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Designed molecules that fold to mimic protein secondary structures.

Molecules that fold to mimic protein secondary structures have emerged as important targets of bioorganic chemistry. Recently, a variety of compounds that mimic helices, turns, and sheets have been developed, with notable advances in the design of beta-peptides that mimic each of these structures. These compounds hold promise as a step toward synthetic molecules with protein-like properties and as drugs that block protein-protein interactions.

Carbohydrate Sequence↗

Effect of cyclodextrin on the activity and secondary structure of horseradish peroxidase.

The activity and secondary structure of horseradish peroxidase (HRP) was studied in aqueous solution containing alpha-, beta- and gamma-cyclodextrin (CD). The results showed that the activity of HRP was enhanced to different extents by the three kinds of CD. A Fourier Transform infrared (FTIR) spectroscopy study indicated that the amount of alpha-helical structure was important for the activity of HRP. This phenomenon is discussed.

Circular Dichroism↗

An algorithm for protein secondary structure prediction based on class prediction.

An algorithm has been developed to improve the success rate in the prediction of the secondary structure of proteins by taking into account the predicted class of the proteins. This method has been called the 'double prediction method' and consists of a first prediction of the secondary structure from a new algorithm which uses parameters of the type described by Chou and Fasman, and the prediction of the class of the proteins from their amino acid composition. These two independent predictions allow one to optimize the parameters calculated over the secondary structure database to provide the final prediction of secondary structure. This method has been tested on 59 proteins in the database (i.e. 10,322 residues) and yields 72% success in class prediction, 61.3% of residues correctly predicted for three states (helix, sheet and coil) and a good agreement between observed and predicted contents in secondary structure.

Algorithms↗

Prediction of surface and interior regions in proteins--Part II: Predicting secondary structure in regions bound by surface exposed regions.

A new secondary structure prediction algorithm (SecondaryPlot) is described and has been developed for the IBM or compatible computer. This algorithm successfully predicts the boundaries of secondary structural regions by combining hydrophilicity, accessibility and flexibility parameters. Within the limits of these predicted structural regions, five algorithms (Chou and Fasman; Garnier, Osguthorpe and Robson; Delange and Roux; Barkovsky and Bandarin; and Lim) were used to predict helix and sheet regions. All of the algorithms correctly predicted 50-60% of the x-ray defined regions. Predictions were improved by combining the two most successful algorithms of Lim and Chou and Fasman. By combining the boundary predictions (hydrophilicity, accessibility, flexibility and linear polar tripeptide sequences) with secondary structure predictions (Lim, Chou and Fasman), approximately 80% of the x-ray defined structural regions were predicted correctly for 30 proteins (86% for the alpha-class, 79% for the beta-class and 82% for the alpha/beta class of proteins). In our hands, the best of the five algorithms studied to predict the state (helix or sheet) of these structural regions predicted 62% of helical regions and 64% of extended regions in a test set of fifteen proteins. However, SecondaryPlot predicted 78% of helical regions and 71% of extended regions for the same test. SecondaryPlot provides a significant improvement to structure prediction and is a necessary first step in the tertiary structure prediction of proteins.

Algorithms↗

Prediction of protein secondary structure and active sites using the alignment of homologous sequences.

The prediction of protein secondary structure (alpha-helices, beta-sheets and coil) is improved by 9% to 66% using the information available from a family of homologous sequences. The approach is based both on averaging the Garnier et al. (1978) secondary structure propensities for aligned residues and on the observation that insertions and high sequence variability tend to occur in loop regions between secondary structures. Accordingly, an algorithm first aligns a family of sequences and a value for the extent of sequence conservation at each position is obtained. This value modifies a Garnier et al. prediction on the averaged sequence to yield the improved prediction. In addition, from the sequence conservation and the predicted secondary structure, many active site regions of enzymes can be located (26 out of 43) with limited over-prediction (8 extra). The entire algorithm is fully automatic and is applicable to all structural classes of globular proteins.

Algorithms↗

An improved secondary structure computation method and its application to intervening sequence in the human alpha-like globin mRNA precursors.

