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At least 325 records · Page 18Linked to original sources
PubMed1992

Secondary structure of the pentraxin female protein in water determined by infrared spectroscopy: effects of calcium and phosphorylcholine.

The secondary structure of hamster female protein in aqueous solutions in the presence or absence of calcium and phosphorylcholine has been investigated using Fourier transform infrared spectroscopy. Our present studies provide the first evaluation of the secondary structure of FP and its calcium- and phosphorylcholine-dependent conformational changes. Quantitative analysis indicated that FP is composed of 50% beta-sheet, 11% alpha-helix, 29% beta-turn, and 10% random structures. Calcium- and phosphorylcholine-dependent infrared spectral changes were observed in regions assigned to beta-sheet, alpha-helix, turn, and random structures. The infrared-based secondary structure compositions were used as constraints to compute theoretical locations for the different secondary structures along the amino acid sequence of the FP protein. Two putative calcium-binding sites were proposed for FP (residues 93-109 and 150-168) as well as other members of the pentraxin family on the basis of the theoretical secondary structure predictions and the similarity in sequence between the pentraxins and EF-hand calcium-binding proteins. The changes in protein conformation detected upon binding of calcium and phosphorylcholine provide a mechanism for the effects of these ligands on physiologically important properties of the protein, e.g., activation of complement and association with amyloids.

Alpha-Globulins↗
PubMed2002

Native-like secondary structure of molten globules.

The most common evidence for the existence of secondary structure in a globular protein is the presence of a strongly pronounced far-UV circular dichroism (CD) spectrum. Although CD spectra of native proteins are well described and their quantitative analysis is widely used, similar studies for denatured proteins have still to be done. Far-UV CD spectra of nine proteins in the native and the pH-induced molten globule states were acquired and analyzed. Singular value decomposition showed that the spectra of molten globules could be described as a superposition of at least three independent components (most likely alpha-, beta- and irregular structure). A self-consistent procedure of CD spectra analysis revealed the existence of a clear correlation between the shape of the molten globule spectra and the content of secondary structure elements in the corresponding native proteins, as determined from X-ray data. A mathematical expression of this correlation in terms of the Pierson coefficient amounts to the value of 0.9 for both the alpha-helix and the beta-structure. Thus, the secondary structure of proteins in the molten globule state is close to that in the native state.

Circular Dichroism↗
PubMed1994

Structure of influenza virus RNP. I. Influenza virus nucleoprotein melts secondary structure in panhandle RNA and exposes the bases to the solvent.

The influenza virus genome consists of eight segments of negative-sense RNA, i.e. the viral (v) RNA forms the template for the mRNA. Each segment is encapsidated by the viral nucleoprotein to form a ribonucleoprotein (RNP) particle and each RNP carries its own polymerase complex. We studied the interaction of purified nucleoprotein with RNA in vitro, by using a variety of enzymatic and chemical probes for RNA conformation. Our results suggest that the nucleoprotein binds to the vRNA backbone without apparent sequence specificity, exposing the bases to the outside and melting all secondary structure. In this way, the viral polymerase may transcribe the RNA without the need for dissociating the nucleoprotein and without being stopped by RNA secondary structure, and the viral RNPs are ready to start transcription as soon as they enter the host cell.

Base Composition↗
PubMed1990

Effect of lysine modification on the secondary structure of ovalbumin.

In order to determine the effect of chemical modification of the epsilon-amino groups on the secondary structure of ovalbumin, we prepared six acetylated (17, 36, 54, 70, 82, and 98%) and four succinylated derivatives (25, 50, 72, and 97%) of the protein. Native ovalbumin and the acylated derivatives were homogeneous as revealed by the electrophoretic pattern. The UV-absorption and fluorescence spectra changed progressively with the extent of modification. However, circular dichroic (CD) studies indicated that acylation of 15 of the 20 lysine residues had little effect on the secondary structure of ovalbumin. Acylation of the remaining five lysine residues resulted in a fairly severe change in the secondary structure. The alpha-helical content decreased from about 31% in the native state to 16.5% in the 97% succinylated ovalbumin and to 21.5% in the 98% acetylated derivative. A comparison of these data with the spectral and hydrodynamic data of Qasim and Salahuddin (1978) suggested that the secondary structure of ovalbumin is more resistant to acylation than is the tertiary structure and, thus, the tertiary and the secondary structures are, to some extent, mutually independent. Raising the pH to 11.2 did not alter the secondary structure of ovalbumin and increasing the ionic strength by more than 20-fold did not reverse the loss of helical structure in 97% succinylated protein. These two observations suggest that the change in secondary structure upon maximal acylation may not only involve electrostatic effects, but also certain other factors, such as steric hindrance due to the entering bulky groups.

