A method of calculating the discrete secondary structures of globular proteins

The model of formation of alpha-helices and beta-structures determined by joint action of the three elements: N-terminal, internal and C-terminal fragments are presented. Algorithm for calculation of their localization in a given amino acid sequence was constructed on the base of this model. The preference of the fragments of the amino acid sequence to a definite type of the secondary structure was estimated on the base of corresponding average values of linear discriminant functions dsk (s = alpha, beta, k = N, in, C). The latter were constructed in the previous paper on the base of the revealed significant characteristics. These integral characteristics are used for calculating the localisation of discrete secondary structures. The total prediction for 3 states (alpha, beta, c) given 71% correctly predicted residues (for 4 states alpha, beta, c, t) 62% for the training set, consisting of 72 proteins. For the control set (15 proteins) the accuracy of prediction is about 65%. The essential advantages of this method are: 1) the possibility to localize the discrete secondary structures; 2) the high accuracy of prediction of long secondary structures (for alpha-helices approximately 90%, for beta-structures approximately 80%), which is important for the determination of the protein folding. The influence of mutation on the secondary structure of proteins was investigated. The anormally high stability of the secondary structures of immunoglobulins to mutations was revealed. This probably results from the selection during evolution of such variants of amino acid sequences, which are able to provide the functional variability of antigenic determinants, but keep invariant the tertially structure of protein.     

Automatic identification of secondary structure in globular proteins

A computer program is used to analyse automatically and objectively the atomic co-ordinates of a large number of globular proteins in order to identify the regions of α-helix, β-sheet and reverse-turn secondary structure. Several different criteria for the assignment of secondary structure are tested for accuracy, reproducibility and efficiency. The most successful criterion, which is based on patterns of peptide hydrogen bonds, inter-C^α distances and inter-C^α torsion angles, is used to find the secondary structure of all the proteins studied. The accuracy of the derived assignments is assessed by comparing them with the secondary structure reported in the literature for each protein. The reliability of the methods is assessed by comparing the secondary structures derived from the independently determined sets of co-ordinates available for some proteins.We provide the first objective and consistent compilation of α-helix, β-sheet and reverse-turn secondary structure in almost all globular proteins of known tertiary structure. These data will be invaluable for analysing the relative tendencies of different amino acids to occur in different types of secondary structure, for analysing the regularity of the secondary structure itself, and for analysing how the pieces of secondary structure fit together to form the globular tertiary structure of each protein.     

Improving the accuracy of predicting secondary structure for aligned RNA sequences

Considerable attention has been focused on predicting the secondary structure for aligned RNA sequences since it is useful not only for improving the limiting accuracy of conventional secondary structure prediction but also for finding non-coding RNAs in genomic sequences. Although there exist many algorithms of predicting secondary structure for aligned RNA sequences, further improvement of the accuracy is still awaited. In this article, toward improving the accuracy, a theoretical classification of state-of-the-art algorithms of predicting secondary structure for aligned RNA sequences is presented. The classification is based on the viewpoint of maximum expected accuracy (MEA), which has been successfully applied in various problems in bioinformatics. The classification reveals several disadvantages of the current algorithms but we propose an improvement of a previously introduced algorithm (CentroidAlifold). Finally, computational experiments strongly support the theoretical classification and indicate that the improved CentroidAlifold substantially outperforms other algorithms.     

A simple method for predicting transmembrane alpha helices with better accuracy.

The prediction of a protein's structure from its amino acid sequence has been a long-standing goal of molecular biology. In this work, a new set of conformational parameters for membrane spanning alpha helices was developed using the information from the topology of 70 membrane proteins. Based on these conformational parameters, a simple algorithm has been formulated to predict the transmembrane alpha helices in membrane proteins. A FORTRAN program has been developed which takes the amino acid sequence as input and gives the predicted transmembrane alpha-helices as output. The present method correctly identifies 295 transmembrane helical segments in 70 membrane proteins with only two overpredictions. Furthermore, this method predicts all 45 transmembrane helices in the photosynthetic reaction center, bacteriorhodopsin and cytochrome c oxidase to an 86% level of accuracy and so is better than all other methods published to date.     

