================================== Launching Templates ================================== .. toctree:: :maxdepth: 2 PelePlatform (cluster) ------------------------- **Last Update:** 14-02-2021 **PelePlatform - v1.6.3, latest release** .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_tests #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=2 #SBATCH --mem-per-cpu=1000 module purge module load intel module load intel-oneapi module load imkl source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/envs/peleplatform-1.6.3 export SCHRODINGER="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/" export SCHRODINGER_PYTHONPATH="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/internal/lib/python2.7/site-packages" export PELE="/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/local_deps/pele_deps/boost_1_52/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -c "import pele_platform; print('Using PELEPlatform, version', pele_platform.__version__)" python -m pele_platform.main input_fast.yaml **PelePlatform - v1.6.2** .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_tests #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=2 #SBATCH --mem-per-cpu=1000 module purge module load intel module load intel-oneapi module load imkl source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/envs/peleplatform-1.6.2 export SCHRODINGER="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/" export SCHRODINGER_PYTHONPATH="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/internal/lib/python2.7/site-packages" export PELE="/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/local_deps/pele_deps/boost_1_52/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -c "import pele_platform; print('Using PELEPlatform, version', pele_platform.__version__)" python -m pele_platform.main input_fast.yaml **PelePlatform - v1.6.1** .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_tests #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=2 #SBATCH --mem-per-cpu=1000 module purge module load intel module load intel-oneapi module load imkl source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/envs/peleplatform-1.6.1 export SCHRODINGER="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/" export SCHRODINGER_PYTHONPATH="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/internal/lib/python2.7/site-packages" export PELE="/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/local_deps/pele_deps/boost_1_52/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -c "import pele_platform; print('Using PELEPlatform, version', pele_platform.__version__)" python -m pele_platform.main input_fast.yaml **PelePlatform - v1.6** .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_tests #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=5 #SBATCH --mem-per-cpu=1000 module purge module load intel-oneapi module load imkl source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/envs/peleplatform-1.6.0 export SCHRODINGER="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/" export SCHRODINGER_PYTHONPATH="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/internal/lib/python2.7/site-packages" export PELE="/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_dependencies/boost-1.66.0/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -m pele_platform.main input.yaml **PelePlatform - v1.5.1** .. code-block:: bash #!/bin/bash #SBATCH -J PELE_MPI_test #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=5 #SBATCH --mem-per-cpu=1000 # DO NOT CHANGE ########################### module purge export SCHRODINGER="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/" export SCHRODINGER_PYTHONPATH="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/internal/lib/python2.7/site-packages" export PELE="/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.6/" export LC_ALL=C; unset LANGUAGE unset PYTHONPATH module load impi/2018.1.163-iccifort-2018.1.163-GCC-6.4.0-2.28 wjelement/1.3-intel-2018a module load Crypto++/6.1.0-intel-2018a OpenBLAS/0.2.20-GCC-6.4.0-2.28 export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/local_deps/pele_deps/boost_1_52/lib:$LD_LIBRARY_PATH export PYTHONPATH="/shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/depend:$PYTHONPATH" export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml ################################################################### /shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/depend/bin/python -m pele_platform.main input.yaml PelePlatform + singularity (cluster) ------------------------------------ **Last Update:** 21-12-2021 **PelePlatform - v1.6.1 + PELE ++ Singularity v1.7.1** .. code-block:: bash #!