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PubMed2003

Q9, a content-balancing accuracy index to evaluate algorithms of protein secondary structure prediction.

A content-balancing accuracy index, called Q(9), has been proposed to evaluate algorithms of protein secondary structure prediction. Here the content-balancing means that the evaluation is independent of the contents of helix, strand and coil in the protein being predicted. It is shown that Q(9) is much superior to the widely used index Q(3). Therefore, algorithms are more objectively evaluated by Q(9) than Q(3). Based on 396 non-homologous proteins, five algorithms of secondary structure prediction were evaluated and compared by the new index Q(9). Of the five algorithms, PHD turned out to be the unique algorithm with an average Q(9) better than 60%. Based on the new index, it is shown that the performance of the consensus method based on a jury-decision from several algorithms is even worse than that of the best individual method. Rather than Q(3), we believe that Q(9) should be used to evaluate algorithms of protein secondary structure prediction in future studies in order to improve prediction quality.

Algorithms↗
PubMed1996

Chemical shift assignments and secondary structure of the Grb2 SH2 domain by heteronuclear NMR spectroscopy.

The growth factor receptor-bound protein-2 (Grb-2) is an adaptor protein that mediates signal transduction pathways. Chemical shift assignments were obtained for the SH2 domain of Grb2 by heteronuclear NMR spectroscopy, employing the uniformly 13C-/15N-enriched protein as well as the protein containing selectively 15N-enriched amino acids. Using the Chemical Shift Index (CSI) method, the chemical shift indices of four nuclei, 1H alpha, 13C alpha, 13C beta and 13CO, were used to derive the secondary structure of the protein. Nuclear Overhauser enhancements (NOEs) were then employed to confirm the secondary structure. The CSI results were compared to the secondary structural elements predicted for the Grb2 SH2 domain from a sequence alignment [Lee et al. (1994) Structure, 2, 423-438]. The core structure of the SH2 domain contains an antiparallel beta-sheet and two alpha-helices. In general, the secondary structural elements determined from the CSI method agree well with those predicted from the sequence alignment.

Adaptor Proteins, Signal Transducing↗
PubMed1996

Secondary structure of the yeast Saccharomyces cerevisiae pre-U3A snoRNA and its implication for splicing efficiency.

The Saccharomyces cerevisiae U3 snoRNA genes contain long spliceosomal introns with noncanonical branch site sequences. By using chemical and enzymatic methods to probe the RNA secondary structure and site-directed mutagenesis, we established the complete secondary structure of the U3A snoRNA precursor. This is the first determination of the complete secondary structure of an RNA spliced in a spliceosome. The peculiar cruciform structure of the U3A snoRNA 3'-terminal region is formed in the precursor RNA and the conserved Boxes B and C are accessible for binding the U3 snoRNP proteins. The intron forms a highly folded structure with a long central stem-loop structure that brings the 5' box and the branch site together. This is in agreement with the idea that secondary structure interactions are necessary for efficient splicing of long introns in yeast. The 3' splice site is in a bulged loop and the branch site sequence is single-stranded. Surprisingly, the 5' splice site is involved in a 6-base pair interaction. We used in vitro splicing experiments to show that, despite a noncanonical branch site sequence and a base paired 5' splice site, transcripts that mimic the authentic pre-U3A snoRNA are spliced very efficiently in vitro. Sequestering the 5' splice site in a more stable structure had a negative effect on splicing, which was partially compensated by converting the branch site sequence into a canonical sequence. Analysis of spliceosomal complex formation revealed a cumulative negative effect of a base pair interaction at the 5' splice site and of a deviation to the consensus sequence at the branch site on the efficiency of spliceosome formation in vitro.

Base Composition↗
PubMed1994

Induction of secondary structure in the peptide hormone motilin by interaction with phospholipid vesicles.

Motilin is an intestinal peptide hormone that binds to a membrane bound receptor located in the gut tissue. Circular dichroism (CD) was used to study the interaction between either porcine or rabbit motilin or a 1-16 fragment of porcine motilin, with model systems of lipid membranes: sodium dodecyl sulphate (SDS), 1,2-dioleoyl-sn-glycero-3-phosphoglycerol (DOPG) and 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC). The CD measurements show significant induction of secondary structure in both motilins and the fragment when negatively charged vesicles (DOPG) or negatively charged micelles (SDS) were present. In contrast, neutral DOPC vesicles did not induce any change in the secondary structure compared to water, in which a random-like secondary structure dominates. The induced secondary structure in the presence of DOPG vesicles is very close to that induced by a mixed aqueous solution containing 30% hexafluoroisopropanol, in which previous NMR-studies have resulted in a three-dimensional solution structure of porcine motilin. In both porcine and rabbit motilin the alpha-helix content is about 50%. This is in agreement with the presence of an amphipathic helix in the C-terminal half of motilin interacting with phospholipid membranes. The interaction appears to be mainly electrostatic in nature, and does not induce any significant alterations in the vesicle, as monitored by EPR studies of spin labels located at the fifth carbon atom of the backbone in a stearic acid molecule. In the 1-16 fragment the alpha-helical content induced by DOPG and SDS is only about 20%.

