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PubMed2004

Predicting protein secondary structure by a support vector machine based on a new coding scheme.

Protein structure prediction is one of the most important problems in modern computational biology. Protein secondary structure prediction is a key step in prediction of protein tertiary structure. There have emerged many methods based on machine learning techniques, such as neural networks (NN) and support vector machine (SVM) etc., to focus on the prediction of the secondary structures. In this paper, a new method was proposed based on SVM. Different from the existing methods, this method takes into account of the physical-chemical properties and structure properties of amino acids. When tested on the most popular dataset CB513, it achieved a Q(3) accuracy of 0.7844, which illustrates that it is one of the top range methods for protein of secondary structure prediction.

Algorithms↗
PubMedDate not supplied

[Study on secondary structure and properties of alpha- and gamma-forms of human thrombin].

Secondary structure and enzymatic properties of human a-thrombin and its gamma-form (obtaining during autolysis of the native enzyme) have been studied by differential scanning calorimetry (DSC) and circular dichroism (CD). According to DSC-data both alpha-thrombin and gamma-thrombin contained only one thermal transition peak at 58.5 and 53.3 degrees C, respectively. A comparison of these values suggested that gamma-form is less stable than initial a-thrombin. In contrast to that the thermogram of DIP-a-thrombin had two peaks (57.5 and 64.5 degrees C). CD spectra showed that conversion a- to gamma-thrombin influenced the secondary structure of the enzyme slightly. The study of the inhibitory effect of such polyanions as ATP and dextran sulfate (DS) upon thrombin-catalyzed cleavages of fibrinogen has shown that the growth of the negative charge of the polyanion molecule resulted in the increase of its inhibitory activity. The catalytically non-active DIP-alpha-thrombin, which retained the native anion-binding exosite 1, was shown to decrease the inhibitory power of the dextran sulfate. It was explained by competition of DS with the exosite 1 of both alpha- and DIP-alpha -thrombin. In contrast to that DIP-gamma-thrombin having exosite 1 destroyed neither competed nor influenced the anticoagulant capacity of dextran sulfate toward the native alpha-thrombin. In accordance with our data thrombin consists of two rather strong interacting domains. It was shown further that its anion-binding exosite 1 may play a significant role in the interaction of the enzyme with dextran sulfate.

Calorimetry, Differential Scanning↗
PubMed2003

GPRM: A genetic programming approach to finding common RNA secondary structure elements.

RNA molecules play an important role in many biological activities. Knowing its secondary structure can help us better understand the molecule's ability to function. The methods for RNA structure determination have traditionally been implemented through biochemical, biophysical and phylogenetic analyses. As the advance of computer technology, an increasing number of computational approaches have recently been developed. They have different goals and apply various algorithms. For example, some focus on secondary structure prediction for a single sequence; some aim at finding a global alignment of multiple sequences. Some predict the structure based on free energy minimization; some make comparative sequence analyses to determine the structure. In this paper, we describe how to correctly use GPRM, a genetic programming approach to finding common secondary structure elements in a set of unaligned coregulated or homologous RNA sequences. GPRM can be accessed at http://bioinfo.cis.nctu.edu.tw/service/gprm/.

Internet↗
PubMed1995

Comparison of and limits of accuracy for statistical analyses of vibrational and electronic circular dichroism spectra in terms of correlations to and predictions of protein secondary structure.

This work provides a systematic comparison of vibrational CD (VCD) and electronic CD (ECD) methods for spectral prediction of secondary structure. The VCD and ECD data are simplified to a small set of spectral parameters using the principal component method of factor analysis (PC/FA). Regression fits of these parameters are made to the X-ray-determined fractional components (FC) of secondary structure. Predictive capability is determined by computing structures for proteins sequentially left out of the regression. All possible combinations of PC/FA spectral parameters (coefficients) were used to form a full set of restricted multiple regressions with the FC values, both independently for each spectral data set as well as for the two VCD sets and all the data grouped together. The complete search over all possible combinations of spectral parameters for different types of spectral data is a new feature of this study, and the focus on prediction is the strength of this approach. The PC/FA method was found to be stable in detail to expansion of the training set. Coupling amide II to amide I' parameters reduced the standard deviations of the VCD regression relationships, and combining VCD and ECD data led to the best fits. Prediction results had a minimum error when dependent on relatively few spectral coefficients. Such a limited dependence on spectral variation is the key finding of this work, which has ramifications for previous studies as well as suggests future directions for spectral analysis of structure. The best ECD prediction for helix and sheet uses only one parameter, the coefficient of the first subspectrum. With VCD, the best predictions sample coefficients of both the amide I' and II bands, but error is optimized using only a few coefficients. In this respect, ECD is more accurate than VCD for alpha-helix, and the combined VCD (amide I' + II) predicts the beta-sheet component better than does ECD. Combining VCD and ECD data sets yields exceptionally good predictions by utilizing the strengths of each. However, the residual error, its distribution, and, most importantly, the lack of dependence of the method on many of the significant components derived from the spectra leads to the conclusion that the heterogeneity of protein structure is a fundamental limitation to the use of such spectral analysis methods. The underutilization of these data for prediction of secondary structure suggests spectral data could predict a more detailed descriptor.