Current secondary structure prediction computations have a serious drawback. The calculated thermodynamically most stable structure often differs from that observed in solution or in crystal form. In this paper we suggest a way to partially over-come some of these limitations by simulating the RNA folding process and calculating the frequencies of occurrence of the various substructures obtained. The frequently recurring substructures are then selected to construct the secondary structure of the whole RNA. 142 tRNA molecules and an E. coli 16S rRNA molecule have been examined by this method. The percentage of successful prediction of the correct helices are significantly higher than those calculated previously. The secondary structures of intervening sequences (IVSs) excised from human alpha-like globin pre-mRNAs are also computed. Thus, in this method the secondary structures obtained are composed of the statistically more significant substructures. This has also been demonstrated by using randomly shuffled sequences. The secondary structures of each of the randomized sequences are computed and their mean and standard deviations are used in evaluating the significance of the substructures obtained in the folding of the biological sequence. Some potentially appealing structural features aligning adjacent exons for ligation have been found.

Base Sequence↗

Exploring the limits of nearest neighbour secondary structure prediction.

This paper presents a simple and robust secondary structure prediction scheme (SIMPA96) based on an updated version of the nearest neighbour method. Using a larger database of known structures, the Blosum 62 substitution matrix and a regularization algorithm, the three state prediction accuracy is increased by 4.7 percentage points to 67.7% for a single sequence and up to 72.8% when using multiple alignments. The increase in prediction accuracy with respect to the previous version can be almost entirely ascribed to the sevenfold increase in the size of the database. A more detailed analysis of the results shows that badly predicted regions of a protein sequence are randomly distributed throughout the database and that the goal of perfect secondary structure predictions by methods which use only local sequence information is illusory.

Algorithms↗

Comparison of P-RnaPredict and mfold--algorithms for RNA secondary structure prediction.

MOTIVATION: Ribonucleic acid is vital in numerous stages of protein synthesis; it also possesses important functional and structural roles within the cell. The function of an RNA molecule within a particular organic system is principally determined by its structure. The current physical methods available for structure determination are time-consuming and expensive. Hence, computational methods for structure prediction are sought after. The energies involved by the formation of secondary structure elements are significantly greater than those of tertiary elements. Therefore, RNA structure prediction focuses on secondary structure. RESULTS: We present P-RnaPredict, a parallel evolutionary algorithm for RNA secondary structure prediction. The speedup provided by parallelization is investigated with five sequences, and a dramatic improvement in speedup is demonstrated, especially with longer sequences. An evaluation of the performance of P-RnaPredict in terms of prediction accuracy is made through comparison with 10 individual known structures from 3 RNA classes (5S rRNA, Group I intron 16S rRNA and 16S rRNA) and the mfold dynamic programming algorithm. P-RnaPredict is able to predict structures with higher true positive base pair counts and lower false positives than mfold on certain sequences. AVAILABILITY: P-RnaPredict is available for non-commercial usage. Interested parties should contact Kay C. Wiese (wiese@cs.sfu.ca).

Algorithms↗

Predicting RNA secondary structures with arbitrary pseudoknots by maximizing the number of stacking pairs.

The paper investigates the computational problem of predicting RNA secondary structures. The general belief is that allowing pseudoknots makes the problem hard. Existing polynomial-time algorithms are heuristic algorithms with no performance guarantee and can handle only limited types of pseudoknots. In this paper, we initiate the study of predicting RNA secondary structures with a maximum number of stacking pairs while allowing arbitrary pseudoknots. We obtain two approximation algorithms with worst-case approximation ratios of 1/2 and 1/3 for planar and general secondary structures, respectively. For an RNA sequence of n bases, the approximation algorithm for planar secondary structures runs in O(n(3)) time while that for the general case runs in linear time. Furthermore, we prove that allowing pseudoknots makes it NP-hard to maximize the number of stacking pairs in a planar secondary structure. This result is in contrast with the recent NP-hard results on psuedoknots which are based on optimizing some general and complicated energy functions.

Algorithms↗

Characterization of secondary structure of neocarzinostatin apoprotein.

Characteristics of the secondary structure of neocarzinostatin apoprotein (apo-NCS) were examined by various means. Gaussian analysis of the Fourier-transform infrared (FT-IR) curve and curve-fitting of the circular dichroism (CD) spectrum for apo-NCS revealed that this peptide was abundant in beta-structures. In the presence of sodium dodecyl sulfate (SDS), the CD bands of NCS originating from phenylalanyl, tyrosyl, and cystinyl residues decreased, indicating a conformational change around the chromophore (CNS-chr). On the other hand, apo-NCS, in the SDS system, showed no change of these bands. We showed that the major parts of the protein moiety consist of beta-structures by measurements of the FT-IR and CD spectra of apo-NCS and a prediction of the secondary structure based on the amino acid sequence of the peptide. It seems that properties of the protein may be important to the hydrophobic interaction between NCS-chr and apo-NCS.