Amino Acid Sequence↗
PubMed1999

Mean free energy topology for nucleotide sequences of varying composition based on secondary structure calculations.

The mean free energy generated from the secondary structure of RNA sequences of varying length and composition has been studied by way of probability theory. The expected boundaries or maximal and minimal values of a given distribution are explored and a method for estimating error as a function of the number of shuffled sequences is also examined. For typical nucleotide sequences found in biologically active organisms, the mean free energy, free energy distributions and errors appear to be scalable in terms of a fixed set of algorithm-dependent parameters and the nucleotide composition of the particular sequence under evaluation. In addition, a general semi-analytical formula for predicting the mean free energy is proposed which, at least to first-order approximation, can be used to rapidly predict the mean free energy of any sequence length and composition of RNA. The general methodology appears to be algorithm independent. The results are expected to provide a reference point for certain types of analysis related to structure of RNA or DNA sequences and to assist in measuring the somewhat related matter of complexity in algorithm development. Some related applications are discussed.

Algorithms↗
PubMed2004

Using artificially generated spectral data to improve protein secondary structure prediction from Fourier transform infrared spectra of proteins.

Secondary structures of proteins have been predicted using neural networks from their Fourier transform infrared spectra. To improve the generalization ability of the neural networks, the training data set has been artificially increased by linear interpolation. The leave-one-out approach has been used to demonstrate the applicability of the method. Bayesian regularization has been used to train the neural networks and the predictions have been further improved by the maximum-likelihood estimation method. The networks have been tested and standard error of prediction (SEP) of 4.19% for alpha helix, 3.49% for beta sheet, and 3.15% for turns have been achieved. The results indicate that there is a significant decrease in the SEP for each type of structure parameter compared to previous works.

Algorithms↗
PubMed2003

A pentapeptide-based method for protein secondary structure prediction.

We present a new method for protein secondary structure prediction, based on the recognition of well-defined pentapeptides, in a large databank. Using a databank of 635 protein chains, we obtained a success rate of 68.6%. We show that progress is achieved when the databank is enlarged, when the 20 amino acids are adequately grouped in 10 sets and when more pentapeptides are attributed one of the defined conformations, alpha-helices or beta-strands. The analysis of the model indicates that the essential variable is the number of pentapeptides of well-defined structure in the database. Our model is simple, does not rely on arbitrary parameters and allows the analysis in detail of the results of each chosen hypothesis.

Databases, Protein↗
PubMed2001

Environmental features are important in determining protein secondary structure.

We have investigated amino acid features that determine secondary structure: (1) the solvent accessibility of each side chain, and (2) the interaction of each side chain with others one to four residues apart. Solvent accessibility is a simple model that distinguishes residue environment. The pairwise interactions represent a simple model of local side chain to side chain interactions. To test the importance of these features we developed an algorithm to separate alpha-helices, beta-strands, and "other" structure. Single residue and pairwise probabilities were determined for 25,141 samples from proteins with <30% homology. Combining the features of solvent accessibility with pairwise probabilities allows us to distinguish the three structures after cross validation at the 82.0% level. We gain 1.4% to 2.0% accuracy by optimizing the propensities, demonstrating that probabilities do not necessarily reflect propensities. Optimization of residue exposures, weights of all probabilities, and propensities increased accuracy to 84.0%.

Algorithms↗
PubMed1996

A Fourier transform infrared spectroscopic study of the secondary structure of myelin basic protein in reconstituted myelin.

The secondary structure of myelin basic protein (MBP) in reconstituted central nervous system myelin was studied using Fourier transform infrared (FTIR) spectroscopy. The spectra of the protein in aqueous solution and in the lipid environment were compared and notable differences were observed. It is proposed that there are significant differences in the conformation of the protein in the contrasting environments. Significant increases in both alpha-helical structure and beta-structure were observed on reconstitution in myelin. The findings of this study also support the view that the presence of both alpha-helices and beta-structure plays a important role in membrane proteins.

Amino Acid Sequence↗
PubMed1996

An object programming based environment for protein secondary structure prediction.

The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.

Amino Acid Sequence↗
PubMed1995

An APL-programmed genetic algorithm for the prediction of RNA secondary structure.

The possibilities of using a genetic algorithm for the prediction of RNA secondary structure were investigated. The algorithm, using the procedure of stepwise selection of the most fit structures (similarly to natural evolution), allows different models of fitness or driving forces determining RNA structure to be easily introduced. This can be used for simulation of the RNA folding process and for the investigation of possible folding pathways. Such an algorithm needs several modifications before it can predict RNA secondary structures. After modification, a fair number of correct stems are predicted, even when using computationally quick, but very crude, fitness criteria such as stem length and stacking energy, including elements of tertiary structure (pseudoknots). The fact that genetic algorithm simulation includes both stem formations and stem disruption allows one to observe intermediate structures that may be used in combination with phylogenetic or experimental research.

Algorithms↗
PubMed2001

Protein secondary structure: category assignment and predictability.