Circular Dichroism↗
PubMed1997

Vibrational circular dichroism spectra of proteins in the amide III region: measurement and correlation of bandshape to secondary structure.

Vibrational circular dichroism (VCD) spectra have been measured for 23 globular proteins dissolved in H2O/phosphate buffer over the 1400 to 1100 cm(-1) region which encompasses the amide III mode. Spectral responses characteristic of the dominant secondary structure type were found as broad features at approximately 1300 cm(-1), with the extreme forms having positive VCD for highly helical proteins and negative VCD for highly sheet-containing proteins. Quantitative correlation with secondary structure was carried out using previously developed factor analysis and restricted multiple regression (FA/RMR) techniques. Since the absorbance intensity of the amide III mode is difficult to determine due to overlap with other transitions, an alternative, absolute intensity-independent, simple structural analysis method was used. A linear regression was developed between the fractional components of secondary structure for the protein set and the overlap integrals of the normalized spectra from the set with that of a selected protein. The results of this simple method are quite comparable to those of the FA/ RMR approach for analysis with amide III VCD. On the other hand, test calculations with the new method when used with electronic CD spectra are not as good as FA/RMR due to its more intensity-dependent relationship with secondary structure.

Circular Dichroism↗
PubMed1992

Detection of secondary structure elements in proteins by hydrophobic cluster analysis.

Hydrophobic cluster analysis (HCA) is a protein sequence comparison method based on alpha-helical representations of the sequences where the size, shape and orientation of the clusters of hydrophobic residues are primarily compared. The effectiveness of HCA has been suggested to originate from its potential ability to focus on the residues forming the hydrophobic core of globular proteins. We have addressed the robustness of the bidimensional representation used for HCA in its ability to detect the regular secondary structure elements of proteins. Various parameters have been studied such as those governing cluster size and limits, the hydrophobic residues constituting the clusters as well as the potential shift of the cluster positions with respect to the position of the regular secondary structure elements. The following results have been found to support the alpha-helical bidimensional representation used in HCA: (i) there is a positive correlation (clearly above background noise) between the hydrophobic clusters and the regular secondary structure elements in proteins; (ii) the hydrophobic clusters are centred on the regular secondary structure elements; (iii) the pitch of the helical representation which gives the best correspondence is that of an alpha-helix. The correspondence between hydrophobic clusters and regular secondary structure elements suggests a way to implement variable gap penalties during the automatic alignment of protein sequences.

Amino Acid Sequence↗
PubMed1994

Effect of the secondary structure in the Euglena gracilis chloroplast ribulose-bisphosphate carboxylase/oxygenase messenger RNA on translational initiation.

The results reported in the previous paper indicate that the translational start site of the Euglena gracilis chloroplast mRNA for the large subunit of ribulose-bisphosphate carboxylase/oxygenase (rbcL) is not defined by primary sequence elements (Koo, J.S., and Spremulli, L.L. (1994) J. Biol. Chem. 269, 7494-7500). In the work presented here, the effects of secondary structure in the 5'-untranslated leader of the rbcL mRNA have been examined. Only weak secondary structure can be detected in the 5'-untranslated leader of the rbcL message by enzymatic and computer analysis. Further reduction of the weak secondary structure of this message by site-directed mutagenesis does not significantly affect the ability of this message to participate in initiation complex formation. The secondary structure near the translational start site was increased by the introduction of an inverted repeat sequence and by site-directed mutagenesis. Messages with increased secondary structure are much less active in initiation complex formation if the structural element introduced is within approximately 10 nucleotides of the start codon. These results suggest that the translational start site in this chloroplast mRNA is specified by the presence of an AUG codon in an unstructured or weakly structured region of the mRNA. No specific sequences around the start codon, either upstream or immediately downstream, were found to have important information directing the chloroplast ribosome to the start site of this mRNA.

Animals↗
PubMed2006

Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures.