Amino Acid Sequence↗

Evaluation of the secondary structure of vaccinia-virus thymidine kinase by circular-dichroism spectroscopy of overlapping synthetic peptides.

A new approach is reported that includes multiple-peptide synthesis and CD spectroscopy of overlapping peptides to evaluate the secondary structure of the vaccinia-virus thymidine kinase (TK). We divided the sequence of the vaccinia-virus TK into 82 peptides of 15 residues that overlapped by 13 residues and covered the complete sequence of vaccinia-virus TK. All peptides were synthesized by solid-phase multiple-peptide synthesis by means of the Fmoc/tert-butyl strategy. Subsequently, the secondary structure of each peptide was studied by means of CD spectroscopy in a mixture of 30% trifluoroethanol and sodium phosphate, pH 7. Secondary-structure evaluation led to determination of a vaccinia-virus-TK secondary-structure pattern. Consecutive peptides with alpha-helical content mainly showed CD spectra with increasing and decreasing Cotton effects typical of alpha-helices. This phenomenon was used to localize the helices on the sequence. In contrast, only single CD spectra with clear beta-sheet conformation, or CD spectra of mixed secondary-structure content were observed for beta-sheets. Therefore, the exact localization of beta-sheet-containing residues was deduced by comparison with isofunctional sequence-dissimilar proteins. We identified seven alpha-helices and six beta-sheet-containing regions, which we used for a secondary-structure model of the vaccinia-virus TK protein.

Amino Acid Sequence↗

Determination of secondary structure in rabbit globin messenger RNA by thermal denaturation.

The secondary structure of highly purified globin messenger RNA has been investigated by alkaline hydrolysis, nuclease digestion, and thermal denaturation. The thermal denaturation properties of globin messenger have been compared to poly(U), poly (A), and a synthetic random sequence RNA copolymer. From these studies it is concluded that globin mRNA contains considerable secondary structure and that the amount of helical structure is greater than that which occurs with a random sequence polyribonucleotide. Globin mRNA contains, by comparison to the secondary structures of native DNA, tRNAs, or 18S rRNA, helices with involve 55-62% of the bases or 58-68% if a correction is made for the 3'-terminal poly(A) segment. The helices of globin mRNA appear to be unique as differences in the NaCl stabilization of this RNA have been noted when compared to other naturally ooccurring and synthetic RNAs. Comparison of the hyperchromicity maxima, obtained at 260 and 280 nm for globin mRNA and 18S rRNA, indicates that the helices of the two RNAs contain similar numbers of G-C base pairs. Differential analysis of NaCl stabilization curves indicate three discrete thermally denaturable helix types in globin mRNA.

Animals↗

Effect of PbII on the secondary structure and biological activity of trypsin.

The effects of Pb(II) on the secondary structure and biological activity of trypsin have been examined by monitoring changes in its conductivity and IR and circular dichroism (CD) spectra. The results show that Pb(II) reacts with trypsin, and that the binding sites might be -OH and -NH groups in pepsin. The CD spectra indicate that interaction with Pb(II) significantly affects the secondary structure of trypsin, the beta-sheet-structure content being increased by about 42%, whilst those of alpha-helix and beta-turn structures are decreased by 13% and 21%, respectively. The results clearly demonstrate that Pb(II) affects the biological activity of trypsin by modifying its secondary structure. Most interesting is that Pb(II) up-regulates the activity of trypsin at low concentrations while down-regulating it at high concentrations.

Binding Sites↗

Secondary structure of human interleukin-3.

1. The secondary structure of human interleuken-3 in solution was determined by circular dichroism spectroscopy. 2. The results were then compared with empirical secondary structure predictions based on primary sequence structure of the protein. 3. The two approaches are in extremently close agreement showing the protein to have 40% alpha-helix, 12% total beta-structure and 48% random coil content.

Amino Acid Sequence↗

Application of multiple sequence alignment profiles to improve protein secondary structure prediction.

