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PubMed1995

The purification, characterization and analysis of primary and secondary-structure of prolyl oligopeptidase from human lymphocytes. Evidence that the enzyme belongs to the alpha/beta hydrolase fold family.

Prolyl oligopeptidase was isolated and purified to homogeneity from human lymphocytes, yielding a specific activity of 7780 mU/mg. The molecular mass using size-exclusion chromatography matches the 76 kDa obtained by SDS/PAGE. This provides evidence that prolyl oligopeptidase is a monomer. The isoelectric point is 4.8 as judged by isoelectric focusing in free solution. Di-isopropyl fluorophosphate and phenylmethylsulphonyl fluoride completely abolish the activity, classifying the enzyme as a serine proteinase. The inhibition by p-chloromercuribenzoic acid indicates the importance of a free sulfhydryl group near the active-site. alpha 1-Casein and ornithine decarboxylase, two proteins containing a PEST sequence, inhibit prolyl oligopeptidase, but were not hydrolyzed. This demonstrates that prolyl oligopeptidase is not participating in the metabolism of proteins according to a PEST-dependent pathway. alpha 1-Antitrypsin partially inhibits the enzyme but in contrast, aprotinin does not. Its inability to cleave corticotropin-releasing factor, ubiquitin, albumin and aprotinin, together with the hydrolysis of bradykinin between Pro7-Arg8 confirms the affinity of prolyl oligopeptidase for small peptides. Multiple sequence alignment does not reveal any similarity with proteases of known tertiary structure. Secondary-structure prediction displays striking similarity with dipeptidyl peptidase IV and acylaminoacyl peptidase. Two characteristic features of the members of the prolyl oligopeptidase family of serine proteases are high-lighted: the linear arrangement of the catalytic triad is nucleophile-acid-base and the proteolytic cleavage releasing the catalytically active C-terminal region of around 500 amino acids from the N-terminal sequence. Secondary structure prediction and comparison of the active-site of serine proteinases with known three-dimensional coordinates prove that Asp641 is the third member of the catalytic triad. The secondary structural organization of the protease domain of prolyl oligopeptidase is in accordance with the alpha/beta hydrolase fold.

Amino Acid Sequence↗
PubMed1981

Primary and secondary structures of Escherichia coli MRE 600 23S ribosomal RNA. Comparison with models of secondary structure for maize chloroplast 23S rRNA and for large portions of mouse and human 16S mitochondrial rRNAs.

We determined 90% of the primary structure of E.coli MRE 600 23S rRNA by applying the sequencing gel technique to products of T1, S1, A and Naja oxiana nuclease digestion. Eight cistron heterogeneities were detected, as well as 16 differences with the published sequence of a 23S rRNA gene of an E.coli K12 strain. The positions of 13 post-transcriptionally modified nucleotides and of single-stranded, double-stranded and subunit surface regions of E.coli 23S rRNA were identified. Using these experimental results and by comparing the sequences of E.coli 23S rRNA, maize chloro. 23S rRNA and mouse and human mit 16S rRNAs, we built models of secondary structure for the two 23S rRNAs and for large portions of the two mit rRNAs. The structures proposed for maize chloroplast and E.coli 23S rRNAs are very similar, consisting of 7 domains closed by long-range base-pairings. In the mitochondrial 16S rRNAs, 3 of these domains are strongly reduced in size and have a very different primary structure compared to those of the 23S rRNAs. These domains were previously found to constitute a compact area in the E.coli 50S subunits. The conserved domains do not belong to this area and contain almost all the modified nucleotides. The most highly conserved domain, 2042-2625, is probably part of the ribosomal A site. Finally, our study strongly suggests that in cytoplasmic ribosomes the 3'-end of 5.8S rRNA is basepaired with the 5'-end of 26S rRNA. This confirms the idea that 5.8S RNA is the counterpart of the 5'-terminal region of prokaryotic 23S rRNA.

Animals↗
PubMed1988

Identification of structural motifs from protein coordinate data: secondary structure and first-level supersecondary structure.