Acetylation↗
PubMed2001

The relationship between third-codon position nucleotide content, codon bias, mRNA secondary structure and gene expression in the drosophilid alcohol dehydrogenase genes Adh and Adhr.

To gain insights into the relationship between codon bias, mRNA secondary structure, third-codon position nucleotide distribution, and gene expression, we predicted secondary structures in two related drosophilid genes, Adh and Adhr, which differ in degree of codon bias and level of gene expression. Individual structural elements (helices) were inferred using the comparative method. For each gene, four types of randomization simulations were performed to maintain/remove codon bias and/or to maintain or alter third-codon position nucleotide composition (N3). In the weakly expressed, weakly biased gene Adhr, the potential for secondary structure formation was found to be much stronger than in the highly expressed, highly biased gene Adh. This is consistent with the observation of approximately equal G and C percentages in Adhr ( approximately 31% across species), whereas in Adh the N3 distribution is shifted toward C (42% across species). Perturbing the N3 distribution to approximately equal amounts of A, G, C, and T increases the potential for secondary structure formation in Adh, but decreases it in Adhr. On the other hand, simulations that reduce codon bias without changing N3 content indicate that codon bias per se has only a weak effect on the formation of secondary structures. These results suggest that, for these two drosophilid genes, secondary structure is a relatively independent, negative regulator of gene expression. Whereas the degree of codon bias is positively correlated with level of gene expression, strong individual secondary structural elements may be selected for to retard mRNA translation and to decrease gene expression.

Alcohol Dehydrogenase↗
PubMed2006

YASSPP: better kernels and coding schemes lead to improvements in protein secondary structure prediction.

The accurate prediction of a protein's secondary structure plays an increasingly critical role in predicting its function and tertiary structure, as it is utilized by many of the current state-of-the-art methods for remote homology, fold recognition, and ab initio structure prediction. We developed a new secondary structure prediction algorithm called YASSPP, which uses a pair of cascaded models constructed from two sets of binary SVM-based models. YASSPP uses an input coding scheme that combines both position-specific and nonposition-specific information, utilizes a kernel function designed to capture the sequence conservation signals around the local window of each residue, and constructs a second-level model by incorporating both the three-state predictions produced by the first-level model and information about the original sequence. Experiments on three standard datasets (RS126, CB513, and EVA common subset 4) show that YASSPP is capable of producing the highest Q3 and SOV scores than that achieved by existing widely used schemes such as PSIPRED, SSPro 4.0, SAM-T99sec, as well as previously developed SVM-based schemes. On the EVA dataset it achieves a Q3 and SOV score of 79.34 and 78.65%, which are considerably higher than the best reported scores of 77.64 and 76.05%, respectively.

Algorithms↗
PubMed1986

Analysis of protein circular dichroism spectra for secondary structure using a simple matrix multiplication.

Inverse circular dichroism (CD) spectra are presented for each of the five major secondary structures of proteins: alpha-helix, antiparallel and parallel beta-sheet, beta-turn, and other (random) structures. The fraction of the each secondary structure in a protein is predicted by forming the dot product of the corresponding inverse CD spectrum, expressed as a vector, with the CD spectrum of the protein digitized in the same way. We show how this method is based on the construction of the generalized inverse from the singular value decomposition of a set of CD spectra corresponding to proteins whose secondary structures are known from X-ray crystallography. These inverse spectra compute secondary structure directly from protein CD spectra without resorting to least-squares fitting and standard matrix inversion techniques. In addition, spectra corresponding to the individual secondary structures, analogous to the CD spectra of synthetic polypeptides, are generated from the five most significant CD eigenvectors.

Chemical Phenomena↗
PubMed1992

Proton, carbon, and nitrogen chemical shifts accurately delineate differences and similarities in secondary structure between the homologous proteins IRAP and IL-1 beta.

