Pathway Gap Filling Post-CHECKSPMUTATE
Introduction
This is a recommended procedure to be used following the use of CHECKSPMUTATE, if it was a pathway which was being reoptimised.
CHECKSPMUTATE mutates a selected set of residues in a protein or protein+ligand system, and reoptimises all of the stationary points from the original system. Thus mutated forms or a close homologue can be directly compared against a wild type protein. This is particularly useful when comparing a particular protein fold or protein+cofactor interaction. In these instances, we are interested in reoptimising only the stationary points comprising a particular pathway, and the database before mutation is set up accordingly.
It is almost inevitable (particularly is we are introducing bulky mutations) that not all of the stationary points post-mutation will reoptimise (there could be steric clashes etc). Thus, there will be gaps in our new, mutated pathway. Hence the need for post-processing to fill these gaps.
Please note this method listed below is highly idiosyncratic, and as such is only meant as a loose guide. It uses very simple bash scripts, which can be easily edited. Please feel free to adapt the procedure to your own needs/preferences.
Method
The directories used for CHECKSPMUTATE and its post-processing. The bash scripts are set up to move between these, so will need to be adapted if the directories are named/organised differently.
Checkmin/Checkts
Rationale
Ordinarily, I will have run CHECKSPMUTATE calculations in checkmin and checkts directories respectively. Because of the way OPTIM jobs are assigned by PATHSAMPLE - with each job being assigned a random number - it is possible that two or more OPTIM jobs get assigned the same random number within the same PATHSAMPLE batch. Therefore, the former job gets overwritten by the latter. This seems to be a fairly significant bug within PATHSAMPLE but nobody else seems to have had a problem with it before (I can only assume nobody else has run into this problem, or have come up with their own workarounds). I didn't want to tamper with the cycle2.f90 routine and so my fix involves optimising again these overwritten files. Typically, the number of overwritten files is small compared to the overall number of reoptimisation first conducted by CHECKSPMUTATE. For example, with my [wt ChuS + haem + NADH] system (please see CHECKSPMUTATE for details), of the 1235 minima which were reoptimised, it was found that 14 of these had been overwritten.
Files Required
To find out which files had been overwritten in the first place, a sub-directory (called all_launched_simult) was created within checkmin. The following files from checkmin were copied into this new folder:
- aa_ringdata.pyc, amino_acids.pyc, atomnumberlog, coordinates_mut.pyc, coords.inpcrd, coords.mdcrd, coords.prmtop, min.A, min.B, min.data, min.in, mutate_aa.py, newreslog, nresidueslog, odata.checksp, odata (exactly the same as odata.checksp), original_protein.pdb, pathsample_checkmin.out, perm.allow, points.min, points.ts, resnumberlog, ts.data
Additionally, pre_pathdata and pre_sub_script_CUDAOPTIM files of the form:
EXEC /home/adk44/bin/CUDAOPTIM_ppt_final_210918 CPUS 1 NATOMS 5501 NATOMS_CHAIN 5357 NATOMS_NEW 5464 CHECKSP_MUT SEED 1 DIRECTION AB CONNECTIONS 1 TEMPERATURE 0.592 PLANCK 9.536D-14 DUMMYRUN PERMDIST ETOL 8D-4 GEOMDIFFTOL 0.2D0 ITOL 0.1D0 NOINVERSION NOFRQS CYCLES 1 AMBER12
and
#!/bin/bash # Request 1 TITAN Black GPU - use '--constraint=teslak20' for a Tesla or '--constraint=maxwell' to request a Maxwell GPU for single precision runs #SBATCH --constraint=titanblack #SBATCH --job-name=test_top #SBATCH --gres=gpu:2 #SBATCH --mail-type=FAIL hostname echo "Time: `date`" source /etc/profile.d/modules.sh # Load the appropriate compiler modules on the node - should be the same as those used to compile the executable on pat module add cuda/6.5 module add icc/64/2013_sp1/4/211 module add anaconda/python2/2.2.0 # Needed for python networkx module - must be python 2, not 3 # Set the GPU to exclusive process mode sudo nvidia-smi -i $CUDA_VISIBLE_DEVICES -c 3 # Run the executable in the local node scratch directory echo Finished at `date`
were included.
Before proceeding, we also required duplicates.sh, duplicates.py, duplicates2.py and reoptimise.sh, all of which can be found in /svn/SCRIPTS/CHECKSPMUTATE/all_launched_simult/minima
Execution
First, execute duplicates.sh. This generates checkminfile, a list of all of the minima which were overwritten during the original CHECKSPMUTATE run. It identifies such minima by reading pathsample_checkmin.out (i.e. the output from the CHECKSPMUTATE calculation), which gives a log of all of the random numbers each respective OPTIM job was assigned.
The script reoptimise.sh is then used to reoptimise these overwritten minima. pre_pathdata and sub_script_CUDAOPTIM are first manipulated to ensure the correct minima are reoptimised. Each reoptimisation is carried out in a sub-directory named after the index of the minimum being reoptimised.
Note on checkts
Because of slightly different requirements, make sure that the auxiliary files from /svn/SCRIPTS/CHECKSPMUTATE/all_launched_simult/TSs are used instead. Also, the file to be read in by duplicates.sh should be called pathsample_checkts.out rather than pathsample_checkmin.out.
Readmin/Readts
From checkmin/all_launched_simult, copy the following files to the readmin directory:
- checkminfile, coords.inpcrd