A computer program is described that produces a description of the secondary structure and supersecondary structure of a polypeptide chain using the list of alpha carbon coordinates as input. Restricting the term "secondary structure" to the conformation of contiguous segments of the chain, the program determines the initial and final residues in helices, extended strands, sharp turns, and omega loops. This is accomplished through the use of difference distance matrices. The distances in idealized models of the segments are compared with the actual structure, and the differences are evaluated for agreement within preset limits. The program assigns 90-95% of the residues in most proteins to at least one type of secondary element. In a second step the now-defined helices and strands are idealized as straight line segments, and the axial directions and locations are compiled from the input C alpha coordinate list. These data are used to check for moderate curvature in strands and helices, and the secondary structure list is corrected where necessary. The geometric relations between these line segments are then calculated and output as the first level of supersecondary structure. A maximum of six parameters are required for a complete description of the relations between each pair. Frequently a less complete description will suffice, for example just the interaxial separation and angle. Both the secondary structure and one aspect of the supersecondary structure can be displayed in a character matrix analogous to the distance matrix format. This allows a quite accurate two-dimensional display of the three-dimensional structure, and several examples are presented. A procedure for searching for arbitrary substructures in proteins using distance matrices is also described. A search for the DNA binding helix-turn-helix motif in the Protein Data Bank serves as an example. A further abstraction of the above data can be made in the form of a metamatrix where each diagonal element represents an entire secondary segment rather than a single atom, and the off-diagonal elements contain all the parameters describing their interrelations. Such matrices can be used in a straightforward search for higher levels of supersecondary structure or used in toto as a representation of the entire tertiary structure of the polypeptide chain.

Computer Simulation↗
PubMed2007

MUPRED: a tool for bridging the gap between template based methods and sequence profile based methods for protein secondary structure prediction.

Predicting secondary structures from a protein sequence is an important step for characterizing the structural properties of a protein. Existing methods for protein secondary structure prediction can be broadly classified into template based or sequence profile based methods. We propose a novel framework that bridges the gap between the two fundamentally different approaches. Our framework integrates the information from the fuzzy k-nearest neighbor algorithm and position-specific scoring matrices using a neural network. It combines the strengths of the two methods and has a better potential to use the information in both the sequence and structure databases than existing methods. We implemented the framework into a software system MUPRED. MUPRED has achieved three-state prediction accuracy (Q3) ranging from 79.2 to 80.14%, depending on which benchmark dataset is used. A higher Q3 can be achieved if a query protein has a significant sequence identity (>25%) to a template in PDB. MUPRED also estimates the prediction accuracy at the individual residue level more quantitatively than existing methods. The MUPRED web server and executables are freely available at http://digbio.missouri.edu/mupred.

Algorithms↗
PubMed1994

Control of translation by mRNA secondary structure: the importance of the kinetics of structure formation.

RNA secondary structure is important in a wide variety of biological processes, but relatively little is known about the pathways and kinetics of RNA folding. When the IS10 transposase (tnp) gene is transcribed from a promoter outside the element, little increase in tnp expression is observed. This protection from outside transcription (pot) occurs at the translational level, presumably resulting from mRNA secondary structure proposed to sequester the tnp ribosome-binding site. Here, we confirm the pot RNA structure and show that it blocks 30S ribosomal subunit binding in vitro. Point mutations that abolish protection in vivo map to the pot structure. Surprisingly, these pot mutations do not severely alter the pot secondary structure or increase 30S subunit binding in vitro, except in one case. Using an oligonucleotide hybridization assay, we show that most of the pot mutations slow the kinetics of pot structure formation, with little or no effect on the inhibitory function of the final structure. Moreover, a suppressor mutation reverses this effect. We propose a pathway for pot mRNA folding that is consistent with the mutations and implicates the formation of important kinetic intermediates. The significance of these observations for the RNA folding problem in general is discussed.

Base Sequence↗
PubMed2006

PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures.

Visualizing RNA secondary structures and pseudoknot structures is essential to bioinformatics systems that deal with RNA structures. However, many bioinformatics systems use heterogeneous data structures and incompatible software components, so integration of software components (including a visualization component) into a system can be hindered by incompatibilities between the components of the system. This paper presents an XML web service and web application program for visualizing RNA secondary structures with pseudoknots. Experimental results show that the PseudoViewer web service and web application are useful for resolving many problems with incompatible software components as well as for visualizing large-scale RNA secondary structures with pseudoknots of any type. The web service and web application are available at http://pseudoviewer.inha.ac.kr/.