BACKGROUND: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for predicting a continuum secondary structure, i.e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models. RESULTS: Several probabilistic models not only successfully estimate the continuum secondary structure, but also provide a categorical output on par with models directly trained on categorical data. Importantly, models trained on the continuum secondary structure are also better than their categorical counterparts at identifying the conformational state for structurally ambivalent residues. CONCLUSION: Cascaded probabilistic neural networks trained on the continuum secondary structure exhibit better accuracy in structurally ambivalent regions of proteins, while sustaining an overall classification accuracy on par with standard, categorical prediction methods.

Algorithms↗
PubMed2006

Protein structural motif prediction in multidimensional phi-psi space leads to improved secondary structure prediction.

A significant step towards establishing the structure and function of a protein is the prediction of the local conformation of the polypeptide chain. In this article, we present systems for the prediction of three new alphabets of local structural motifs. The motifs are built by applying multidimensional scaling (MDS) and clustering to pair-wise angular distances for multiple phi-psi angle values collected from high-resolution protein structures. The predictive systems, based on ensembles of bidirectional recurrent neural network architectures, and trained on a large non-redundant set of protein structures, achieve 72%, 66%, and 60% correct motif prediction on an independent test set for di-peptides (six classes), tri-peptides (eight classes) and tetra-peptides (14 classes), respectively, 28-30% above baseline statistical predictors. We then build a further system, based on ensembles of two-layered bidirectional recurrent neural networks, to map structural motif predictions into a traditional 3-class (helix, strand, coil) secondary structure. This system achieves 79.5% correct prediction using the "hard" CASP 3-class assignment, and 81.4% with a more lenient assignment, outperforming a sophisticated state-of-the-art predictor (Porter) trained in the same experimental conditions. The structural motif predictor is publicly available at: http://distill.ucd.ie/porter+/.

Amino Acid Motifs↗
PubMed2001

Multiple linear regression for protein secondary structure prediction.

In the present work, a novel method was proposed for prediction of secondary structure. Over a database of 396 proteins (CB396) with a three-state-defining secondary structure, this method with jackknife procedure achieved an accuracy of 68.8% and SOV score of 71.4% using single sequence and an accuracy of 73.7% and SOV score of 77.3% using multiple sequence alignments. Combination of this method with DSC, PHD, PREDATOR, and NNSSP gives Q3 = 76.2% and SOV = 79.8%.

Databases, Factual↗
PubMed2004

Statistical correlation between protein secondary structure and messenger RNA stem-loop structure.

A new integrated sequence-structure database, called IADE (Integrated ASTRAL-DSSP-EMBL), incorporating matching mRNA sequence, amino acid sequence, and protein secondary structural data, is constructed. It includes 648 protein domains. Based on the IADE database, we studied the relation between RNA stem-loop frequencies and protein secondary structure. It was found that the alpha-helices and beta-strands on proteins tend to be preferably "coded" by mRNA stem region, while the coils on proteins tend to be preferably "coded" by mRNA loop region. These tendencies are more obvious if we observe the structural words (SWs). An SW is defined by a four-amino-acid-fragment that shows the pronounced secondary structural (alpha-helix or beta-strand) propensity. It is demonstrated that the deduced correlation between protein and mRNA structure can hardly be explained as the stochastic fluctuation effect.

Databases as Topic↗
PubMed1989

Secondary structure prediction of 52 membrane-bound cytochromes P450 shows a strong structural similarity to P450cam.

The secondary structure of 52 aligned cytochrome P450 sequences, all of which are membrane bound, is predicted and collectively compared with the crystal structure of the soluble cytochrome P450cam. Ten of 13 helical regions, 6 of 7 beta-pair regions, and beta-structure corresponding to a known beta-bulge near the active site of P450cam are predicted to exist in the membrane-bound P450s. Three turns associated with beta-structure in the soluble enzyme are also predicted for the membrane-bound forms. A strong structural similarity is evident between membrane P450s and the soluble P450cam. Consequently, a multitransmembrane structure involving much of P450 seems highly unlikely. A structure with two N-terminal transmembrane segments is compatible with these observations.

Animals↗
PubMed1999

Physico-chemical and biological properties of antisense phosphodiester oligonucleotides with various secondary structures.

The influence of the secondary structure of oligonucleotides having a natural phosphodiester backbone on their ability to interact with DNA and RNA targets and on their resistance to the nucleolytic digestion is investigated. Oligonucleotides having hairpin, looped and snail-like structure are found to be much more stable to nuclease degradation in different biological media and inside cells than the linear ones. The structured oligonucleotides can also hybridise with their DNA and RNA targets.

3T3 Cells↗
PubMed2004

Analytical description of finite size effects for RNA secondary structures.

