗
PubMed2003

Secondary structure alterations in insulin and growth hormone water-in-oil emulsions.

Water-in-oil (w/o) emulsions have shown a promising release profile of small drug molecules and proteins. However, the major concerns are the structural stability, the retention of the activity and to avoid unwanted immunological reactions caused by the changes in protein structure. In the present study, the secondary structure of insulin and growth hormone is investigated after manufacture of w/o emulsions, using Fourier transform infrared (FTIR) spectroscopy. Initial investigations indicate an altered distribution in the secondary structure elements, e.g. alpha-helix and beta-sheet, measured by area overlap calculations. The changes are more pronounced for growth hormone than for insulin. The overlapping area is 0.93 +/- 0.01 for the emulsion containing insulin manufactured at 0 degrees C and homogenised for 3 min, the corresponding value for growth hormone is 0.83 +/- 0.01. The droplet size changes from 0.27 +/- 0.04 microm in the blank w/o emulsion to 0.79 +/- 0.13 and 0.66 +/- 0.21 microm when insulin or growth hormone is incorporated into the w/o emulsions, respectively.

Chemistry, Pharmaceutical↗
PubMed1993

Secondary structure prediction of all-helical proteins in two states.

Can secondary structure prediction be improved by prediction rules that focus on a particular structural class of proteins? To help answer this question, we have assessed the accuracy of prediction for all-helical proteins, using two conceptually different methods and two levels of description. An overall two-state single-residue accuracy of approximately 80% can be obtained by a neural network, no matter whether it is trained on two states (helix and non-helix) or first trained on three states (helix, strand and loop) and then evaluated on two states. For four test proteins, this is similar to the accuracy obtained with inductive logic programming. We conclude that on the level of secondary structure, there is no practical advantage in training on two states, especially given the added margin of error in identifying the structural class of a protein. In the further development of these methods, it is increasingly important to focus on aspects of secondary structure that aid in the construction of a correct 3-D model, such as the correct placement of segments.

Amino Acid Sequence↗
PubMed1985

Prediction of homology and divergence in the secondary structure of polypeptides.

A quantitative procedure is described for the comparison of secondary structure of homologous proteins. Standard predictive methods are used to generate probability profiles from pairs of homologous amino acid sequences; correlation coefficients (R) are then computed between each pair of amino acids for alpha-helix (R alpha), extended structure (R beta), turn (R(t)), and coil (R(c)). R values are >0.2 for correctly aligned homologous sequences. Unrelated or incorrectly aligned sequences give R values near zero. Lack of correlation for a segment of otherwise well-correlated sequences is used to identify structural divergence, which is then evaluated graphically by using difference profiles. A combination of these techniques correctly predicts secondary structural differences between melittin or beta-endorphin and their respective synthetic analogs. The method is potentially useful to describe evolutionary changes in protein secondary structure as well as in the design of peptide analogs.

Amino Acid Sequence↗
PubMed2004

Prediction of protein secondary structure based on residue pairs.

The GOR program for predicting protein secondary structure is extended to include triple correlation. A score system for a residue pair to be at certain conformation state is derived from the conditional weight matrix describing amino acid frequencies at each position of a window flanking the pair under the condition for the pair to be at the fixed state. A program using this score system to predict protein secondary structure is established. After training the model with a learning set created from PDB_SELECT, the program is tested with two test sets. As a method using single sequence for predicting secondary structures, the approach achieves a high accuracy near 70%.

Algorithms↗
PubMed1999

Novel matrix descriptor for secondary structure segments in proteins: demonstration of predictability from circular dichroism spectra.

An extension to standard protein secondary structure predictions using optical spectra that encompasses the number and average lengths of segments of uniform secondary structure in the sequence is demonstrated. The connectivity and numbers of segments can be described by a matrix descriptor [sij] (i, j representing segment types such as helix and beta-sheet strands). Independent knowledge of the fractional concentration of each secondary structure type and of the total number of residues in the protein then with [sij] yields the average segment length of each type. The physical background for prediction of this extended structural descriptor from spectral data is summarized, rules for its generation from reference X-ray structures are defined, and formal variants of its form are discussed. Using a novel neural network approach to analyze a training set of electronic circular dichroism (ECD) and vibrational circular dichroism (VCD) spectra for 23 proteins, matrix descriptors encompassing helix, sheet, and other forms are predicted. The results show that the matrix descriptor can be predicted to an accuracy comparable to that of conventionally predicted average fractional secondary structures. In this respect the ECD predictions of [sij] were significantly more accurate than the VCD ones, which may result from the longer range length dependence of the ECD bandshape and intensity. Summary results for a parallel analysis using Fourier transform infrared spectra indicate somewhat lower reliability than those for VCD.

Circular Dichroism↗