1H alpha, 13C alpha, and 15N alpha secondary shifts, defined as the difference between the observed value and the random coil value, have been calculated for interleukin-1 receptor antagonist protein and interleukin-1 beta. Averaging of the secondary chemical shifts with those of adjacent residues was used to smooth out local effects and to obtain a correlation dependent on secondary structure. Differences and similarities in the placement of secondary structure elements in the primary sequences of these structurally homologous proteins are manifested in the smoothed secondary chemical shifts of all three types of nuclei. The close correlation observed between the secondary chemical shifts and the previously defined locations of secondary structure, as defined by traditional methods, exemplifies the advantage of chemical shifts to delineate regions of secondary structure.

Amino Acid Sequence↗
PubMed2007

Study and prediction of secondary structure for membrane proteins.

In this paper we present a novel approach to membrane protein secondary structure prediction based on the statistical stepwise discriminant analysis method. A new aspect of our approach is the possibility to derive physical-chemical properties that may affect the formation of membrane protein secondary structure. The certain physical-chemical properties of protein chains can be used to clarify the formation of the secondary structure types under consideration. Another aspect of our approach is that the results of multiple sequence alignment, or the other kinds of sequence alignment, are not used in the frame of the method. Using our approach, we predicted the formation of three main secondary structure types (alpha-helix, beta-structure and coil) with high accuracy, that is Q(3) = 76%. Predicting the formation of alpha-helix and non-alpha-helix states we reached the accuracy which was measured as Q(2) = 86%. Also we have identified certain protein chain properties that affect the formation of membrane protein secondary structure. These protein properties include hydrophobic properties of amino acid residues, presence of Gly, Ala and Val amino acids, and the location of protein chain end.

Amino Acid Sequence↗
PubMed2000

Estimating the significance of sequence order in protein secondary structure and prediction.

MOTIVATION: How critical is the sequence order information in predicting protein secondary structure segments? We tried to get a rough insight on it from a theoretical approach using both a prediction algorithm and structural fragments from Protein Databank (PDB). RESULTS: Using reverse protein sequences and PDB structural fragments, we theoretically estimated the significance of the order for protein secondary structure and prediction. On average: (1) 79% of protein sequence segments resulted in the same prediction in both normal and reverse directions, which indicated a relatively high conservation of secondary structure propensity in the reverse direction; (2) the reversed sequence prediction alone performed less accurately than the normal forward sequence prediction, but comparably high (2% difference); (3) the commonly predicted regions showed a slightly higher prediction accuracy (4%) than the normal sequences prediction; and (4) structural fragments which have counterparts in reverse direction in the same protein showed a comparable degree of secondary structure conservation (73% identity with reversed structures on average for pentamers). CONTACT: jong@biosophy.org; dietmann@ebi.ac.uk; heger@ebi.ac.uk; holm@ebi.ac.uk

Algorithms↗
PubMed2001

A refined accuracy index to evaluate algorithms of protein secondary structure prediction.

Nowadays even a 1% increase of the accuracy for the secondary structure prediction is considered remarkable progress. In this case, we have to consider the reasonableness of the accuracy index Q3, which is used widely. A refined accuracy index, called Q8, is proposed to evaluate algorithms of secondary structure prediction. It is shown that Q8 is superior to the widely used index Q3 in that the former carries more information of the predictive accuracy matrix than does the latter. Therefore, algorithms are evaluated more objectively by Q8 than Q3. Based on 396 nonhomologous proteins, five currently available algorithms of secondary structure prediction were evaluated and compared using the new index Q8. Of the five algorithms, PHD turned out to be the unique algorithm, with Q8 accuracy better than 70%. It is suggested that Q3 should be replaced by Q8 in evaluating secondary structure prediction in future studies.

Algorithms↗
PubMed2005

Protein energetic conformational analysis from NMR chemical shifts (PECAN) and its use in determining secondary structural elements.

