Author: P. Douglas Renfrew (firstname.lastname@example.org)
State when the documentation was last updated December 2011 by P. Douglas Renfrew. The PI for this application is Brian Kuhlman (email@example.com).
The main mover is located in the application code at
main/source/src/protocols/unfolded_state_energy_calculator . The application code is located at
main/source/src/apps/public/ncaa_utilities/UnfoldedStateEnergyCalculator.cc . The integration tests can be found at
main/tests/integration/tests/unfolded_state_energy_calc/ . The demo can be found at
P. Douglas Renfrew, Eun Jung Choi, Brian Kuhlman, "Using Noncanonical Amino Acids in Computational Protein-Peptide Interface Design" (2011) PLoS One.
Calculating the explicit unfolded state energies is the third of three steps toward being able to use a noncanonical amino acid (NCAA) in Rosetta. The explicit unfolded state energies of an amino acid represent the energy of an amino acid in the unfolded state of a protein and is used to replace the reference energies in Rosetta.
The UnfoldedStateEnergyCalculator uses a fragment based method to calculate the average unfolded state energies for each ResidueType. The protocols works on a large set of protein structures that are split in to randomly generated fragments. The central residue of each fragment is mutated to the residue of interest. The fragment is repacked. The unweighted energy for each energy method in the scoring function is recorded for the central residue. After the energies for all fragment central residues are collected, a boltzmann-weighted-average average energy is calculated for each term.
Calculation explicit unfolded state energies for a NCAA requires three steps:
This code is for calculating unfolded energies and nothing else.
Since the UnfoldedStateEnergyCalculator protocol uses fragments from protein structures, we need a set of high quality structures to work with. Through their PISCES server, the Dunbrack laboratory maintains lists of structures in the Protein Data Bank organized based on xray resolution, precent sequence similarity, and r-factors**. These lists are a convenient way to get a set of high quality structures. In this example we will use a list culled on May 20, 2011. It contains 1801 pdb files that have an an xray resolution of at least 1.6 angstroms, less than 20% sequence identity, and r-factors of less than 0.25. To get the pdbs simply use a supplied script to download the pdbs from the Protein Data Bank ftp servers.
$ cd inputs $ ../scripts/get_pdbs.bash cullpdb_pc20_res1.6_R0.25_d110520_chains1859
There should be 1801 gzipped pdb files and a text file containing a list of them called
cullpdb_pc20_res1.6_R0.25_d110520_chains1859_list_pruned in the inputs directory of the demo. Rosetta will sometimes fail to correctly read in particular pdbs files. The
cullpdb_pc20_res1.6_R0.25_d110520_chains1859_list_pruned file is a list of the pdbs which have been screened to be read successfully by Rosetta.
Citation: G. Wang and R. L. Dunbrack, Jr. PISCES: a protein sequence culling server. Bioinformatics, 19:1589-1591, 2003.
The UnfoldedStateEnergyCalculator is relatively easy to run.
Additionally it is strongly recommended to add the following flags as they will make Rosetta handle more pdb files and improves runtime by disabling default features that will be negated by the fragmenting and prepacking
Continuing the ornithine example we have used in the two previous protocol captures, to calculate the unfolded state energies one would run the following command.
$ cd outputs $ PATH/TO/bin/UnfoldedStateEnergyCalculator.macosgccrelease -database PATH/TO/rosetta/main/database -ignore_unrecognized_res -ex1 -ex2 -extrachi_cutoff 0 -l ../inputs/cullpdb_pc20_res1.6_R0.25_d110520_chains1859_list_pruned -residue_name C40 -mute all -unmute devel.UnfoldedStateEnergyCalculator -unmute protocols.jd2.PDBJobInputer -no_optH true -detect_disulf false >& ufsec_log_c40 &
NOTE: The extension on your executable my be different.
The run will take between 30-60 seconds per pdb file.
The log file contains lots of useful information. It contains the unweighted energies for each of the energy methods for each of the individual fragments. At the end it will print the average unweighted energies for each ResidueType as well as the Boltzmann weighted average unweighted energies. Boltzmann weighted average unweighted energies are used because some backbones just can't tolerate a mutation to a particular ResidueType and there are extremely high repulsive energies for some fragments that skew the average value. Using the Boltzmann weighting removes the higher energy outliers in a more elegant fashion than a hard energy cutoff.
Once the UnfoldedStateEnergyCalculator has finished running the Boltzmann weighted average unweighted energies need to be added to the database. The line you want is the
BOLZMANN UNFOLDED ENERGIES . These are the Boltzmann weighted average unfolded energies for each energy method. The file you need to modify is unfolded_state_residue_energies_mm_std.
Using the ornithine line as an example, the line form the log file is bellow
BOLZMANN UNFOLDED ENERGIES: fa_atr: -2.462 fa_rep: 1.545 fa_sol: 1.166 mm_lj_intra_rep: 1.933 mm_lj_intra_atr: -1.997 mm_twist: 2.733 pro_close: 0.009 hbond_sr_bb: -0.006 hbond_lr_bb: 0.000 hbond_bb_sc: -0.001 hbond_sc: 0.000 dslf_ss_dst: 0.000 dslf_cs_ang: 0.000 dslf_ss_dih: 0.000 dslf_ca_dih: 0.000
We could add the following to the unfolded_state_residue_energies_mm_std file in the database using the command bellow.
$ echo "C40 -2.462 1.545 1.166 1.933 -1.997 2.733 0.009 -0.006 0.000 -0.001 0.000" >> minirosetta_database/scoring/score_functions/unfolded/unfolded_state_residue_energies_mm_std
The ResidueType can now be used in almost any Rosetta protocol that is compatible with the MM_STD scoring function.
This application is new for the Rosetta 3.4 release.