Prediction Of Secondary Structure And Molecular Modeling

Many attempts have been made to predict protein structures from their primary sequences using a variety of parameters such as amino acid frequency, energy calculation, and <p and values. As a result of these studies, it was possible to identify and quantify the secondary structure of proteins based on sequence data alone, with some degree of accuracy. In one of the most common of the secondary structure prediction methods, a statistical survey was conducted for 15 proteins in which the a-helix, /?-sheet, and fi-turn conformational potentials of all 20 amino acids were established (30). A set of empirical rules was then derived that allowed for the determination of the folding of the secondary structure regions in the proteins. Computer programs for this prediction, including programs for personal computers, have been published.

Although numerous prediction methods, in addition to the above Chou-Fasman approach (30), have been developed, the accuracy of these methods has not been very high, which is undoubtedly a result of the probabilistic nature of the methods (31). Moreover, protein structure hierarchy is not so rigorous as to assume that the secondary structure formation of a certain segment is entirely dependent on the sequence information alone; other segments at a distance along the chain also exert an influence.

To improve the correctness of prediction, attempts have been made by using sequence homology, multivariate analysis, and especially energy minimization. It is generally agreed that the maximum correctness is expected to be far less than 80%. In contrast, molecular modeling is based on known three-dimensional structures of homologous molecules with the expectation of maximum accuracy in prediction of about 80% (32).

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