We present an energy model that combines information from the amino acid sequence of a protein and available NMR chemical shifts for the purposes of identifying low energy conformations and determining elements of secondary structure. The model ("PECAN", Protein Energetic Conformational Analysis from NMR chemical shifts) optimizes a combination of sequence information and residue-specific statistical energy function to yield energetic descriptions most favorable to predicting secondary structure. Compared to prior methods for secondary structure determination, PECAN provides increased accuracy and range, particularly in regions of extended structure. Moreover, PECAN uses the energetics to identify residues located at the boundaries between regions of predicted secondary structure that may not fit the stringent secondary structure class definitions. The energy model offers insights into the local energetic patterns that underlie conformational preferences. For example, it shows that the information content for defining secondary structure is localized about a residue and reaches a maximum when two residues on either side are considered. The current release of the PECAN software determines the well-defined regions of secondary structure in novel proteins with assigned chemical shifts with an overall accuracy of 90%, which is close to the practical limit of achievable accuracy in classifying the states.

Algorithms↗
PubMed1996

Prediction of the secondary structure content of globular proteins based on structural classes.

The prediction of the secondary structure content (alpha-helix and beta-strand content) of a globular protein may play an important complementary role in the prediction of the protein's structure. We propose a new prediction algorithm based on Chou's database [Chou (1995), Proteins Struct. Funct. Genet. 21, 319]. The new algorithm is an improved multiple linear regression method, taking the nonlinear and coupling terms of the frequencies of different amino acids into account. The prediction is also based on the structural classes of proteins. A resubstitution examination for the algorithm shows that the average errors are 0.040 and 0.033 for the prediction of alpha-helix content and beta-strand content, respectively. The examination of cross-validation, the jackknife analysis, shows that the average errors are 0.051 and 0.044 for the prediction of alpha-helix content and beta-strand content, respectively. Both examinations indicate the self-consistency and the extrapolative effectiveness of the new algorithm. Compared with the other methods available currently, our method has the merits of simplicity and convenience for use, as well as a high prediction accuracy. By incorporating the prediction of the structural classes, the only input of our method is the amino acid composition of the protein to be predicted.

Algorithms↗
PubMed1998

Prediction of the secondary structure contents of globular proteins based on three structural classes.

The prediction of the secondary structural contents (those of alpha-helix and beta-strand) of a globular protein is of great use in the prediction of protein structure. In this paper, a new prediction algorithm has been proposed based on Chou's database [Chou (1995), Proteins 21, 319-344]. The new algorithm is an improved multiple linear regression method, taking into account the nonlinear and coupling terms of the frequencies of different amino acids and the length of the protein. The prediction is also based on the structural classes of proteins, but instead of four classes, only three classes are considered, the alpha class, beta class, and the mixed alpha+beta and alpha/beta class or simply the alphabeta class. Thus the ambiguity that usually occurs between alpha+beta proteins and alpha/beta proteins is eliminated. A resubstitution examination for the algorithm shows that the average absolute errors are 0.040 and 0.035 for the prediction of alpha-helix content and beta-strand content, respectively. An examination of cross-validation, the jackknife analysis, shows that the average absolute errors are 0.051 and 0.045 for the prediction of alpha-helix content and beta-strand content, respectively. Both examinations indicate the self-consistency and the extrapolating effectiveness of the new algorithm. Compared with other methods, ours has the merits of simplicity and convenience for use, as well as high prediction accuracy. By incorporating the prediction of the structural classes, the only input of our method is the amino acid composition and the length of the protein to be predicted.

Algorithms↗
PubMed2006

Identification of consensus RNA secondary structures using suffix arrays.

BACKGROUND: The identification of a consensus RNA motif often consists in finding a conserved secondary structure with minimum free energy in an ensemble of aligned sequences. However, an alignment is often difficult to obtain without prior structural information. Thus the need for tools to automate this process. RESULTS: We present an algorithm called Seed to identify all the conserved RNA secondary structure motifs in a set of unaligned sequences. The search space is defined as the set of all the secondary structure motifs inducible from a seed sequence. A general-to-specific search allows finding all the motifs that are conserved. Suffix arrays are used to enumerate efficiently all the biological palindromes as well as for the matching of RNA secondary structure expressions. We assessed the ability of this approach to uncover known structures using four datasets. The enumeration of the motifs relies only on the secondary structure definition and conservation only, therefore allowing for the independent evaluation of scoring schemes. Twelve simple objective functions based on free energy were evaluated for their potential to discriminate native folds from the rest. CONCLUSION: Our evaluation shows that 1) support and exclusion constraints are sufficient to make an exhaustive search of the secondary structure space feasible. 2) The search space induced from a seed sequence contains known motifs. 3) Simple objective functions, consisting of a combination of the free energy of matching sequences, can generally identify motifs with high positive predictive value and sensitivity to known motifs.

