What is Rosetta@home?

Blind Protein Structure Prediction High-Resolution Protein Structure Prediction Protein Design Protein-Protein Docking

Rosetta@home needs your help to determine the 3-dimensional shapes of proteins in research that may ultimately lead to finding cures for some major human diseases. By running the Rosetta program on your computer while you don't need it you will help us speed up and extend our research in ways we couldn't possibly attempt without your help. You will also be helping our efforts at designing new proteins to fight diseases such as HIV, Malaria, Cancer, and Alzheimer's. Please join us in our efforts! Rosetta@home is not for profit.

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We believe that we are getting closer to accurately predicting and designing protein structures and protein complexes, one of the holy grails of computational biology. But in order to prove this, we require an enormous amount of computing resources, an amount greater than the world's largest super computers. This is only achievable through a collective effort from volunteers like you.

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Why predict and design protein structures and complexes?

Proteins are the molecular machines and building blocks of life. Their functions and interactions are critical for the chemical and biological framework and processes of all living organisms. The function of a protein and how it iteracts with other molecules are largely determined by its shape (the three-dimensional structure). Proteins are initially synthesized as long chains of amino acids and, for the most part, they cannot function properly until they fold into intricate globular structures. Understanding and predicting the rules that govern this complex folding process -- involving the folding of the main backbone and the packing of the molecular side chains of the amino acids -- is one of the central problems of biology. Knowing how proteins fold and interact with other molecules and determining their functions may ultimately lead to drug discoveries and cures for human diseases. Currently, millions of dollars are being spent to determine the structures of proteins experimentally using X-ray crystallography and nuclear magnetic resonance (NMR). If this could be done computationally, it would significantly reduce the cost and revolutionize structural biology. Designing protein structures and complexes also offers significant scientific and practical benefits. If one can design completely new structures, one can potentially design novel molecular machines -- proteins for carrying out new functions as therapeutics, catalysts, etc. And finally, there's the evolutionary question of whether the folds that are sampled in nature are the limit to what's possible; or whether there are quite different folds that are also possible. Understanding the rules that govern folding and design may help answer this question.

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