During the last two decades, the number of sequence-known proteins has increased rapidly. In contrast, the corresponding increment for structure-known proteins is much slower. The unbalanced situation has critically limited our ability to understand the molecular mechanism of proteins and conduct structurebased drug design by timely using the updated information of newly found sequences. Therefore, it is highly desired to develop an automated method for fast deriving the 3D (3-dimensional) structure of a protein from its sequence. Under such a circumstance, the structural bioinformatics was emerging naturally as the time required. In this review, three main strategies developed in structural bioinformatics, i.e., pure energetic approach, heuristic approach, and homology modeling approach, as well as their underlying principles, are briefly introduced. Meanwhile, a series of demonstrations are presented to show how the structural bioinformatics has been applied to timely derive the 3D structures of some functionally important proteins, helping to understand their action mechanisms and stimulating the course of drug discovery. Also, the limitation of these approaches and the future challenges of structural bioinformatics are briefly addressed.
Keywords: bovine somatotropin, antifreeze protein, adhesion proteins, complement control protein, caspase, secretase, &, zymogen, neuronal kinase, nachr, ion-channels, gfat
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