A U-turn occurs when a loop section of a protein makes a short, 3-5 segment bend between the two secondary structures that it connects. These secondary structures are usually a pair of hydrogen bonded sheets, although a U-turn can appear between a sheet and a helix, or between two helices, as happens in Halorhodopsin. Strictly speaking, U-turns are not secondary structures. They can have neither hydrogen bonds nor disulfide bonds connecting them, as is the case with sheets and helices, respectively. Yet U-turns appear frequently in proteins, and they may have particular strategic considerations of their own. Finding these commonalities would be of great value to players of FoldIt.

For example, it has often been noted that U-turns typically contain very low-scoring amino acids when Show Relative Score is turned on. A U-turn is frequently the lowest-scoring area of a puzzle, but this does not necessarily mean that it is always the most suitable area for improvement. This is because while the local area may score poorly, the presence and location of the U-turn may allow other, quite large areas to score very well -- and adjusting the U-turn may throw these other areas out of alignment. A U-turn between two well-positioned sheets sharing many hydrogen bonds, with hydrophobics hidden deep within the protein, will cause these sheets to score very well. Adjusting the U-turn with the goal of raising its score may or may not yield any additional points, depending on how these adjustments affect the global structure.

With that said, U-turns are still very often good targets for rebuilds, local wiggles, and the Manual Rebuild strategy. Locking the sheets or helices that they connect, and using local-only adjustments until the protein stabilizes, are frequently advisable if you want to preserve the good characteristics of the connected pieces while exploring alternate U-turn configurations.

- AAs found most in reverse b-turns are proline, glycine, aspartate, asparagine, and serine.

Some articles regarding U-turns:

http://bioinformatics.oxfordjournals.org/content/20/16/2751.long is a free article (PMID: 15145798 [PubMed - indexed for MEDLINE]) about using neural nets for predicting beta turns. 2 webservers for this are at:

• http://www.imtech.res.in/raghava/betaturns/

• http://bioinformatics.uams.edu/mirror/betaturns/ [mirror site]