Threading, predicting proteins

A major problem in predicting protein structure is the computational intractability. A short, 100-residue protein will contain at least 100 side-chain-to-side-chain or side-chain-to-solvent interactions. The orientation of each of these interactions will lead to cascading effects throughout the protein. Comparative modeling, threading algorithms, and de novo predictions seek to predict protein structure in reasonable execution times. 

Structure prediction methods have to be validated using comprehensive and representative benchmark sets. A couple of benchmark sets have been proposed [188, 199, 270] consisting of a fold library and a list of structurally similar protein pairs without significant sequence similarity. Such a benchmark [335] involves using the method in question to thread one protein of each pair against the library and to count the number of successful recognitions of the structural match or the number of correct identifications of related protein pairs. A couple of methods have been evaluated this way. 

In CASPI a total of 21 protein sequences with no significant sequence homology to proteins of known structure were made available for threading predictions. Nine teams submitted a total of 86 predictions for these proteins using different... 

This section briefly reviews prediction of the native structure of a protein from its sequence of amino acid residues alone. These methods can be contrasted to the threading methods for fold assignment [Section II.A] [39-47,147], which detect remote relationships between sequences and folds of known structure, and to comparative modeling methods discussed in this review, which build a complete all-atom 3D model based on a related known structure. The methods for ab initio prediction include those that focus on the broad physical principles of the folding process [148-152] and the methods that focus on predicting the actual native structures of specific proteins [44,153,154,240]. The former frequently rely on extremely simplified generic models of proteins, generally do not aim to predict native structures of specific proteins, and are not reviewed here. 

L Jaroszewski, L Rychlewski, B Zhang, A Godzik. Fold prediction by a hierarchy of sequence, threading, and modeling methods. Protein Sci 6 1431-1440, 1998. 

B Rost, R Schneider, C Sander. Protein fold recognition by prediction-based threading. J Mol Biol 270 471-480, 1997. 

Approaches of de novo predictions, which try to calculate how the structural elements are folded into the 3D-stmcture (tertiary structure) of complete proteins are nowadays far away from reliable large-scale applications. On the other, hand this topic is under strong development indicated by recent successful results at the contest for structural prediction methods CASP4. With the fast growing number of experimentally solved 3D-stmctures of protein and new promising approaches like threading tools combined with experimental structural constraints, one can expect more reliable de novo predictions for 3D-protein structures in the future. 

Threading techniques try to match a target sequence on a library of known 3D structures by threading the target sequence over the known coordinates. In this manner, threading tries to predict the 3D structure starting from a given protein sequence. It is sometimes successful when comparisons based on sequences or sequence profiles alone fail due to a too low sequence similarity. 

The contractile proteins of the spindle apparatus must draw apart the replicated chromosomes before the cell can divide. This process is prevented by the so-called spindle poisons (see also colchicine, p. 316) that arrest mitosis at metaphase by disrupting the assembly of microtubules into spindle threads. The vinca alkaloids, vincristine and vinblastine (from the periwinkle plant. Vinca rosea) exert such a cell-cycle-specific effect. Damage to the nervous system is a predicted adverse effect arising from injury to microtubule-operated axonal transport mechanisms. 

Keywords Genetic algorithm Protein structure prediction Evolutionary algorithms Alignment Threading... 

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