Application of expert networks for predicting proteins secondary structure

The present study utilizes expert neural networks for the prediction of proteins secondary structure. We use three independent networks, one for each structure (alpha, beta and coil) as the first-level processing unit; decision upon the chosen structure for each residue is carried out by a second-level, post-processing unit, which utilizes the Chou and Fasman frequency values Falpha and Fbeta in order to strengthen and/or deplete the probability of the specific structure under investigation. The highest prediction case was 76%. Our method requires primitive computational means and a relatively small training set, while still been comparable to previous work. It is not meant to be an alternative to the determination of secondary structure by means of free energy minimization, integration of dynamic equations of motion or crystallography, which are expensive, time-consuming and complicated, but to provide additional constrains, which might be considered and incorporated into larger computing setups in order to reduce the initial search space for the above methods.     

Predicting the secondary structure of globular proteins using neural network models

We present a new method for predicting the secondary structure of globular proteins based on non-linear neural network models. Network models learn from existing protein structures how to predict the secondary structure of local sequences of amino acids. The average success rate of our method on a testing set of proteins non-homologous with the corresponding training set was 64.3% on three types of secondary structure (alpha-helix, beta-sheet, and coil), with correlation coefficients of C alpha = 0.41, C beta = 0.31 and Ccoil = 0.41. These quality indices are all higher than those of previous methods. The prediction accuracy for the first 25 residues of the N-terminal sequence was significantly better. We conclude from computational experiments on real and artificial structures that no method based solely on local information in the protein sequence is likely to produce significantly better results for non-homologous proteins. The performance of our method of homologous proteins is much better than for non-homologous proteins, but is not as good as simply assuming that homologous sequences have identical structures.     

A simple statistical method for discriminating outer membrane proteins with better accuracy

MOTIVATION: Discriminating outer membrane proteins from other folding types of globular and membrane proteins is an important task both for identifying outer membrane proteins from genomic sequences and for the successful prediction of their secondary and tertiary structures. RESULTS: We have systematically analyzed the amino acid composition of globular proteins from different structural classes and outer membrane proteins. We found that the residues, Glu, His, Ile, Cys, Gln, Asn and Ser, show a significant difference between globular and outer membrane proteins. Based on this information, we have devised a statistical method for discriminating outer membrane proteins from other globular and membrane proteins. Our approach correctly picked up the outer membrane proteins with an accuracy of 89% for the training set of 337 proteins. On the other hand, our method has correctly excluded the globular proteins at an accuracy of 79% in a non-redundant dataset of 674 proteins. Furthermore, the present method is able to correctly exclude alpha-helical membrane proteins up to an accuracy of 80%. These accuracy levels are comparable to other methods in the literature, and this is a simple method, which could be used for dissecting outer membrane proteins from genomic sequences. The influence of protein size, structural class and specific residues for discrimination is discussed.     

Influence of drying on the secondary structure of intrinsically disordered and globular proteins

Circular dichroism (CD) spectroscopy of five Arabidopsis late embryogenesis abundant (LEA) proteins constituting the plant specific families LEA_5 and LEA_6 showed that they are intrinsically disordered in solution and partially fold during drying. Structural predictions were comparable to these results for hydrated LEA_6, but not for LEA_5 proteins. FTIR spectroscopy showed that verbascose, but not sucrose, strongly affected the structure of the dry proteins. The four investigated globular proteins were only mildly affected by drying in the absence, but strongly in the presence of sugars. These data highlight the larger structural flexibility of disordered compared to globular proteins and the impact of sugars on the structure of both disordered and globular proteins during drying.     

Determination of secondary structure of globular proteins using circular dichroism spectra

A ridge regression method is presented for prediction of the secondary structure of proteins by the circular dichroism spectra (CD) from 190 to 236 nm. Eight types of the secondary structure were calculated on a microcalculator. The method is based on the X-ray data of Kabsh and Sander. The teaching rule is constructed on CD spectra of 30 proteins of all structural classes of the globular proteins (alpha, alpha/beta, alpha + beta and beta-proteins). The errors of the methods are analysed by removing each protein from the reference set and analyzing its structure in terms of the remaining proteins. Correlation coefficients and root-mean square deviations between CD and X-ray data were: 0.99 and 0.03 for alpha-helix, 0.86 and 0.02 for 3(10)-helix, 0.92 and 0.06 for antiparallel beta-sheet, 0.86 and 0.03 for parallel beta-sheet, 0.94 and 0.01 for T3 beta-turn, 0.85 and 0.02 for other beta-turn, 0.84 and 0.03 for S-bends, 0.83 and 0.04 for "random" structure.     