Algorithms↗
PubMed2002

Dynalign: an algorithm for finding the secondary structure common to two RNA sequences.

With the rapid increase in the size of the genome sequence database, computational analysis of RNA will become increasingly important in revealing structure-function relationships and potential drug targets. RNA secondary structure prediction for a single sequence is 73 % accurate on average for a large database of known secondary structures. This level of accuracy provides a good starting point for determining a secondary structure either by comparative sequence analysis or by the interpretation of experimental studies. Dynalign is a new computer algorithm that improves the accuracy of structure prediction by combining free energy minimization and comparative sequence analysis to find a low free energy structure common to two sequences without requiring any sequence identity. It uses a dynamic programming construct suggested by Sankoff. Dynalign, however, restricts the maximum distance, M, allowed between aligned nucleotides in the two sequences. This makes the calculation tractable because the complexity is simplified to O(M(3)N(3)), where N is the length of the shorter sequence. The accuracy of Dynalign was tested with sets of 13 tRNAs, seven 5 S rRNAs, and two R2 3' UTR sequences. On average, Dynalign predicted 86.1 % of known base-pairs in the tRNAs, as compared to 59.7 % for free energy minimization alone. For the 5 S rRNAs, the average accuracy improves from 47.8 % to 86.4 %. The secondary structure of the R2 3' UTR from Drosophila takahashii is poorly predicted by standard free energy minimization. With Dynalign, however, the structure predicted in tandem with the sequence from Drosophila melanogaster nearly matches the structure determined by comparative sequence analysis.

3' Untranslated Regions↗
PubMed2000

Comparative sequence analysis and patterns of covariation in RNA secondary structures.

A novel method of RNA secondary structure prediction based on a comparison of nucleotide sequences is described. This method correctly predicts nearly all evolutionarily conserved secondary structures of five different RNAs: tRNA, 5S rRNA, bacterial ribonuclease P (RNase P) RNA, eukaryotic small subunit rRNA, and the 3' untranslated region (UTR) of the Drosophila bicoid (bcd) mRNA. Furthermore, covariations occurring in the helices of these conserved RNA structures are analyzed. Two physical parameters are found to be important determinants of the evolution of compensatory mutations: the length of a helix and the distance between base-pairing nucleotides. For the helices of bcd 3' UTR mRNA and RNase P RNA, a positive correlation between the rate of compensatory evolution and helix length is found. The analysis of Drosophila bcd 3' UTR mRNA further revealed that the rate of compensatory evolution decreases with the physical distance between base-pairing residues. This result is in qualitative agreement with Kimura's model of compensatory fitness interactions, which assumes that mutations occurring in RNA helices are individually deleterious but become neutral in appropriate combinations.

Analysis of Variance↗
PubMed2004

Secondary-structure characterization by far-UV CD of highly purified uncoupling protein 1 expressed in yeast.

The rat UCP1 (uncoupling protein 1) is a mitochondrial inner-membrane carrier involved in energy dissipation and heat production. We expressed UCP1 carrying a His6 epitope at its C-terminus in Saccharomyces cerevisiae mitochondria. The recombinant-tagged UCP1 was purified by immobilized metal-ion affinity chromatography to homogeneity (>95%). This made it suitable for subsequent biophysical characterization. Fluorescence resonance energy transfer experiments showed that n-dodecyl-beta-D-maltoside-solubilized UCP1-His6 retained its PN (purine nucleotide)-binding capacity. The far-UV CD spectrum of the functional protein clearly indicated the predominance of alpha-helices in the UCP1 secondary structure. The UCP1 secondary structure exhibited an alpha-helical degree of approx. 68%, which is at least 25% higher than the previously reported estimations based on computational predictions. Moreover, the helical content remained unchanged in free and PN-loaded UCP1. A homology model of the first repeat of UCP1, built on the basis of X-ray-solved close parent, the ADP/ATP carrier, strengthened the CD experimental results. Our experimental and computational results indicate that (i) alpha-helices are the major component of UCP1 secondary structure; (ii) PN-binding mechanism does not involve significant secondary-structure rearrangement; and (iii) UCP1 shares similar secondary-structure characteristics with the ADP/ATP carrier, at least for the first repeat.

Amino Acid Sequence↗