Rosetta@home - Project Significance

Project Significance

Further information: Protein structure prediction, Protein docking, Protein design

With the proliferation of genome sequencing projects, scientists can infer the amino acid sequence, or primary structure, of many proteins that carry out functions within the cell. To better understand a protein's function and aid in rational drug design, scientists need to know the protein's three-dimensional tertiary structure.

Protein 3D structures are currently determined experimentally through X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The process is slow (it can take weeks or even months to figure out how to crystallize a protein for the first time) and comes at high cost (around $100,000 USD per protein). Unfortunately, the rate at which new sequences are discovered far exceeds the rate of structure determination – out of more than 7,400,000 protein sequences available in the NCBI non-redundant (nr) protein database, fewer than 52,000 proteins' 3D structures have been solved and deposited in the Protein Data Bank, the main repository for structural information on proteins. One of the main goals of Rosetta@home is to predict protein structures with the same accuracy as existing methods, but in a way that requires significantly less time and money. Rosetta@home also develops methods to determine the structure and docking of membrane proteins (e.g., GPCRs), which are exceptionally difficult to analyze with traditional techniques like X-ray crystallography and NMR spectroscopy, yet represent the majority of targets for modern drugs.

Progress in protein structure prediction is evaluated in the biannual Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, in which researchers from around the world attempt to derive a protein's structure from the protein's amino acid sequence. High scoring groups in this sometimes competitive experiment are considered the de facto standard-bearers for what is the state of the art in protein structure prediction. Rosetta, the program on which Rosetta@home is based, has been used since CASP5 in 2002. In the 2004 CASP6 experiment, Rosetta made history by being the first to produce a close to atomic-level resolution, ab initio protein structure prediction in its submitted model for CASP target T0281. Ab initio modeling is considered an especially difficult category of protein structure prediction, as it does not use information from structural homology and must rely on information from sequence homology and modeling physical interactions within the protein. Rosetta@home has been used in CASP since 2006, where it was among the top predictors in every category of structure prediction in CASP7. These high quality predictions were enabled by the computing power made available by Rosetta@home volunteers. Increasing computational power allows Rosetta@home to sample more regions of conformation space (the possible shapes a protein can assume), which, according to Levinthal's paradox, is predicted to increase exponentially with protein length.

Rosetta@home is also used in protein docking prediction, which determines the structure of multiple complexed proteins, or quaternary structure. This type of protein interaction affects many cellular functions, including antigen–antibody and enzyme–inhibitor binding and cellular import and export. Determining these interactions is critical for drug design. Rosetta is used in the Critical Assessment of Prediction of Interactions (CAPRI) experiment, which evaluates the state of the protein docking field similar to how CASP gauges progress in protein structure prediction. The computing power made available by Rosetta@home's project volunteers has been cited as a major factor in Rosetta's performance in CAPRI, where its docking predictions have been among the most accurate and complete.

In early 2008, Rosetta was used to computationally design a protein with a function never before observed in nature. This was inspired in part by the retraction of a high-profile paper from 2004 which originally described the computational design of a protein with improved enzymatic activity compared to its natural form. The 2008 research paper from David Baker's group describing how the protein was made, which cited Rosetta@home for the computational resources it made available, represented an important proof of concept for this protein design method. This type of protein design could have future applications in drug discovery, green chemistry, and bioremediation.

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