<unk>  takes advantage of completed genome sequences in several ways in order to determine protein structures. The gene sequence of the target protein can also be compared to a known sequence and<unk>  information can then be inferred from the known protein's structure.<unk>  can be used to predict novel protein folds based on other<unk>  data.<unk>  can also take modeling-based approach that relies on homology between the unknown protein and a solved protein structure. de novo methods Completed genome sequences allow every open reading frame (ORF), the part of a gene that is likely to contain the sequence for the messenger RNA and protein, to be cloned and expressed as protein. These proteins are then purified and crystallized, and then subjected to one of two types of structure determination: X-ray crystallography and nuclear magnetic resonance (NMR). The whole genome sequence allows for the design of every primer required in order to amplify all of the ORFs, clone them into bacteria, and then express them. By using a whole-genome approach to this traditional method of protein structure determination, all of the proteins encoded by the genome can be expressed at once. This approach allows for the<unk>  determination of every protein that is encoded by the genome. Modelling-based methods ab initio modeling This approach uses protein sequence data and the chemical and physical interactions of the encoded amino acids to predict the 3-D structures of proteins with no homology to solved protein structures. One highly successful method for ab initio modeling is the Rosetta program, which divides the protein into short segments and arranges short polypeptide chain into a low-energy local conformation. Rosetta is available for commercial use and for non-commercial use through its public program, Robetta. Sequence-based modeling This modeling technique compares the gene sequence of an unknown protein with sequences of proteins with known structures. Depending on the degree of similarity between the sequences, the structure of the known protein can be used as a model for solving the structure of the unknown protein. Highly accurate modeling is considered to require at least 50% amino acid sequence identity between the unknown protein and the solved structure. 30-50% sequence identity gives a model of intermediate-accuracy, and sequence identity below 30% gives low-accuracy models. It has been predicted that at least 16,000 protein structures will need to be determined in order for all<unk>  motifs to be represented at least once and thus allowing the structure of any unknown protein to be solved accurately through modeling. One disadvantage of this method, however, is that structure is more conserved than sequence and thus sequence-based modeling may not be the most accurate way to predict protein structures. Threading Threading bases<unk>  modeling on fold similarities rather than sequence identity. This method may help identify distantly related proteins and can be used to infer molecular functions.
Structural genomics
Genomics
Molecular biology
Molecular genetics
Phylogenomics
Genotyping
Toxicogenomics
Virology