/bin/bash #SBATCH -J peleplat #SBATCH --output=peleplat_%j.out #SBATCH --error=peleplat_%j.err #SBATCH --ntasks=5 #SBATCH --mem-per-cpu=1000 ################################################################## module purge module load OpenMPI/3.1.4-GCC-8.3.0 export PELE="/opt/PELE" export SCHRODINGER="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4" export SCHRODINGER_PYTHONPATH="/sNow/easybuild/centos/7.4.1708/Skylake/software/schrodinger2017-4/internal/lib/python2.7/site-packages" export PELE_LICENSE="/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.7.1/licenses" export SINGULARITY_BIND="$PELE_LICENSE" export PELE_MPI_PARAMS="--verbose" export SINGULARITY_EXEC="/shared/work/NBD_Utilities/PELE/PELE_Softwares/containers/pele1.7.1_release.sif" export LC_ALL=C; unset LANGUAGE source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/PELE/PELE_Softwares/PelePlatform/envs/peleplatform-1.6.1 ################################################################## python -m pele_platform.main input.yaml PelePlatform (tirant) ------------------------- **Last Update:** 17-12-2021 **PelePlatform - v1.6.2, latest release** .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_test #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=5 #SBATCH --mem-per-cpu=1000 module purge module load impi mkl module load miniconda source activate /storage/projects/cns14/Utilities/platform/envs/peleplatform-1.6.2 export SCHRODINGER="/storage/projects/cns14/Utilities/schrodinger2021-4/" export SCHRODINGER_PYTHONPATH="/storage/projects/cns14/Utilities/schrodinger2021-4/internal/lib/python3.8/site-packages" export PELE="/storage/projects/cns14/Utilities/PELE/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/storage/projects/cns14/Utilities/PELE/dependencies/boost-1.66.0/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -m pele_platform.main input.yaml **PelePlatform - v1.6.1 .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_test #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=5 #SBATCH --mem-per-cpu=1000 module purge module load impi mkl module load miniconda source activate /storage/projects/cns14/Utilities/platform/envs/peleplatform-1.6.1 export SCHRODINGER="/storage/projects/cns14/Utilities/schrodinger2021-4/" export SCHRODINGER_PYTHONPATH="/storage/projects/cns14/Utilities/schrodinger2021-4/internal/lib/python3.8/site-packages" export PELE="/storage/projects/cns14/Utilities/PELE/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/storage/projects/cns14/Utilities/PELE/dependencies/boost-1.66.0/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -m pele_platform.main input.yaml **PelePlatform - v1.6.0 .. code-block:: bash #!/bin/bash #SBATCH -J peleplat_test #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=5 #SBATCH --mem-per-cpu=1000 module purge module load impi mkl module load miniconda source activate /storage/projects/cns14/Utilities/platform/envs/peleplatform-1.6.0 export SCHRODINGER="/storage/projects/cns14/Utilities/schrodinger2021-4/" export SCHRODINGER_PYTHONPATH="/storage/projects/cns14/Utilities/schrodinger2021-4/internal/lib/python3.8/site-packages" export PELE="/storage/projects/cns14/Utilities/PELE/PELE1.7.1/" export LC_ALL=C; unset LANGUAGE export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/storage/projects/cns14/Utilities/PELE/dependencies/boost-1.66.0/lib:$LD_LIBRARY_PATH export SRUN=1 # this is to avoid having to set usesrun: true in input.yaml python -m pele_platform.main input.yaml PeleSimulationAnalysis (cluster) ------------------------------------ **Last Update:** 05-07-2021 This script allows the user to create a dispersion plot of any two metrics from a PELE simulation. A third metric can be represented with a colorbar. .. code-block:: bash # Generate plot with interactive interactive -n 1 -X # Import modules module purge module load intel-oneapi module load imkl # Set up conda source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh # Activate conda environment conda activate /shared/work/NBD_Utilities/PELE/PELE_Softwares/conda_envs/pele_analysis # Run PELEPlot.py python -m PELEPlot.run -i output/0/report_* -X 7 -Y 5 # Or call its helper python -m PELEPlot.run --help .. code-block:: none #Generate plot with interactive interactive -n 1 -X export PYTHONPATH=/work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2015_GNU/AdaptivePELE_1.5.1 module load Python/2.7.10-foss-2015a python /work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2015_GNU/AdaptivePELE_1.5.1/AdaptivePELE/analysis/interactivePlot.py 5 6 8 --top topology.pdb --cpus 15 --min_clustsize 5 (5 6) columns in run_report that will be plotted, starting by 1 (8) number of adaptive steps (--top topology.pdb) if working with .xtc format instead of .pdb #Clustering of all the trajectories and selection of centroid representative module load Python/2.7.10-foss-2015a export PYTHONPATH=/work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2015_GNU/AdaptivePELE_1.5.1/ #If using xtc python -m AdaptivePELE.analysis.clusterAdaptiveRun 