Computer method for predicting the secondary structure of single-stranded RNA.

We present a computer method utilizing published values for base pairing energies to compute the most energetically favorable secondary structure of an RNA from its primary nucleotide sequence. After listing all possible double-helical regions, every pair of mutally incompatible regions (whose nucleotides overlap) is examined to determine whether parts of those two regions can be combined by branch migration to form a pair of compatible new subregions which together are more stable than either of the original regions separately. These subregions are added to the list of base pairing regions which will compete to form the best overall structure. Then, a 'hyperstructure matrix' is generated, containing the unique topological relationship between every pair of regions. We have shown that the best structure can be chosen directly from this matrix, without the necessity of creating and examing every possible secondary structure. We have included the results from our solution of the 5S rRNA of the cyanobacterium Anacystis nidulans as an example of our program's capabilities.     

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

The prediction of the secondary structure content (-helix and-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. Fund 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-helix content and-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-helix content and-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.     

A simple electrostatic criterion for predicting the thermal stability of proteins

The enhancement of protein thermostability is an important issue for both basic science and biotechnology purposes. We have developed a thermostability criterion for a protein in terms of a quasi-electric dipole moment (contributed by its charged residues) defined for an electric charge distribution whose total charge is not zero. It was found that minimization of the modulus of this dipole moment increased its thermal stability, as demonstrated by surveying these values in pairs of mesostable-thermostable homologous proteins and in mutations described in the literature. The analysis of these observations provides criteria for thermostabilization of a protein, by computing its dipole profile. This profile is obtained by direct substitution of each amino acid of the sequence by either a positive, negative or neutral amino acid, followed by a recalculation of the dipole moment. As an experimental example, these criteria were applied to a beta-glucanase to enhance its thermal stability.     

Induction of changes in the secondary structure of globular proteins by a hydrophobic surface

Circular dichroism, ellipsometry and radiolabeling techniques were employed to study the induction of changes in the secondary structure of BSA, myoglobin and cytochrome C by a hydrophobic surface. The results showed that adsorbed protein molecules lose their ordered native structure in the initial stage of adsorption and the structure appears to be a random or disordered conformation. Protein molecules adsorbed in later stages adopt a more ordered secondary structure ( helix and structure). The changes of secondary structure of globular proteins induced by a hydrophobic surface can be explained by the steric interaction between adsorbed proteins as well as by hydrophobic interactions during the adsorption process. In addition, there is obviously an intermediate stage in which the protein molecules are mainly in the structure, indicating that for certain proteins, the structure may be a more stable secondary structure than helix on the hydrophobic surface. Correspondence to: S.-F. Sui     

A view of the three dimensional structure of globular proteins

A view of the three dimensional structure of globular proteins based on continuous networks of hydrogen bonds is proposed. Active sites of enzymes and ion sites are prominent and, within the networks, there are islands of hydrophobic regions giving an overall piebald effect to the appearance of the molecule. This point of view was originally suggested by the results of quantum mechanical computations on the coupling between hydrogen bonds. A formalism for the total energy of a globular protein in water is also suggested.The study of five lines of experimental evidence supports this suggestion. The analysis of the experimental X-ray data for ten globular proteins, using the NETWORK program, revealed the existence of these hydrogen bond networks; X-ray data showed that water molecules tend to occupy fixed positions relative to the protein molecule; a survey has shown that water molecules tend to occupy specific positions relative to the hydrogen bonding side chains; experimental evidence on the bulk properties of lysozyme showed that there exist tightly bound water molecules; graphics studies of the ribonucleaseA molecule demonstrated the networks and the piebald effect. This point of view is pictorially simple and, to illustrate the use of such networks, we discuss the simple ion pairs which occur as substructures within the networks.     

A study of the occurrence of regulator secondary structures in globular proteins

The distribution of regular secondary structures, viz. α-helices and β-strands, along the length of over 70 properties whose secondary structural details have been reported, has been analysed. The occurrence of these regular structures tends to be a maximum at the N- and C-termini. Our analysis suggests that both these free ends could possibly serve as nucleating centers for secondary structures and could play an important role in the folding of proteins.