Computational Biology↗
PubMed1998

Analysis of RNA-dependent RNA polymerase structure and function as guided by known polymerase structures and computer predictions of secondary structure.

RNA-dependent RNA polymerases (RdRps) function as the catalytic subunit of the viral replicase required for the replication of all positive strand RNA viruses. The vast majority of RdRps have been identified solely on the basis of sequence similarity. Structural studies of RdRps have lagged behind those of the DNA-dependent DNA polymerases, DNA-dependent RNA polymerases, and reverse transcriptases until the recent report of the partial crystal structure of the poliovirus RdRp, 3Dpol [Hansen, J. L., et al. (1997). Structure 5, 1109-1122]. We seek to address whether all RdRps will have structures similar to those found in the poliovirus polymerase structure. Therefore, the PHD method of Rost and Sander [Rost, B., and Sander, C. (1993a). J. Mol. Biol. 232, 584-599; Rost, B., and Sander, C. (1994). Protein 19, 55-77] was used to predict the secondary structure of the RdRps from six different viral families: bromoviruses, tobamoviruses, tombusvirus, leviviruses, hepatitis C-like viruses, and picornaviruses. These predictions were compared with the known crystal structure of the poliovirus polymerase. The PHD method was also used to predict picornavirus structures in places in which the poliovirus crystal structure was disordered. All five families and the picornaviruses share a similar order of secondary structure elements present in their polymerase proteins. All except the leviviruses have the unique region observed in the poliovirus 3Dpol that is suggested to be involved in polymerase oligomerization. These structural predictions are used to explain the phenotypes of a collection of mutations that exist in several RNA polymerases. This analysis will help to guide further characterization of RdRps.

Amino Acid Sequence↗
PubMed1996

The use of amino acid patterns of classified helices and strands in secondary structure prediction.

Elements of secondary structure from known protein three-dimensional structures have been classified with respect to their environments in tertiary structures. The size of the solvent-inaccessible face of an alpha-helix and the accessibility patterns on the two sides of a beta-strand have been used to classify the secondary structures. For each class, we have derived a sequence template, giving the amino acid propensity at each position. A prediction is made by calculating the compatibility of segments of polypeptide sequence against templates for each type of secondary structure. This method predicts not only position of a secondary structure in a protein sequence but also the orientation of the secondary structure with respect to the core of the protein tertiary structure. A jack-knife test is applied to 78 proteins of known structure solved at better than 2 A resolution. It shows that this method predicts between 13% and 17% better than the methods of Lim, GOR and Chou and Fasman at the level of secondary structure. The orientations of inaccessible faces are predicted within 50 degrees of correct value for about two-thirds of alpha-helices.

Adenylate Kinase↗
PubMed1994

Long DNA palindromes, cruciform structures, genetic instability and secondary structure repair.

Long DNA palindromes pose a threat to genome stability. This instability is primarily mediated by slippage on the lagging strand of the replication fork between short directly repeated sequences close to the ends of the palindrome. The role of the palindrome is likely to be the juxtaposition of the directly repeated sequences by intra-strand base-pairing. This intra-strand base-pairing, if present on both strands, results in a cruciform structure. In bacteria, cruciform structures have proved difficult to detect in vivo, suggesting that if they form, they are either not replicated or are destroyed. SbcCD, a recently discovered exonuclease of Escherichia coli, is responsible for preventing the replication of long palindromes. These observations lead to the proposal that cells may have evolved a post-replicative mechanism for the elimination and/or repair of large DNA secondary structures.

Base Sequence↗
PubMed2002

Protein and peptide secondary structure and conformational determination with vibrational circular dichroism.

Vibrational circular dichroism (VCD) provides alternative views of protein and peptide conformation with advantages over electronic (UV) CD (ECD) or IR spectroscopy. VCD is sensitive to short-range order, allowing it to discriminate beta-sheet and various helices as well as disordered structure. Quantitative secondary structure analyses use protein VCD bandshapes, but are best combined with ECD and IR for balance. Much recent work has focused on empirical and theoretical VCD analyses of peptides, with detailed prediction of helix, sheet and hairpin spectra and site-specific application of isotopic substitution for structure and folding.

