Fold recognition modeling

Jones, D. T. (2001) Evaluating the potential of using fold-recognition models for molecular replacement. Acta Crystallogr. D 57,1428-1434. 

Detecting low-homology models (using fold-recognition algorithms)... 

The 3D-PSSM (Kelley et ah, 2000) server at http //www.bmm.icnet.uk/ 3dpssm/ offers online protein fold recognition. On the submission form, enter your e-mail address and a one-line description of the query protein, then paste the query sequence into the sequence box and click the Submit button. The query sequence is used to search the Fold library for homologues. You will be informed of the URL where the result is located for 4 days. The output includes a summary table (hits with statistics models that can be viewed with RasMol classifications and links) and fold recognition by 3D-PSSM with a printout as exemplified in Figure 12.13. The alignment displays consensus sequence, secondary structures (C for coil, E for extended, and H for helix), and core score (0 for exterior to 9 for interior core). 

A. Kolinski, J.M. Bujnicki, Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models. Proteins 61(S7), 84-97 (2005)... 

What does this have to do with structure prediction In fact, we would like to solve a fold recognition problem (Fig. 7.3). For each domain, we consider several million possible sequences, and identify the most favorable. These provide a signature of the 3D domain structure, or fold. Indeed, if we consider a new protein sequence, for which the 3D structure is unknown, we can compare it to our database of computed sequences. If the new sequence is similar to one or more in our database, we can infer that it will adopt the same 3D stmcture. In effect, we have identified the fold of the new sequence, and this is the first step towards structure prediction by homology modeling (above) [7]. 

In tertiary structure prediction, there are three distinct scenarios. The sequence to be modeled may be closely related to a protein whose structure has been determined experimentally. Here, there is the prospect of developing a relatively accurate structural model through comparative modeling. This prospect drops markedly with the strength of the relationship between the sequence to be modeled and known structures. As this relationship weakens, one moves from the realm of comparative modeling to an approach known as fold recognition. Here, one attempts to utilize... 

For the CASP2 experiment, Marchler-Bauer and Bryant defined a large number of quantitative criteria [110] to be used by the assessor to judge and rank the models and prediction teams. These criteria include several measures for fold recognition specificity, for threading alignment specificity, threading contact specificity, and model accuracy. 

Several methods have been developed for this purpose. These include (a) comparative or homology modeling, (b) threading method or fold recognition, (c) ab initio method, and (d) visualization of protein folding by computer simulation. 

Fold recognition Protein structure can be predicted with fold recognition. A protein sequence and its predicted secondary structure are compared to the sequences of a library of experimentally known folds. If a structure has more than 50% sequence homology, homology modeling is used instead. A similar procedure is threading. 

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