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At least 649 records · Page 36Linked to original sources
PubMed2006

Probing the secondary structure of expansion segment ES6 in 18S ribosomal RNA.

Expansion segment ES6 in 18S ribosomal RNA is, unlike many other expansion segments, present in all eukaryotes. The available data suggest that ES6 is located on the surface of the small ribosomal subunit. Here we have analyzed the secondary structure of the complete ES6 sequence in intact ribosomes from three eukaryotes, wheat, yeast, and mouse, representing different eukaryotic kingdoms. The availability of the ES6 sequence for modification and cleavage by structure sensitive chemicals and enzymatic reagents was analyzed by primer extension and gel electrophoresis on an ABI 377 automated DNA sequencer. The experimental results were used to restrict the number of possible secondary structure models of ES6 generated by the folding software MFOLD. The modification data obtained from the three experimental organisms were very similar despite the sequence variation. Consequently, similar secondary structure models were obtained for the ES6 sequence in wheat, yeast, and mouse ribosomes. A comparison of sequence data from more than 6000 eukaryotes showed that similar structural elements could also be formed in other organisms. The comparative analysis also showed that the extent of compensatory base changes in the suggested helices was low. The in situ structure analysis was complemented by a secondary structure analysis of wheat ES6 transcribed and folded in vitro. The obtained modification data indicate that the secondary structure of the in vitro transcribed sequence differs from that observed in the intact ribosome. These results suggest that chaperones, ribosomal proteins, and/or tertiary rRNA interactions could be involved in the in vivo folding of ES6.

Animals↗
PubMed1994

Effects of calcium, magnesium, and phosphorylcholine on secondary structures of human C-reactive protein and serum amyloid P component observed by infrared spectroscopy.

The secondary structures of human C-reactive protein (CRP) and serum amyloid P component (SAP) in D2O-based solutions in the presence or absence of calcium, magnesium, and phosphorylcholine have been investigated using Fourier transform infrared spectroscopy. Quantitative analysis provided estimations of about 50% beta-sheet, 12% alpha-helix, 24% beta-turn, and 14% unordered structure for CRP and about 54% beta-sheet, 12% alpha-helix, 25% beta-turn, and 9% unordered structure for SAP. With both proteins significant calcium-dependent changes were observed in conformation-sensitive amide I regions assigned to each type of structure. The CRP spectrum was also affected by magnesium, but the changes differed from those induced by calcium. The SAP spectrum was not affected by magnesium. Phosphorylcholine in the presence of calcium also affected the spectrum of CRP but not the spectrum of SAP. Our present study provides the first direct comparison of the secondary structures of the pentraxins human CRP and SAP and hamster female protein (Dong, A., Caughey, B., Caughey, W. S., Bhat, K. S., and Coe, J. E. (1992) Biochemistry 32, 9364-9370). These findings suggest that the three pentraxins have similar secondary structure compositions and calcium-dependent conformational changes, but differ significantly in their responses to phosphorylcholine and magnesium. Such properties are expected to be relevant to the incompletely understood roles of these highly conserved proteins including binding to nuclear proteins, complement activation, and association with amyloids.

C-Reactive Protein↗
PubMed1994

The role of side-chain hydrogen bonds in the formation and stabilization of secondary structure in soluble proteins.

Intra-molecular side-chain:main-chain (sch:mch) and side-chain (sch:sch) hydrogen bonds observed in 44 well refined crystallographic protein structures with non-homologous sequences have been identified, classified and analysed to detect recurring structural patterns. Each observed bond was characterized by the position of its acceptor and donor groups relative to the N and C termini of the particular secondary structure in which they occur and according to their appearance within the same of sequentially separated secondary structures. The role of short-range hydrogen bonds in the formation and stabilization of a secondary structure and the importance of long-range hydrogen bonds as a cohesive force for different structural segments were also examined. It was found that the N terminus of alpha-helices is characterized by recurring sch:mch and sch:sch bonds with elements of the preceding coil segment, while at the C terminus a frequent intra-helix sch:mch hydrogen bond was frequently observed. The residues at or near the beta-strand termini often cross-linked, through hydrogen-bonding, non-sequential coil segments. Coil structures were characterized by recurring, internal sch:mch hydrogen bonding involving small polar side-chain groups situated at or near their N termini (coil N-capping). The significance of hydrogen bonds as formers and stabilizers of a protein fold and the association of its secondary structural units was also considered through an examination of bond density and distribution throughout the protein tertiary structure.

