Secondary structure predictions approaches

Currently, there exists an enormous and growing deficit between the number of polypeptides whose amino acid sequence has been determined and the numbers of polypeptides whose three-dimensional structure has been resolved. Given the complexities of resolving three-dimensional structure experimentally, it is not surprising that scientists are continually attempting to develop methods by which they could predict higher order structure from amino acid sequence data. Although modestly successful secondary structure predictive approaches have been developed, no method by which tertiary structure may be predicted from primary data has thus far been developed. 

Rule-based Approaches Using Secondary Structure Prediction... 

Ihe rule-based approach to protein structure prediction is obviously very reliant on th quality of the initial secondary structure prediction, which may not be particularly accurate The method tends to work best if it is known to which structural class the protein belongs this can sometimes be deduced from experimental techniques such as circular dichroism... 

Over 20 different methods of secondary structure prediction have been reported (Table 2.6). The approaches taken fall into two main categories ... 

Naive approaches avoid theoretical assumptions and instead focus on statistics about solved RNA structures, using these to probabilistically align new sequences with solved structures. One elegant approach to this problem has used an rRNA database to generate a novel RNA-specific substitution matrix. The advantage of this approach is that it makes the whole spectrum of primary-structure sequence-analysis tools available for secondary-structure prediction (27). 

Computation proteome annotation is the process of proteome database mining, which includes structure/fold prediction and functionality assignment. Methodologies of secondary structure prediction and problems of protein folding are discussed. Approaches to identify functional sites are presented. Protein structure databases are surveyed. Secondary structure predictions and pattern/fold recognition of proteins using the Internet resources are described. 

There are four approaches to secondary structure prediction (Fasman, 1989) ... 

A number of Web sites offer services in the secondary structure predictions of proteins using different approaches with varied accuracy. The Secondary structure prediction of ExPASy Proteomic tools (http //www.expasy.ch/tools/) provides pointers to different Web servers for predicting secondary structures of proteins. The ProtScale of ExPASy Proteomic tools produces conformational profiles by plotting statistical scales of various parameters (e.g., Chou and Fasman s conformational propensities, Levitt s conformational parameters) against residue positions. 

Yi TM, Lander ES. Protein secondary structure prediction using nearest neighbor methods. J. Mol. Biol. 1993 232 1117-1129. de Dios AC, Pearson JG, Oldfield E. Secondary and tertiary structural effects on protein NMR chemical shifts an ab initio approach. Science 1993 260 1491-1496. 

Yao XQ, Zhu H, She ZS. A dynamic Bayesian network approach to protein secondary structure prediction. BMC Bioinformatics. 2008 9 49. 

This methodology has been used to predict the structure of loops of helical-bundle proteins, given the positions of the connection to the helices (372). Because of the uncertainties in secondary structure predictions that are used as inputs to constrain the search, any single prediction of the method must be viewed with skepticism. Development of scoring functions that discriminate between alternative models at the Ca level of resolution would complement this approach. 

Other, perhaps alternative, approaches that could be used for epitope mapping include homolog-scanning mutagenesis (5), which could also be a means of complementing the secondary structure predictions. This involves the synthesis of an array of small peptides that completely span the protein... 

Algorithms for secondary structure prediction are based upon diverse theoretical approaches. There are three mainstream classes of methods (Gamier and Levin, 1991) ... 

One important experimental result was available, the quantitative measurement of the fraction of each secondary structural element by circular dichroism (CD) on purified lipid-protein complexes. This provided a constraint that allowed a careful evaluation of the secondary structure predictions derived from the various approaches, some of which were developed for water-soluble proteins and therefore of uncertain reliability for proteins in a lipid environment. The data from these analyses were combined using an integrated prediction method to arrive at a consensus secondary structure model for each protein. The integrated method involved 36 steps, with independent predictions at each step. The final model was based on an evaluation of the various predictions, with judicious intervention by the authors. As an aid to developing the appropriate weighting of all the data, they carried out the analysis for apoE-3 without reference to the available crystal structure (Wilson et al., 1991), then used the known structure of the HDL-binding amino-terminal domain of apoE-3 as feedback to reevaluate the weighting. 

Secondary structure prediction assigns a local helical (alpha) or extended (beta) structure to amino acid chains. The problem has been approached in an ab initio manner [46-48] for some time and many prediction methods have been developed based on properties of amino acids. Major advances have been achieved by employing homology-based approaches to 2D prediction. Such methods using sequence family information or consensus formation from several prediction methods are discussed in Section 6.4.1. 

Hua, S. Sun, Z. (2001). A novel method of protein secondary structure prediction with high segment overlap measure Support Vector Machine approach. J Mol Biol 308(2), 397-407. 

The first step in this procedure requires the secondary structural elements to be predicted. In other words, each amino acid must be assigned to one of three classes a-helix, / -strand or coil (i.e. neither helix nor strand) Some approaches also predict whether an amino acid is present in a turn structure. One of the first methods for secondary structure prediction was devised by Chou and Fasman [Chou and Fasman 1978]. Theirs is a statistical method, based upon the observed propensity of each of the 20 amino acids to exist as a-helix, / -strand and coil. These propensities were originaUy determined by analysing 15 protein X-ray structures. The fractional occurrence of each amino acid in each of these three states was calculated, as was the fractional occurrence of the amino acid over all 15 structures. The propensity of that residue for a given t3rpe of secondary structure then equals the ratio of these two values. Each residue was also classified according to its propensity to act as an initiator or as a breaker of a-helices and /3-strands. To predict the secondary structure, the amino acid sequence is searched for potential a-helix or /3-strand initiating... 

For example, some proteins contain only n-helices, which obviously makes the problem of predicting the secondary structure considerably easier. Overall, such approaches have had variable success at predicting protein structure. Nevertheless, secondary structure prediction is increasingly used as part of more general approaches to predicting protein structure. 

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