| abstract | - Since 1960s we know that protein's three-dimensional structure is determined by its amino acid sequence (today we also know that sometimes help from "chaperone" proteins is needed during folding). Predicting the shape of the protein (tertiary structure) based only on the amino acid sequence (primary structure), however, was a daunting task. Proteinomics is a science of solving this problem. It is important, because once we solve it, we will be able to predict the shape of proteins generated by particular genetic code, which is just one step away from predicting the chemical and biological activity of the protein, which is one step from predicting the results (entirely in silico) of a genetic modification. This will essentially (ignoring all the technical difficulties) make it easy to genetically engineer anything to a specification and fix all problems with any living organism, including ourselves. The development of supercomputers (as well as distributed projects such as Folding@Home) is one important aspect of proteinomics, as the power of brute force should never be underestimated. But in addition to that scientists are working on better prediction methods, theories, algorithms, etc. There are some typical structures in all proteins (spirals, etc.), but we are still far from understading how proteins work completely. The state of the art (as described here) is getting about one-third of relatively short proteins more or less correctly, getting the general idea right. On the illustration blue shows the simulation result, red shows the experimental data. Pretty close, isn't it? As said above, the next step after solving the folding problem will be understanding how proteins work in generally, predicting the interactions and characteristics of the protein, knowing its 3d shape.
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