Loop modeling in YASARA

YASARA Structure features a loop modeler, that can quickly retrieve loop conformations that bridge two sets of anchor residues from the Protein Data Bank. This knowledge-based approach benefits enormously from the steadily growing PDB, and has been shown to be a strong competition for ab-initio loop prediction[1].

• A non-redundant subset of the PDB (90% sequence identity cutoff[2]) forms the database from which the loop conformations can be retrieved. Currently the database contains ~14000 complete protein chains.
• Since complete chains are stored in the database, queries are not limited to loops. It is easily possible to extract e.g. all fragments spanning two selected anchor points that contain 10 helical residues in the middle.
• For loops up to 18 residues long, a database index allows to retrieve the hits within a fraction of a second. Longer loops take around a minute to model.
• The loop conformations extracted from the database are ranked by a combined quality score, that considers sequence similarity, bumps with the rest of the structure, and the fit to the terminal loop anchor points.
• Since loops extracted from a database do normally not fit the anchor points exactly, they are closed using cyclic coordinate descent, an algorithm developed to steer robotic arms[3].
• To identify the best conformation of potentially hundreds of database hits, YASARA analyzes the loops sequentially, optimizing the side-chains of loop- and surrounding residues[4], and calculating interaction and solvation energies, including knowledge based dihedral and packing components.

R E F E R E N C E S
[1] Loops In Proteins (LIP) - a comprehensive loop database for homology modelling
Michalsky E, Goede A and Preissner R (2003) Protein Engineering 16, 979-985
[2] PISCES: a protein sequence culling server
Wang G and Dunbrack RL Jr. (2003) Bioinformatics 19, 1589-1591
[3] Cyclic coordinate descent: A robotics algorithm for protein loop closure
Canutescu AA and Dunbrack RL Jr. (2003)Protein Sci. 12, 963-972
[4] A graph-theory algorithm for rapid protein side-chain prediction
Canutescu AA, Shelenkov AA and Dunbrack RL Jr. (2003), Protein Sci. 12,2001-2014.