In the last decade, the prediction of protein secondary structure has been optimized using essentially one and the same assignment scheme known as DSSP. We present here a different scheme, which is more predictable. This scheme predicts directly the hydrogen bonds, which stabilize the secondary structures. Single sequence prediction of the new three category assignment gives an overall prediction improvement of 3.1% and 5.1% compared to the DSSP assignment and schemes where the helix category consists of alpha-helix and 3(10)-helix, respectively. These results were achieved using a standard feed-forward neural network with one hidden layer on a data set identical to the one used in earlier work.

Algorithms↗
PubMed1985

The secondary structure of mRNAs from Escherichia coli: its possible role in increasing the accuracy of translation.

A secondary structure model was proposed for mRNAs during translation (in a polysome) where the secondary structure is described by a set of small unbranched hairpins. Computer simulation experiments reveal that the number of hairpins is much greater (P less than 10(-6) in highly expressed mRNAs from E. coli as compared with the random sequences coding for the same amino acid sequence, i.e. certain synonymous codons are used in definite mRNA positions to increase the number of hairpins. No constraints on the amino acid sequence, which would affect the secondary structure of mRNAs, were found. The codons UGU, UGC (Cys), GCC (Ala), ACA, ACG (Thr), CCU, CCC (Pro), etc. translated by minor tRNAs were found to occur significantly more frequently in the position 5' to the hairpins than the other codons translated by major tRNAs (P less than 5.10(-6). This correlation leads to the hypothesis that the process of hairpin unfolding can increase the time of translocation from the A to P ribosome site of the codon 5' to the hairpin, thus decreasing the probability of translational error (the latter would likely occur more frequently in the codons translated by minor tRNAs).

Base Sequence↗
PubMed2004

Effects of unpaired nucleotides within HIV-1 genomic secondary structures on pausing and strand transfer.

Reverse transcriptase-mediated RNA displacement synthesis is required for DNA polymerization through the base-paired stem portions of secondary structures present in retroviral genomes. These regions of RNA duplex often possess single unpaired nucleotides, or "bulges," that disrupt contiguous base pairing. By using well defined secondary structures from the human immunodeficiency virus, type 1 (HIV-1), genome, we demonstrate that removal of these bulges either by deletion or by introducing a complementary base on the opposing strand results in increased pausing at specific positions within the RNA duplex. We also show that the HIV-1 nucleocapsid protein can increase synthesis through the pause sites but not as efficiently as when a bulge residue is present. Finally, we demonstrate that removing a bulge increases the proportion of strand transfer events to an acceptor template that occur prior to complete replication of a donor template secondary structure. Together our data suggest a role for bulge nucleotides in enhancing synthesis through stable secondary structures and reducing strand transfer.

Base Sequence↗
PubMed1992

Generation of a substructure library for the description and classification of protein secondary structure. II. Application to spectra-structure correlations in Fourier transform infrared spectroscopy.

Fourier transform infrared spectroscopy has become well known as a sensitive and informative tool for studying secondary structure in proteins. Present analysis of the conformation-sensitive amide I region in protein infrared spectra, when combined with band narrowing techniques, provides more information concerning protein secondary structure than can be meaningfully interpreted. This is due in part to limited models for secondary structure. Using the algorithm described in the previous paper of this series, we have generated a library of substructures for several trypsin-like serine proteases. This library was used as a basis for spectra-structure correlations with infrared spectra in the amide I' region, for five homologous proteins for which spectra were collected. Use of the substructure library has allowed correlations not previously possible with template-based methods of protein conformational analysis.

Algorithms↗
PubMed2005

Protein secondary structure prediction with dihedral angles.

We present DESTRUCT, a new method of protein secondary structure prediction, which achieves a three-state accuracy (Q3) of 79.4% in a cross-validated trial on a nonredundant set of 513 proteins. An iterative set of cascade-correlation neural networks is used to predict both secondary structure and psi dihedral angles, with predicted values enhancing the subsequent iteration. Predictive accuracies of 80.7% and 81.7% are achieved on the CASP4 and CASP5 targets, respectively. Our approach is significantly more accurate than other contemporary methods, due to feedback and a novel combination of structural representations.

Amino Acid Sequence↗
PubMed1998

Assessing the impact of secondary structure and solvent accessibility on protein evolution.

Empirically derived models of amino acid replacement are employed to study the association between various physical features of proteins and evolution. The strengths of these associations are statistically evaluated by applying the models of protein evolution to 11 diverse sets of protein sequences. Parametric bootstrap tests indicate that the solvent accessibility status of a site has a particularly strong association with the process of amino acid replacement that it experiences. Significant association between secondary structure environment and the amino acid replacement process is also observed. Careful description of the length distribution of secondary structure elements and of the organization of secondary structure and solvent accessibility along a protein did not always significantly improve the fit of the evolutionary models to the data sets that were analyzed. As indicated by the strength of the association of both solvent accessibility and secondary structure with amino acid replacement, the process of protein evolution-both above and below the species level-will not be well understood until the physical constraints that affect protein evolution are identified and characterized.

Databases, Factual↗