Protein sequence-structure growing database

The database of protein sequences is growing at an exponential rate. Analyses of these sequences alone do not capture the physical and chemical properties of the 3D structure of the folded protein. Knowing the structure of a protein gives insight into its biochemical function and therefore its role in the molecular processes in the cell. Unfortunately, experimental methods to elucidate protein structures are time-consuming and can not keep up with the rate at which sequences are generated. Thus, there is considerable interest in computational methods to predict the protein structure from its sequence accurately... 

An important factor in the progress of bioinformatics has been the constant increase in computer speed and memory capacity of desktop computers and the increasing sophistication of data processing techniques. The computation power of common personal computers has increased within 12 years approximately 100-fold in processor speed, 250-fold in RAM memory space and 500-fold or more in hard disk space, while the price has nearly halved. This enables acquisition, transformation, visuahsation and interpretation of large amounts of data at a fraction of the cost compared to 12 years ago. Presently, bioanalytical databases are also growing quickly in size and many databases are directly accessible via the Internet One of the first chemical databases to be placed on the Internet was the Brookha-ven protein data bank, which contains very valuable three-dimensional structural data of proteins. The primary resource for proteomics is the ExPASy (Expert Protein Analysis System) database, which is dedicated to the analysis of protein sequences and structures and contains a rapidly growing index of 2D-gel electrophoresis maps. Some primary biomolecular database resources compiled from spectroscopic data are given in Tab. 14.1. 

Native 3D structures of proteins are encoded by a linear sequence of amino acid residues. To predict 3D structure from sequence is a task challenging enough to have occupied a generation of researchers. Have they finally succeeded in their goal The bad news is no. we still cannot predict structure for any sequence. The good news is we have come closer, and growing databases facilitate the task. 

The rich information contained in the growing sequence and structure databases has been used to improve the accuracy of predictions of some aspects of protein structure. Evolutionary information is successfully used for predictions of secondary structure, solvent accessibility, and transmembrane helices. These predictions of protein structure in ID are significantly more accurate, and more useful than five years ago. Some methods have indicated that ID predictions can be useful as an intermediate step on the way to predicting 3D structure (inter-strand contacts prediction-based threading). Another advantage of predictions in ID is that they are not very CPU-intensive, i.e., ID structure can be predicted for the... 

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