The ensemble of RNA secondary structures of uniform sequences is studied analytically. We calculate the partition function for very long sequences and discuss how the crossover length, beyond which asymptotic scaling laws apply, depends on thermodynamic parameters. For realistic choices of parameters this length can be much longer than natural RNA molecules. This has to be taken into account when applying asymptotic theory to interpret experiments or numerical results.

Base Pairing↗
PubMed2006

Statistical and Bayesian approaches to RNA secondary structure prediction.

Prediction of RNA secondary structure is a fundamental problem in computational structural biology. For several decades, free energy minimization has been the most popular method for prediction from a single sequence. In recent years, the McCaskill algorithm for computation of partition function and base-pair probabilities has become increasingly appreciated. This paradigm-shifting work has inspired the developments of extended partition function algorithms, statistical sampling and clustering, and application of Bayesian statistical inference. The performance of thermodynamics-based methods is limited by thermodynamic rules and parameters. However, further improvements may come from statistical estimates derived from structural databases for thermodynamics parameters with weak or little experimental data. The Bayesian inference approach appears to be promising in this context.

Algorithms↗
PubMed1997

1H, 15N and 13C NMR assignments, secondary structure and overall topology of the Escherichia coli GlgS protein.

GlgS is a 7892-Da protein which is involved in glycogen biosynthesis in bacteria. We report the 1H, 15N and 13C NMR assignments of the backbone and side-chain resonances at 25 degrees C and pH 6.7 from two-dimensional homonuclear and three-dimensional heteronuclear NMR experiments. The secondary structure of the protein was determined using sequential and medium-range NOE correlations, vicinal 3J(NH-H alpha) coupling values and amide proton exchange rates. The secondary structure obtained is consistent with the secondary chemical shifts of 1H alpha, 13C alpha and 13C = O. It was found that the secondary structure of GlgS comprises two amphipathic helices (Asn10-Met21 and Glu39-Arg60), one short highly hydrophobic helix (Ile30-Val33), a short extended beta-strand-like fragment (Arg26-Asp29) and two type I beta-turns (His22-Gly25 and Thr34-Met37). An overall topology of GlgS is suggested based on long-range NOEs. The elements of secondary structure form a sandwich in which the beta-strand and the short hydrophobic helix are positioned between the two amphipathic helices.

Amino Acid Sequence↗
PubMedDate not supplied

[Defects in the secondary structure of DNA recognizable by nuclease S1 and their possible role in the aging of mammalian somatic cells].

The amount of defects in DNA secondary structure recognized by nuclease S1 and their localization by sequences of various nucleotide composition were studied in relation to the age factor. It was established that a significant twofold increase in defects of DNA secondary structure was observed in hepatic cells of very old (30 months and older) intact mice only, as well as in radiation-induced acceleration of aging at the age 19 months. The prevailing localization of the defects of DNA secondary structure has been demonstrated in those sequences which were enriched with AT pairs by 3% (as compared with the average level). It was concluded that the mentioned defects of DNA secondary structure are not the cause of aging. Nevertheless they can play an essential role in the process of irreversible destruction of genome in the terminal phase of aging.

Aging↗
PubMed2001

Study on the secondary structure of protein in amide I band from human colon cancer tissue by Fourier-transform infrared spectroscopy.

BACKGROUND: Fourier-transform infrared spectroscopy (FT-IR) is a powerful tool for study of the secondary conformation of intact protein in biological tissues and for diagnosis of disease states. The purpose of this study is to utilize FT-IR as a diagnostic tool to estimate the secondary structure of amide I in normal and cancer tissue of human colon. METHODS: Pairs of tissue samples from colon cancer and histologically normal mucosa tissue 5-10 cm from the tumor were obtained from a patient who underwent partial colectomy. In the present study we investigated the changes in the secondary structure of amide I of normal and malignant human colon tissue using FT-IR microspectroscopy with attenuated total reflectance. Secondary-derivative analysis relative to the original and curve-fitting analysis infrared spectra were also carried out. RESULTS: The conformational changes of the secondary structure of protein in normal and cancerous human colon tissue were (1) the composition of alpha-helixes increased in human cancerous colon tissue (15.30%) compared to normal colon tissue (11.72%); (2) beta-sheets which were 46.8% in healthy tissue decreased to 30.71% in cancer tissue; (3) beta-turns increased from 26.28% in normal tissue to 38.48% in cancer tissue; and (4) the composition of random coils was not significantly different between normal tissue (15.12%) and cancer tissue (15.51%). CONCLUSION: Our data demonstrate that protein in colon cancer displays abnormal FT-IR spectra. The conformational changes of the secondary structure of this protein in terms of alpha-helixes, beta-sheets and beta-turns were observed in normal and cancerous tissue from the same individual were compared.

Aged↗