Amino Acids↗
PubMed2004

Effects of acid and alkali on the light absorption, energy transfer and protein secondary structures of core antenna subunits CP43 and CP47 of photosystem II.

The effects of acid and alkali treatment on the light absorption, energy transfer and protein secondary structure of the photosystem II core antenna CP43 and CP47 of spinach were investigated by the absorption spectra, fluorescence emission spectra and circular dichroism spectra. It has been found that acid treatment caused the appearance of absorption characteristic of pheophytin a (Pheo a), whereas alkali treatment induced a new absorption peak at 642 nm. The energy transfer between beta-carotene and chlorophyll a (Chl a) in CP43 was easily disturbed by alkali, whereas in CP47 was readily affected by acid. As to the effects on the secondary structure of proteins in CP43 and CP47, effects of acid were far less than those of alkali. Both acid and alkali disturbed the microenvironment of Chl a and interfered exciton interaction between Chl a molecules. It was suggested that acid and alkali affect the light absorption, energy transfer and protein secondary structure of CP43 and CP47 in a different way. H+ can permeate into the internal space of alpha-helix, change Chl a into Pheo a and disturb the microenvironment of pigments without damaging the secondary structure of protein, whereas OH- can induce the protein unfolding at first, then saponify Chl a to chlorophyllide and disturb the microenvironment of pigments.

Acids↗
PubMed1998

UV resonance Raman-selective amide vibrational enhancement: quantitative methodology for determining protein secondary structure.

We have directly determined the amide band resonance Raman spectra of the "average" pure alpha-helix, beta-sheet, and unordered secondary structures by exciting within the amide pi-->pi* transitions at 206.5 nm. The Raman spectra are dominated by the amide bands of the peptide backbone. We have empirically determined the average pure alpha-helix, beta-sheet, and unordered resonance Raman spectra from the amide resonance Raman spectra of 13 proteins with well-known X-ray crystal structures. We demonstrate that we can simultaneously utilize the amide I, II, and III bands and the Calpha-H amide bending vibrations of these average secondary structure spectra to directly determine protein secondary structure. The UV Raman method appears to be complementary, and in some cases superior, to the existing methods, such as CD, VCD, and absorption spectroscopy. In addition, the spectra are immune to the light-scattering artifacts that plague CD, VCD, and IR absorption measurements. Thus, it will be possible to examine proteins in micelles and other scattering media.

Amides↗
PubMed1983

Secondary structure of bovine beta-lactoglobulin B.

Secondary-structure-prediction algorithms have been used to find the segments of beta-lactoglobulin sequence most likely to fit the circular dichroism assignment of 15% alpha-helix, 50% beta-sheet, and 15-20% reverse turn. A number of segments may have an alpha-helical conformation but the most prominent region of alpha-helix is from residue 129 to 143. A further probable alpha-helix segment is residues 65-76. The number of residues predicted to occur in segments of beta-sheet structure is less than expected. However, the most likely segments are for residues 1-6, 11-16, 39-45, 80-85, 92-96, 101-107, 117-123, and 145-151. Predicted reverse-turn tetrapeptides are residues 7-10, 49-52, 61-64, 88-91, and 112-115. These predicted secondary structures are consistent with the low-resolution structure of the molecule determined by X-ray diffraction studies.

Amino Acid Sequence↗
PubMed1993

Sequence-specific 1H-NMR assignment and secondary structure of black mamba dendrotoxin I, a highly selective blocker of voltage-gated potassium channels.

The secondary structure of dendrotoxin I, an important constituent of the venom of the African black mamba snake Dendroaspis polylepis polylepis, was determined in aqueous solution by two-dimensional methods. Complete sequence-specific 1H-NMR assignment was obtained with the exception of the backbone amide proton of Gly39 and Cys40. Dendrotoxin I is based on a central antiparallel beta-sheet and two small helices located at the N- and the C-terminal extremities. These secondary-structural units occur at exactly the same places in the amino acid sequence as those of bovine pancreatic trypsin inhibitor (BPTI), with which dendrotoxin I shares 33% sequence similarity. According to the disulfide-bridge positions and the long-range NOE observed these secondary-structural elements fold in a similar manner to BPTI. This similarity allows an hypothesis according to which dendrotoxin I could derive from an ancestral Künitz-type proteinase inhibitor. This ancestor would have been heavily mutated at amino acid positions not critical for gross structure. The spatial locations of the solvent-exposed amino acids concerned could therefore serve as a guideline for interpretation of the structure/activity relationship of dendrotoxin I for the blockage of voltage-sensitive potassium channels of which dendrotoxin I is a strong inhibitor. The possible connections with other polypeptide toxins that block related ion currents is discussed.

