1. rosetta -design -s acdt.pdb -fixbb -profile -ex1 -ex1aro -ex2 -ex2aro_only -ndruns 1000 -resfile reslist.res -pdbout acdt -scorefile acdt -no_new_CG -fa_input -try_both_his_tautomers -fix_disulf disulf.txt -norepack_disulf
Do you have cys in your protein?The command line looks really
complicated. I would start with a simple one first and if it doesn’t
work out well, then try to play with it.Try this first
rosetta -design -s acdt.pdb -fixbb -ex1 -ex2 -ex2aro_only
-ndruns 100 -resfile reslist.res -try_both_his_tautomers
2. The particular protein I’m studying has many beta sheets, so I’d assume that –use_bw would give better scores, but with the above keywords + -use_bw, I get approximately the same scores.
That suggest something is wrong. Usually when you use use_bw flag, the scores will be different. But actually, you don’t have to use use_bw flag. Just don’t use it at this moment, see what happens.
3. What you mean acceptance is always zero?Is the 1000 output structures
are exactly the same?
> I am attempting to use RosettaDesign for the first time. I would like to identify mutations that will yield enhanced packing in the core of a 234 residue protein. In the manner of Dantas et al, JMB (2003) 332, 449-460, I would like to do 2 rounds of optimization: during the first round, I would like to allow the selected amino acids in the protein core to change into any other amino acid (except for CYS and GLY). During the second round, I would like to restrict the amino acid selection to those that were found in the first round.
> For round 1, I have setup a resfile that contains amino acids in the core with the option ALLAA. I am using the following command:
> rosetta -design -s acdt.pdb -fixbb -profile -ex1 -ex1aro -ex2 -ex2aro_only -ndruns 1000 -resfile reslist.res -pdbout acdt -scorefile acdt -no_new_CG -fa_input -try_both_his_tautomers -fix_disulf disulf.txt -norepack_disulf
> However, I’m having difficulties with knowing if this set of keywords will yield the best results:
> In the documentation, there was mention of using -use_aw and –use_bw. Is one of these keywords typically used in these types of design runs? The particular protein I’m studying has many beta sheets, so I’d assume that –use_bw would give better scores, but with the above keywords + -use_bw, I get approximately the same scores.
> In addition, if I run the command with a resfile containing NATRO for all amino acids for 1 trial, the score is -234. However, for all 1,000 mutants generated during round 1, the score is always >= -227 and the acceptance is always 0.00. Is there something important that I’m missing, such as repack or mcmin_trials? Should I expect to achieve lower scores than the wild type protein during round 1?
> Any help and advice would be greatly appreciated!
> Thanks very much, Gregg