This document was last updated March 26th, 2015, by Shane Ó Conchúir. The original version of the application was created by Michael Tyka et al., and the first loop closure algorithm (CCD) was implemented by Chu Wang et al. in 2007. The robotics-inspired kinematic closure (KIC) algorithm for loop closure was added by Daniel J. Mandell et al. in 2009, and the refined next generation KIC algorithm by Amelie Stein and Tanja Kortemme in 2013. The latest algorithmic development in loop modeling is KIC with fragments, added by Roland A. Pache and Tanja Kortemme in 2014.
An introductory tutorial on loop modeling can be found here.
Stein A, Kortemme T. (2013). Increased sampling of near-native protein conformations. PLoS One. 2013 May 21;8(5):e63090. doi: 10.1371/journal.pone.0063090. Print 2013. PMID: 23704889
Mandell DJ, Coutsias EA, Kortemme T. (2009). Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling. Nat Methods. 2009 Aug;6(8):551-2. doi: 10.1038/nmeth0809-551. PMID: 19644455
Qian, B., Raman, S., Das, R., Bradley, P., McCoy, A.J., Read, R.J. and Baker D. (2007). High resolution protein structure prediction and the crystallographic phase problem. Nature. 2007 Nov 8;450(7167):259-64. Epub 2007 Oct 14. PMID: 17934447
Wang, C., Bradley, P. and Baker, D. (2007) Protein-protein docking with backbone flexibility. J Mol Biol. 2007 Oct 19;373(2):503-19. Epub 2007 Aug 2. PMID: 17825317
This protocol was originally developed to be combined with Rosetta full atom structure refinement (relax mode) to streamline the task of comparative modeling. It has since then evolved into a general protocol for modeling loops in protein structures. There are currently the following algorithms available (can be selected using specific flags; see documentation pages for these different algorithms for details):
CCD: fragment insertion with cyclic coordinate descent to close chain breaks
KIC: robotics-inspired kinematic closure combined with random sampling of non-pivot loop torsions from Ramachandran space
next generation KIC: refined version of KIC; using omega sampling, neighbor-dependent Ramachandran distributions and ramping of rama and fa_rep score terms to achieve higher loop reconstruction performance and increase sampling of sub-Angstrom conformations (recommended algorithm if no fragment data is available)
KIC with fragments: fragment-based loop modeling using kinematic closure; combining the sampling powers of KIC and coupled phi/psi/omega degrees of freedom from protein fragment data to achieve higher loop reconstruction performance and the best sampling yet of sub-Angstrom conformations (recommended algorithm if fragment data is available)
Common input files include:
Start pdb: Template pdb file with real coordinates for all residues plus the first and last residue of each loop region.
NOTE: Residue indices in loop definition files refer to Rosetta numbering (numbered continuously from '1', including across multi-chain proteins). It may be useful to renumber starting structures with Rosetta numbering so loop defintions and PDB residue indices agree.
column1 "LOOP": The loop file identify tag column2 "integer": Loop start residue number column3 "integer": Loop end residue number column4 "integer": Cut point residue number, >=startRes, <=endRes. Default: 0 (let the loop modeling code choose the cut point) Note: Setting the cut point outside the loop can lead to a segmentation fault. column5 "float": Skip rate. Default: 0 (never skip modeling this loop) column6 "boolean": Extend loop (i.e. discard the native loop conformation and rebuild the loop from scratch, idealizing all bond lengths and angles). Default: 0 (false)
Fragment files (for CCD and KIC with fragments)
Depending on the specific loop algorithm you choose (CCD/KIC/next generation KIC/KIC with fragments), different sets of flags apply. Please check the documentation for the respective algorithm for details.
For a full list of all available loop modeling flags, please check the full options list
A protocol capture for some of the loop modeling algorithms above (KIC, next generation KIC, KIC with fragments) can be downloaded from the Macromolecular modeling and design benchmarks website. The loop modeling page also lists suggested parameters to use for the different protocols.
The loopmodel executable has a separate MPI implementation from the JD2 implementation that serves most of Rosetta. As normal, just compile Rosetta in mpi (add extras=mpi to the scons command line when compiling) to activate MPI. When you run loopmodel.mpi.***, it will expect that you have precreated output directories for it, named ./output_#, where # is the zero-indexed processor rank (and you need one for each processor). So, for a 8-processor MPI job, created output_0, output_1, ..., output_7.