Amino Acid Sequence↗
PubMed2006

Finding motifs in protein secondary structure for use in function prediction.

This paper presents a novel algorithm for the discovery of biological sequence motifs. Our motivation is the prediction of gene function. We seek to discover motifs and combinations of motifs in the secondary structure of proteins for application to the understanding and prediction of functional classes. The motifs found by our algorithm allow both flexible length structural elements and flexible length gaps and can be of arbitrary length. The algorithm is based on neither top-down nor bottom-up search, but rather is dichotomic. It is also "anytime," so that fixed termination of the search is not necessary. We have applied our algorithm to yeast sequence data to discover rules predicting function classes from secondary structure. These resultant rules are informative, consistent with known biology, and a contribution to scientific knowledge. Surprisingly, the rules also demonstrate that secondary structure prediction algorithms are effective for membrane proteins and suggest that the association between secondary structure and function is stronger in membrane proteins than globular ones. We demonstrate that our algorithm can successfully predict gene function directly from predicted secondary structure; e.g., we correctly predict the gene YGL124c to be involved in the functional class "cytoplasmic and nuclear degradation." Datasets and detailed results (generated motifs, rules, evaluation on test dataset, and predictions on unknown dataset) are available at www.aber.ac.uk/compsci/Research/bio/dss/yeast.ss.mips/, and www.genepredictions.org.

Algorithms↗
PubMed1994

The secondary structure of the ets domain of human Fli-1 resembles that of the helix-turn-helix DNA-binding motif of the Escherichia coli catabolite gene activator protein.

The ets family of eukaryotic transcription factors is characterized by a conserved DNA-binding domain of approximately 85 amino acids for which the three-dimensional structure is not known. By using multidimensional NMR spectroscopy, we have determined the secondary structure of the ets domain of one member of this gene family, human Fli-1, both in the free form and in a complex with a 16-bp cognate DNA site. The secondary structure of the Fli-1 ets domain consists of three alpha-helices and a short four-stranded antiparallel beta-sheet. This secondary structure arrangement resembles that of the DNA-binding domain of the catabolite gene activator protein of Escherichia coli, as well as those of several eukaryotic DNA-binding proteins including histone H5, HNF-3/fork head, and the heat shock transcription factor. Differences in chemical shifts of backbone resonances and amide exchange rates between the DNA-bound and free forms of the Fli-1 ets domain suggest that the third helix is the DNA recognition helix, as in the catabolite gene activator protein and other structurally related proteins. These results suggest that the ets domain is structurally similar to the catabolite gene activator protein family of helix-turn-helix DNA-binding proteins.

Amino Acid Sequence↗
PubMed2005

HYPROSP II--a knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence.

MOTIVATION: In our previous approach, we proposed a hybrid method for protein secondary structure prediction called HYPROSP, which combined our proposed knowledge-based prediction algorithm PROSP and PSIPRED. The knowledge base constructed for PROSP contains small peptides together with their secondary structural information. The hybrid strategy of HYPROSP uses a global quantitative measure, match rate, to determine whether PROSP or PSIPRED is to be used for the prediction of a target protein. HYPROSP made slight improvement of Q(3) over PSIPRED because PROSP predicted well for proteins with match rate >80%. As the portion of proteins with match rate >80% is quite small and as the performance of PSIPRED also improves, the advantage of HYPROSP is diluted. To overcome this limitation and further improve the hybrid prediction method, we present in this paper a new hybrid strategy HYPROSP II that is based on a new quantitative measure called local match rate. RESULTS: Local match rate indicates the amount of structural information that each amino acid can extract from the knowledge base. With the local match rate, we are able to define a confidence level of the PROSP prediction results for each amino acid. Our new hybrid approach, HYPROSP II, is proposed as follows: for each amino acid in a target protein, we combine the prediction results of PROSP and PSIPRED using a hybrid function defined on their respective confidence levels. Two datasets in nrDSSP and EVA are used to perform a 10-fold cross validation. The average Q(3) of HYPROSP II is 81.8% and 80.7% on nrDSSP and EVA datasets, respectively, which is 2.0% and 1.1% better than that of PSIPRED. For local structures with match rate >80%, the average Q(3) improvement is 4.4% on the nrDSSP dataset. The use of local match rate improves the accuracy better than global match rate. There has been a long history of attempts to improve secondary structure prediction. We believe that HYPROSP II has greatly utilized the power of peptide knowledge base and raised the prediction accuracy to a new high. The method we developed in this paper could have a profound effect on the general use of knowledge base techniques for various predictionalgorithms. AVAILABILITY: The Linux executable file of HYPROSP II, as well as both nrDSSP and EVA datasets can be downloaded from http://bioinformatics.iis.sinica.edu.tw/HYPROSPII/.

