Rosetta ddg_monomer 사용법

Application 위치

Helper application minimize_with_cst → cst=constraint
Helper script


Monomeric protein에 발생한 mutation에 의해서 변화하는 단백질 안정성 예측
ddG = mutant energy - wildtype energy


Crystal structure of wild-type (Pre-minimized 되어야 함.)
Mutation file (resfile) 형태


Wildtype과 mutant structure 각각 50개의 모델을 만들어서, 가장 좋은 3개의 structure의 score 평균의 차이로 구한다.

1) High-resolution protocol

Backbone conformational freedom을 조금만 허용한다.
Rosetta의 side-chain optimization module (packer)를 사용해서 단백질의 모든 residue를 최적화.
Gradient-based minimization을 3 round로 진행 (van der Waals repulsive component term의 downweight을 다르게 하여 진행. detail은 생략)
Pre-minimization -
$ROSETTABIN/minimize_with_cst.static.linuxgccrelease -in:file:l lst -in:file:fullatom \ -ignore_unrecognized_res -fa_max_dis 9.0 \ -database $ROSETTABIN \ -ddg::harmonic_ca_tether 0.5 -ddg::constraint_weight 1.0 \ -ddg::out_pdb_prefix min_cst_0.5 -ddg::sc_min_only false > mincst.log
lst는 pdb 파일 경로가 모여 있는 리스트 파일이다.
Distance restraints 파일 생성 - backbone conformation이 많이 변하는 것을 막기 위해서 Ca-Ca distance에 제약 조건을 둔다.
./ mincst.log > input.cst
mincst.log 파일은 pre-minimization step에서 얻을 수 있다고 함.
./ 파일을 약간 수정해야 함. minimize_with_cst.static.linuxgccrelease 파일 로그 앞에 apps.public.ddg.minimize_with_cst prefix가 붙기 때문.
-in:file:s min_cst_0.5.WT_0001.pdb # the PDB file of the structure on which point mutations should be made -ddg::mut_file Y176A.resfile # the list of point mutations to consider in this run -ddg:weight_file soft_rep_design # Use soft-repulsive weights for the initial sidechain optimization stage -ddg:minimization_scorefunction <weights file> # optional -- the weights file to use, if not given, then the current default scorefunction will be used. -ddg::minimization_patch <weights patch file > # optional -- the weight-patch file to apply to the weight file; does not have to be given -database /path/to/rosetta/main/database #the full oath to the database is required -fa_max_dis 9.0 # optional -- if not given, the default value of 9.0 Angstroms is used. -ddg::iterations 50 # 50 is the recommended number of iterations -ddg::dump_pdbs true # write out PDB files for the structures, one for the wildtype and one for the pointmutant for each iteration -ignore_unrecognized_res # optional -- if there are residues in the input PDB file that Rosetta cannot recognize, ignore them instead of quitting with an error message -ddg::local_opt_only false # recommended: local optimization restricts the sidechain optimization to only the 8 A neighborhood of the mutation (equivalent to row 13) -ddg::min_cst true # use distance restraints (aka constraints) during the backbone minimization phase -constraints::cst_file <cbeta-distance-constraint-file> # the set of constraints to use during minimization which should reflect distances in the original (non-pre-relaxed) structure -ddg::suppress_checkpointing true # don't checkpoint LIZ DOES CHECKPOINTING WORK AT ALL? -in::file::fullatom # read the input PDB file as a fullatom structure -ddg::mean false # do not report the mean energy -ddg::min true # report the minimum energy -ddg::sc_min_only false # do not minimize only the backbone during the backbone minimization phase -ddg::ramp_repulsive true # perform three rounds of minimization (and not just the default 1 round) where the weight on the repulsive term is increased from 10% to 33% to 100% -mute all # optional -- silence all of the log-file / stdout output generated by this protocol -unmute core.optimization.LineMinimizer # optional -- unsilence a particular tracer -ddg::output_silent true # write output to a silent file
Plain Text

2) Low-resolution protocol

Backbone conformational freedom을 허용하지 않고, sidechain conformational flexibility만 허용. Mutation 주변의 residue의 rotamer를 최적화한다.


E. Kellogg, A. Leaver-Fay, and D. Baker, (2011) "Role of conformational sampling in computing mutation-induced changes in protein structure and stability", Proteins: Structure, Function, and Bioinformatics. V 79, pp 830–838.