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Most proteome-wide functional annotation focuses on sequence similarity, however, this ignores valuable information that protein structure can provide an important consideration in the era of structural genomics when many more protein structures are becoming available [1].

Moreover, as more protein structures are determined and more domains assigned the repertoire of domains that can be mapped to a given genome will also increase.

This has key practical consequences for the derivation and analysis of protein structures, and is exploited by the process of "molecular sieving" whereby a common core is progressively distilled from a comparison of two or more protein structures.

Root mean square deviation (RMSD) is frequently used in structural bioinformatics to measure the average distances between atoms from two or more protein structures.

The puzzle of how specificity is achieved in these reactions grows as more and more protein structures confirm the conservation of a lipoxygenase protein fold in plants, animals, and bacteria.

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Both searches are detailed in text of Figure 1: simple search (analysis of one or more protein structure) and advanced search based on specific criteria to perform more complex queries.

Cation−π interactions are increasingly being appreciated as important for stabilizing both protein protein and protein ligand interactions, and, as more proteins structures are being revealed at atomic resolution, we have an ever increasing understanding of how and where these interactions are formed.

As a result of technological advances in various fields, more and more membrane protein structures have become available [13], although their numbers are still much smaller than those of globular proteins [14].

New folds and superfamilies are assigned to protein structure classification schemes as more protein 3D structures are solved; this increased the average domain coverage of genomes from 53% in SCOP 1.63 (765 folds, 1232 FSFs) to 60% in SCOP 1.73 (1086 folds, 1777 FSFs) over a period of four years (Supplementary Text S2).

They also found that later clades had higher rates of amino acid substitution, more flexible protein structures and greater ligand-binding efficiency than more ancestral lipocalins.

With these novel structural alphabets, we are able to construct more accurate protein structures than the state-of-art ab initio protein structure prediction programs such as ROSETTA.

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