Algorithms↗
PubMed2007

Achieving 80% ten-fold cross-validated accuracy for secondary structure prediction by large-scale training.

An integrated system of neural networks, called SPINE, is established and optimized for predicting structural properties of proteins. SPINE is applied to three-state secondary-structure and residue-solvent-accessibility (RSA) prediction in this paper. The integrated neural networks are carefully trained with a large dataset of 2640 chains, sequence profiles generated from multiple sequence alignment, representative amino acid properties, a slow learning rate, overfitting protection, and an optimized sliding-widow size. More than 200,000 weights in SPINE are optimized by maximizing the accuracy measured by Q(3) (the percentage of correctly classified residues). SPINE yields a 10-fold cross-validated accuracy of 79.5% (80.0% for chains of length between 50 and 300) in secondary-structure prediction after one-month (CPU time) training on 22 processors. An accuracy of 87.5% is achieved for exposed residues (RSA >95%). The latter approaches the theoretical upper limit of 88-90% accuracy in assigning secondary structures. An accuracy of 73% for three-state solvent-accessibility prediction (25%/75% cutoff) and 79.3% for two-state prediction (25% cutoff) is also obtained.

Algorithms↗
PubMed2005

HotKnots: heuristic prediction of RNA secondary structures including pseudoknots.

We present HotKnots, a new heuristic algorithm for the prediction of RNA secondary structures including pseudoknots. Based on the simple idea of iteratively forming stable stems, our algorithm explores many alternative secondary structures, using a free energy minimization algorithm for pseudoknot free secondary structures to identify promising candidate stems. In an empirical evaluation of the algorithm with 43 sequences taken from the Pseudobase database and from the literature on pseudoknotted structures, we found that overall, in terms of the sensitivity and specificity of predictions, HotKnots outperforms the well-known Pseudoknots algorithm of Rivas and Eddy and the NUPACK algorithm of Dirks and Pierce, both based on dynamic programming approaches for limited classes of pseudoknotted structures. It also outperforms the heuristic Iterated Loop Matching algorithm of Ruan and colleagues, and in many cases gives better results than the genetic algorithm from the STAR package of van Batenburg and colleagues and the recent pknotsRG-mfe algorithm of Reeder and Giegerich. The HotKnots algorithm has been implemented in C/C++ and is available from http://www.cs.ubc.ca/labs/beta/Software/HotKnots.

Algorithms↗
PubMed1993

Effects of relative band intensity on prediction of protein secondary structure from CD.

Increasing the magnitude of a protein CD spectrum obviously increases the magnitude of each predicted secondary structure by the same amount. However, increasing the magnitude of the negative, long-wave-length portion of a protein CD spectrum usually has the opposite effect from increasing the positive, short-wave-length portion. Thus small distortions in the CD spectra of proteins at short wavelength can have a significant effect on the analysis for secondary structure. This measurement error and its effect on the analysis are systematically investigated for 16 proteins of known structure. The results demonstrate that a two-point calibration of a CD instrument is mandatory to avoid serious errors when estimating secondary structure from protein CD spectra.

Calibration↗
PubMed2005

An efficient algorithm to compute the landscape of locally optimal RNA secondary structures with respect to the Nussinov-Jacobson energy model.

