Secondary structure prediction method

Table 2.6 Some secondary structure predictive methods currently used. Refer to text for further details...

A variety of secondary structure prediction methods has been applied to (3-casein. Regions of a helix around residues 24, 94, and 133 and (3 strands near residues 83, 147, and 190 are widely predicted (Creamer etal., 1981 Graham et al., 1984 Holt and Sawyer, 1988a,b). The predicted a helix in the N-terminal phosphopeptide region may only be stable at low pH, causing the increase in apparent helix content at pH 1.5, compared to neutrality (Creamer et al., 1981). 

Source Data from Liljas A, Rossmann MG. X-ray studies of protein interactions. Annu Rev Biochem 43 475-505, 1974 Argos P, Schwarz JS, Schwarz J. An assessment of protein secondary structure prediction methods based on amino acid sequence. Biochim Biophys Acta 439 261-273, 1976. 

Discrimination Between Folds. Because of the inherent error in potential functions, secondary structure prediction methods, limited sampling, and so forth, one can anticipate that prediction of a variety of alternative structures (perhaps, by several methods) would be more likely to generate a correctly folded structure than any single prediction. The problem then becomes one of discriminating between the correct structure and alterna-... 

All the methods developed so far try to extract information, directly or indirectly (Lim, 1974), from the ever growing databases of X-ray crystallography resolved protein structures. Unfortunately, the rate at which new structures are added to the structure databases is far from optimal. Chothia (1992) estimated that all proteins, when their structures are known, would fall into about one thousand folding classes, more than half of them yet to be discovered. If so, this means that a great deal of information in the forthcoming structures is not available for the current methods, and therefore we still must rely on the future to see a coherent and realistic increase in the accuracy of secondary structure prediction methods. 

Table t List of secondary structure prediction methods utilized... 

One key element in the performance analysis of secondary structure prediction methods is the proper selection of the accuracy measurement to be employed. Three different types of predictive accuracy measurements were used (Schultz and Schirmer, 1979) ... 

Figure 3. Multidimensional scaling analysis of the dissimilarities between accuracies of different protein secondary structure prediction methods. The method codes can be found in Table I.

Secondary structure prediction methods have been complemented by packing analyses of amino acid residues in globular proteins. Packing arrangements have been examined extensively [13, 14] in attempts to identify preferred interaction patterns between non-contiguous amino acid residues. While there is no straightforward way to cast this information into a scheme for prediction of protein structure from sequence, it can certainly be used for plausibility checks on hypothetical protein models or to score protein models obtained by protein folding simulations on lattices [15]. 

We use the following secondary structure prediction methods in our ab initio... 

The Samudrala group achieved an RMSD of 10.1 A for all 76 residues and 7.4 A for 66 residues after postprocessing. The Scheraga group results in this case have to be considered best. Much of their success can be attributed to an impressive 79% accuracy in the secondary structure assembled in their most successful simulation in this case, the standard neural-network-based secondary structure prediction methods that we (and Samudrala and co-workers) employed have a much poorer performance than they do for the test set, with accuracies below 65% in all cases. 

Approaches to structure prediction using different flavors of secondary structure constraints have been recently reported. This renewed interest in the use of secondary structure information as a way of reducing conformational space when building molecular models is the result of the recent improvement in accuracy of secondary structure prediction methods due to the introduction of evolutionary information. 

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