Amino Acid Sequence↗
PubMed1993

Computer simulation of tRNA secondary structure folding.

Computer simulation results of folding linear RNA molecules into secondary structures are presented. The structure is formed by two interacting processes: the RNA molecular chain growth (beginning from an initial length, L0), and the structuring (secondary structure sequential growth in the region of the existing molecular chain, based on the local free energy minimization by sequential addition of elementary substructures--stems). It was found that the final secondary structure formation is greatly influenced by the 'structuring period' T (the ratio of the molecular chain growth rate to the structuring rate), and the direction of RNA synthesis. The computer simulation has been performed for 219 and 906 tRNA genes from two published catalogues, on the whole two-dimensional domain (T,L0) parameters, by using four known free-energy models. Minimum stem length and molecular chain growth direction have been also varied. The calculated secondary structures have been compared to the natural tRNA structures given in the catalogues, and the region of best coincidence for the model parameters has been determined. It has been proved that, on average, > 86% of the paired bases of natural tRNA structures appear in the folding simulation.

Computer Simulation↗
PubMed2003

Neuro-fuzzy structural classification of proteins for improved protein secondary structure prediction.

Fourier transform infrared (FTIR) spectroscopy is a very flexible technique for characterization of protein secondary structure. Measurements can be carried out rapidly in a number of different environments based on only small quantities of proteins. For this technique to become more widely used for protein secondary structure characterization, however, further developments in methods to accurately quantify protein secondary structure are necessary. Here we propose a structural classification of proteins (SCOP) class specialized neural networks architecture combining an adaptive neuro-fuzzy inference system (ANFIS) with SCOP class specialized backpropagation neural networks for improved protein secondary structure prediction. Our study shows that proteins can be accurately classified into two main classes "all alpha proteins" and "all beta proteins" merely based on the amide I band maximum position of their FTIR spectra. ANFIS is employed to perform the classification task to demonstrate the potential of this architecture with moderately complex problems. Based on studies using a reference set of 17 proteins and an evaluation set of 4 proteins, improved predictions were achieved compared to a conventional neural network approach, where structure specialized neural networks are trained based on protein spectra of both "all alpha" and "all beta" proteins. The standard errors of prediction (SEPs) in % structure were improved by 4.05% for helix structure, by 5.91% for sheet structure, by 2.68% for turn structure, and by 2.15% for bend structure. For other structure, an increase of SEP by 2.43% was observed. Those results were confirmed by a "leave-one-out" run with the combined set of 21 FTIR spectra of proteins.

Fuzzy Logic↗
PubMed1982

Studies on the structure of avian myeloblastosis virus (AMV) RNA. III. Electron microscopic definition of secondary structure.

The secondary structure of avian myeloblastosis virus (AMV) RNA was characterized by electron microscopy under moderately denaturing spreading conditions. Under denaturation by aqueous 44% formamide or 77% formamide in the presence of salts, partly stretched RNA molecules with measurable double-stranded regions were observed. This approach allowed the localization from 5 to 11 regions of preserved secondary structure on AMV RNA molecules. Topographic analysis revealed a nonrandom occurrence of stable secondary structures in several prevalent regions. These regions with higher secondary structure stability revealed certain similarity to hairpin structures localized by electron microscopy on Rous sarcoma virus RNA or to highly structured regions found on this RNA by T1 ribonuclease oligonucleotide analysis.

Avian Leukosis Virus↗
PubMed2006

Improved Chou-Fasman method for protein secondary structure prediction.