We make a novel contribution to the theory of biopolymer folding, by developing an efficient algorithm to compute the number of locally optimal secondary structures of an RNA molecule, with respect to the Nussinov-Jacobson energy model. Additionally, we apply our algorithm to analyze the folding landscape of selenocysteine insertion sequence (SECIS) elements from A. Bock (personal communication), hammerhead ribozymes from Rfam (Griffiths-Jones et al., 2003), and tRNAs from Sprinzl's database (Sprinzl et al., 1998). It had previously been reported that tRNA has lower minimum free energy than random RNA of the same compositional frequency (Clote et al., 2003; Rivas and Eddy, 2000), although the situation is less clear for mRNA (Seffens and Digby, 1999; Workman and Krogh, 1999; Cohen and Skienna, 2002),(1) which plays no structural role. Applications of our algorithm extend knowledge of the energy landscape differences between naturally occurring and random RNA. Given an RNA molecule a(1), ... , a(n) and an integer k > or = 0, a k-locally optimal secondary structure S is a secondary structure on a(1), ... , a(n) which has k fewer base pairs than the maximum possible number, yet for which no basepairs can be added without violation of the definition of secondary structure (e.g., introducing a pseudoknot). Despite the fact that the number numStr(k) of k-locally optimal structures for a given RNA molecule in general is exponential in n, we present an algorithm running in time O(n (4)) and space O(n (3)), which computes numStr(k) for each k. Structurally important RNA, such as SECIS elements, hammerhead ribozymes, and tRNA, all have a markedly smaller number of k-locally optimal structures than that of random RNA of the same dinucleotide frequency, for small and moderate values of k. This suggests a potential future role of our algorithm as a tool to detect noncoding RNA genes.

Algorithms↗
PubMed2005

Potential structure/function relationships of predicted secondary structural elements of tau.

The microtubule-associated protein tau is believed to be a natively unfolded molecule with virtually no secondary structure. However, this protein self-associates into filamentous forms in various neurodegenerative diseases. Since these filamentous forms show a remarkable degree of higher order due to their regular widths and periodicity, it is widely speculated that tau does contain secondary structures that come together to form tertiary and quaternary structures in the filamentous form. The purpose of this review is to use the primary sequence of tau along with predictive methods in an effort to identify potential secondary structural elements that could be involved in its normal and pathological functions. Although there are few predicted structural elements in the tau molecule, these analyses should lead to a better understanding of the structure/function relationships that regulate the behavior of tau.

Amino Acid Sequence↗
PubMedDate not supplied

[Correlation between the effectiveness of translation initiation and secondary structure of mRNA in the hybrid gene cro-lacIZ].

A set of plasmids containing short DNA deletions in the N-part of cro-lacIZ coding zone as constructed using Bal31 nuclease. Development of models of mRNA secondary structure was carried out stepwise beginning from the 5'-end by taking into consideration the hairpins first formed during mRNA synthesis. Comparison of the results of mRNA secondary structure determination and protein production analysis demonstrated a correlation between the efficiency of translation initiation and the appearance of a single-stranded region upon disruption of the mRNA local secondary structure in the translation initiation zone generated by ribosomes. These results confirm the suggestion of the central role played by the Shine-Dalgarno sequence in the generation of a single-stranded region. Some plasmids from the set are supposed to determine protein synthesis by a translation reinitiation mechanism in the absence of Shine--Dalgarno interaction. In this case, correlation between reinitiation efficiency and local disruption of the mRNA secondary structure by the terminating ribosome was also observed. The terminating ribosome that forms the single-stranded region near the initiation codon fulfils the major function of the Shine--Dalgarno interaction. In addition, the possible effect of another mRNA secondary structure region on the translation initiation efficiency is discussed.

Escherichia coli↗
PubMed1997

A correlation between computer-predicted changes in secondary structure and the phenotype of retinal degeneration associated with mutations in peripherin/RDS.

PURPOSE: To investigate a molecular understanding of how mutations can lead to different phenotypes, we analyzed the relationship between altered secondary structures predicted by missense mutations in the peripherin/RDS and clinical severity of autosomal-dominant retinal degeneration. METHODS: We analyzed thirteen different kinds of missense mutations in the second intradiscal loop of peripherin/RDS, previously reported in peer review journals. Alteration of the secondary structure of peripherin/RDS was predicted by computer-assisted protein structure analysis. The number of amino acid residues that would be involved in the secondary structural change produced by a given missense mutation was scored as a grade of molecular change. Clinical severity was estimated by the impairment based on electroretinographic recordings of rods and cones, and was scored according to the severity of their recordings. Regression analysis was carried out between both scores of molecular change and clinical severity. Effects of patients' ages on clinical severity was also analyzed. RESULTS: Significant correlation was found between scores of molecular change and those of clinical severity (rods, r = 0.89, p < 0.001; cones, r = 0.76, p < 0.005) by regression analysis. There was no correlation between clinical severity and patients' ages. CONCLUSION: . These findings indicate that the degree of change in the secondary structure of peripherin/RDS can explain in part the correlation between genotype and phenotype in autosomal-dominant retinal degeneration associated with missense mutations in the peripherin/RDS gene.

Adult↗