The effect of training a neural network secondary structure prediction algorithm with different types of multiple sequence alignment profiles derived from the same sequences, is shown to provide a range of accuracy from 70.5% to 76.4%. The best accuracy of 76.4% (standard deviation 8.4%), is 3.1% (Q(3)) and 4.4% (SOV2) better than the PHD algorithm run on the same set of 406 sequence non-redundant proteins that were not used to train either method. Residues predicted by the new method with a confidence value of 5 or greater, have an average Q(3) accuracy of 84%, and cover 68% of the residues. Relative solvent accessibility based on a two state model, for 25, 5, and 0% accessibility are predicted at 76.2, 79.8, and 86. 6% accuracy respectively. The source of the improvements obtained from training with different representations of the same alignment data are described in detail. The new Jnet prediction method resulting from this study is available in the Jpred secondary structure prediction server, and as a stand-alone computer program from: http://barton.ebi.ac.uk/. Proteins 2000;40:502-511.

Algorithms↗

RNA secondary structure prediction based on free energy and phylogenetic analysis.

We describe a computational method for the prediction of RNA secondary structure that uses a combination of free energy and comparative sequence analysis strategies. Using a homology-based sequence alignment as a starting point, all favorable pairings with respect to the Turner energy function are identified. Each potentially paired region within a multiple sequence alignment is scored using a function that combines both predicted free energy and sequence covariation with optimized weightings. High scoring regions are ranked and sequentially incorporated to define a growing secondary structure. Using a single set of optimized parameters, it is possible to accurately predict the foldings of several test RNAs defined previously by extensive phylogenetic and experimental data (including tRNA, 5 S rRNA, SRP RNA, tmRNA, and 16 S rRNA). The algorithm correctly predicts approximately 80% of the secondary structure. A range of parameters have been tested to define the minimal sequence information content required to accurately predict secondary structure and to assess the importance of individual terms in the prediction scheme. This analysis indicates that prediction accuracy most strongly depends upon covariational information and only weakly on the energetic terms. However, relatively few sequences prove sufficient to provide the covariational information required for an accurate prediction. Secondary structures can be accurately defined by alignments with as few as five sequences and predictions improve only moderately with the inclusion of additional sequences.

Algorithms↗

Effect of RNA secondary structure on the kinetics of DNA synthesis catalyzed by HIV-1 reverse transcriptase.

The effect of RNA secondary structure on the kinetics of DNA synthesis catalyzed by HIV-1 RT was determined using a 66 nucleotide RNA template containing a stable 12 base pair hairpin structure. Prior to reaching the hairpin structure, the primer elongation by RT was fast and the kinetics of polymerization was not affected by the presence of the secondary structure. Once within the regions of template secondary structure, polymerization was much slower and RT paused at five distinct sites [Suo, Z., & Johnson, K. A. (1997) Biochemistry (manuscript submitted for publication)]. Kinetic analysis of single nucleotide incorporation at the pause sites showed polymerization occurred by both a fast phase (54-76 s-1) and a slow phase (0.07-0.4 s-1) during a single binding event. The biphasic kinetics suggests that the DNA substrates are initially bound in both productive and nonproductive states at the polymerase site of RT. The nonproductively bound DNA is slowly converted into a productive state without dissociation from the enzyme. At the pause sites, the enzyme amplitudes of the fast phase are small (4.0-15%) while the amplitudes of the slow phase are large (11-40%). In contrast, only the reaction at the fast phase was observed at the nonpause sites and the enzyme amplitudes were large (63-66%) although the nucleotide incorporation rates (62-78 s-1) are similar to the fast phase rates at the pause sites. These indicate that DNA substrates were bound predominantly nonproductively at pause sites and productively at nonpause sites. However, the overall binding affinity of DNA substrates was measured by the nitrocellulose-DEAE double filter binding assay, binding affinity at both pause sites and nonpause sites was similar (9-38 nM). This indicates that substrates are bound tightly at the large binding cleft of HIV-1, although they may not be productively bound at the polymerase active site. These results and those reported elsewhere [Suo, Z., & Johnson, K. A. (1997) Biochemistry (manuscript submitted for publication)] are consistent with a model in which, at pause sites, HIV-1 RT remains bound to DNA substrates waiting for the melting of the next stem base pair of template secondary structure. Upon melting of the stem base pair, polymerization to fill the open template site is fast and largely irreversible, allowing RT to read through the stable hairpin structures.

Base Sequence↗

An interactive technique for the display of nucleic acid secondary structure.

The ability to visualize nucleic acid secondary structure has become quite important since the advent of computer prediction and biochemical techniques that depict such structures. Manually drawing the conformations can be quite time consuming and tedious. Thus, the ability to draw with the aid of a computer the secondary structure of nucleic acid molecules is quite advantageous. This paper describes an interactive algorithm that permits one to generate such drawings which may then be used for further analysis and/or publications.

Animals↗