BACKGROUND: Protein secondary structure prediction is a fundamental and important component in the analytical study of protein structure and functions. The prediction technique has been developed for several decades. The Chou-Fasman algorithm, one of the earliest methods, has been successfully applied to the prediction. However, this method has its limitations due to low accuracy, unreliable parameters, and over prediction. Thanks to the recent development in protein folding type-specific structure propensities and wavelet transformation, the shortcomings in Chou-Fasman method are able to be overcome. RESULTS: We improved Chou-Fasman method in three aspects. (a) Replace the nucleation regions with extreme values of coefficients calculated by the continuous wavelet transform. (b) Substitute the original secondary structure conformational parameters with folding type-specific secondary structure propensities. (c) Modify Chou-Fasman rules. The CB396 data set was tested by using improved Chou-Fasman method and three indices: Q3, Qpre, SOV were used to measure this method. We compared the indices with those obtained from the original Chou-Fasman method and other four popular methods. The results showed that our improved Chou-Fasman method performs better than the original one in all indices, about 10-18% improvement. It is also comparable to other currently popular methods considering all the indices. CONCLUSION: Our method has greatly improved Chou-Fasman method. It is able to predict protein secondary structure as good as current popular methods. By locating nucleation regions with refined wavelet transform technology and by calculating propensity factors with larger size data set, it is likely to get a better result.

Algorithms↗
PubMed2004

Comparison of probabilistic combination methods for protein secondary structure prediction.

MOTIVATION: Protein secondary structure prediction is an important step towards understanding how proteins fold in three dimensions. Recent analysis by information theory indicates that the correlation between neighboring secondary structures are much stronger than that of neighboring amino acids. In this article, we focus on the combination problem for sequences, i.e. combining the scores or assignments from single or multiple prediction systems under the constraint of a whole sequence, as a target for improvement in protein secondary structure prediction. RESULTS: We apply several graphical chain models to solve the combination problem and show that they are consistently more effective than the traditional window-based methods. In particular, conditional random fields (CRFs) moderately improve the predictions for helices and, more importantly, for beta sheets, which are the major bottleneck for protein secondary structure prediction.

Algorithms↗
PubMed2006

Measures for the assessment of fuzzy predictions of protein secondary structure.

Many of the recent secondary structure prediction methods incorporate the idea of fuzzy set theory, where instead of assigning a definite secondary structure to a query residue, probability for the residue being in each of the conformational states is estimated. Moreover, continuous assignment of conformational states to the experimentally observed protein structures can be performed in order to reflect inherent flexibility. Although various measures have been developed for evaluating performances of secondary structure prediction methods, they depend only on the most probable secondary structures. They do not assess the accuracy of the probabilities produced by fuzzy prediction methods, and they cannot incorporate information contained in continuous assignments of conformational states to observed structures. Three important measures for evaluating performance of a secondary structure prediction algorithm, Q score, Segment OVerlap (SOV) measure, and the k-state correlation coefficient (Corr), are deformed into fuzzy measures F score, Fuzzy OVerlap (FOV) measure, and the fuzzy correlation coefficient (Forr), so that the new measures not only assess probabilistic outputs of fuzzy prediction methods, but also incorporate information from continuous assignments of secondary structure. As an example of application, prediction results of four fuzzy secondary structure prediction methods, PSIPRED, PROFking, SABLE, and PREDICT, are assessed using the new fuzzy measures.

Computer Simulation↗
PubMed2002

Efficiency of paramagnetism-based constraints to determine the spatial arrangement of alpha-helical secondary structure elements.

A computational approach has been developed to assess the power of paramagnetism-based backbone constraints with respect to the determination of the tertiary structure, once the secondary structure elements are known. This is part of the general assessment of paramagnetism-based constraints which are known to be relevant when used in conjunction with all classical constraints. The paramagnetism-based constraints here investigated are the pseudocontact shifts, the residual dipolar couplings due to self-orientation of the metalloprotein in high magnetic fields, and the cross correlation between dipolar relaxation and Curie relaxation. The relative constraints are generated by back-calculation from a known structure. The elements of secondary structure are supposed to be obtained from chemical shift index. The problem of the reciprocal orientation of the helices is addressed. It is shown that the correct fold can be obtained depending on the length of the alpha-helical stretches with respect to the length of the non helical segments connecting the alpha-helices. For example, the correct fold is straightforwardly obtained for the four-helix bundle protein cytochrome b562, while the double EF-hand motif of calbindin D9k is hardly obtained without ambiguity. In cases like calbindin D9k, the availability of datasets from different metal ions is helpful, whereas less important is the location of the metal ion with respect to the secondary structure elements.

Algorithms↗