De novo protein structure prediction

In computational biology, de novo protein structure prediction refers to an algorithmic process by which protein tertiary structure is predicted from its amino acid primary sequence. The problem itself has occupied leading scientists for decades while still remaining unsolved. According to Science, the problem remains one of the top 125 outstanding issues in modern science. At present, some of the most successful methods have a reasonable probability of predicting the folds of small, single-domain proteins within 1.5 angstroms over the entire structure.

De novo methods tend to require vast computational resources, and have thus only been carried out for relatively small proteins. De novo protein structure modeling is distinguished from Template-based modeling (TBM) by the fact that no solved homolog to the protein of interest is used, making efforts to predict protein structure from amino acid sequence exceedingly difficult. Prediction of protein structure de novo for larger proteins will require better algorithms and larger computational resources such as those afforded by either powerful supercomputers (such as Blue Gene or MDGRAPE-3) or distributed computing projects (such as Folding@home, Rosetta@home, the Human Proteome Folding Project, or Nutritious Rice for the World). Although computational barriers are vast, the potential benefits of structural genomics (by predicted or experimental methods) to fields such as medicine and drug design make de novo structure prediction an active research field.

Currently, the gap between known protein sequences and confirmed protein structures is immense. At the beginning of 2008, only about 1% of the sequences listed in the UniProtKB database corresponded to structures in the Protein Data Bank (PDB), leaving a gap between sequence and structure of approximately five million. Experimental techniques for determining tertiary structure have faced serious bottlenecks in their ability to determine structures for particular proteins. For example, whereas X-ray crystallography has been successful in crystallizing approximately 80,000 cytosolic proteins, it has been far less successful in crystallizing membrane proteins – approximately 280. In light of experimental limitations, devising efficient computer programs to close the gap between known sequence and structure is believed to be the only feasible option.

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