200 5 6 STR --traj trajectory_ --report report_ --top topology.pdb --CA --cpus 50 #If using pdb python -m AdaptivePELE.analysis.clusterAdaptiveRun 200 5 6 STR --traj trajectory_ --report report_ --CA --cpus 50 (200) number of clusters - decide based on plot Output: ClusterMap.pdf --use_pdb (only in case of having pdb files with .xtc extension) #Generate movie of a selected trajectory: interactive -n 1 -X module load Python/2.7.14-intel-2018a export PYTHONPATH=/work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2_intel/AdaptivePELE_1.5.1/ python /work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2015_GNU/AdaptivePELE_1.5.1/AdaptivePELE/analysis/backtrackAdaptiveTrajectory.py 5 123 1 (5) epoch (123) trajectory number (2) snapshot #Genenerate n bestStructures from a metric interactive -n 1 -X module load Python/2.7.14-intel-2018a export PYTHONPATH=/work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2_intel/AdaptivePELE_1.5.1/ python /work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2015_GNU/AdaptivePELE_1.5.1/AdaptivePELE/analysis/backtrackAdaptiveTrajectory.py COM Distance -n 50 #Plot with Gnuplot export PYTHONPATH=/work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2_intel/AdaptivePELE_1.5.1/ module load Python/2.7.14-intel-2018a python /work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2_intel/AdaptivePELE_1.5.1/AdaptivePELE/analysis/plotAdaptive.py 8 5 6 run_report_ -points -zcol 4 | gnuplot -p python /work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2_intel/AdaptivePELE_1.5.1/AdaptivePELE/analysis/plotAdaptive.py 8 5 6 run_report_ -points -traj_col | gnuplot -p # Normal PELE export PYTHONPATH=/work/NBD_Utilities/PELE/PELE_Softwares/adaptive_types/adaptive_python_2_intel/AdaptivePELE_1.5.1/ gnuplot plot for [i=1:X] 'run_report_'.i.'' using 5:6 title ''.i.'' (X=number of processors in PELE) .. code-block:: bash $ #Path: $ /shared/work/NBD_Utilities/PELE/PELE_Templates/analisis.sl Launch with: Copy and paste the analysis part you want to run to commandline Pele++ (cluster) ------------------------------------ **Last Update:** 09-06-2021 **PELE-1.7.1** .. code-block:: bash #!/bin/bash #SBATCH -J PELE_MPI #SBATCH --output=mpi_%j.out #SBATCH --error=mpi_%j.err #SBATCH --ntasks=5 # Change this value to match CPUs in mpi run --ntasks=XXX #SBATCH --mem-per-cpu=1000 ################################################################## module purge export LC_ALL=C; unset LANGUAGE module load intel-oneapi module load imkl export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_dependencies/boost-1.66.0/lib:$LD_LIBRARY_PATH export PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.7.1/bin:$PATH module list ################################################################## #CHOOSE NUMBER OF PROCESSORS TO USE i.e. XXX = 5 #srun -n XXX Pele_mpi pele.conf srun -n 5 Pele_mpi pele.conf .. code-block:: bash $ # Path: $ /shared/work/NBD_Utilities/PELE/PELE_Templates/PELE_mpi/run_pele-1.7.1_nbd.sl Launch with: `sbatch run_pele-1.7.1_nbd.sl` **PELE-1.6** .. code-block:: bash #!/bin/bash #SBATCH -J PELE_MPI #SBATCH --output=mpi_%j.out #SBATCH --error=mpi_%j.err #SBATCH --ntasks=5 # Change this value to match CPUs in mpi run --ntasks=XXX #SBATCH --mem-per-cpu=1000 ################################################################## module purge export LC_ALL=C; unset LANGUAGE module load impi/2018.1.163-iccifort-2018.1.163-GCC-6.4.0-2.28 wjelement/1.3-intel-2018a module load Crypto++/6.1.0-intel-2018a OpenBLAS/0.2.20-GCC-6.4.0-2.28 export I_MPI_PMI_LIBRARY=/usr/lib64/libpmi.so export LD_LIBRARY_PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/local_deps/pele_deps/boost_1_52/lib:$LD_LIBRARY_PATH export PATH=/shared/work/NBD_Utilities/PELE/PELE_Softwares/bin/PELE1.6/bin:$PATH module list ################################################################## #CHOOSE NUMBER OF PROCESSORS TO USE i.e. XXX = 5 #srun -n XXX Pele_mpi pele.conf srun -n 5 Pele_mpi pele.conf .. code-block:: bash $ # Path: $ /shared/work/NBD_Utilities/PELE/PELE_Templates/PELE_mpi/run_pele-1.6_nbd.sl Launch with: `sbatch run_pele-1.6_nbd.sl` AI Environment (cluster) ------------------------- **Last Update:** 02-03-2022 .. code-block:: bash #!/bin/bash #SBATCH -J ai_env #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=2 #SBATCH --mem-per-cpu=1000 module purge source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/conda_envs/aienv python ai_script.py AnalogsSearch (Office) --------------------------- **Last Update:** 19-03-2020 .. code-block:: bash #Read the docs for more info in the possible searches and commands: # https://danielsoler93.github.io/analogs_finder/ export PYTHONPATH=/data/software/python_scripts/analogs_finder/v1.1/ python -m analogs_finder.main database.sd query.sdf --combi_subsearch .. code-block:: bash $ # Path: $ /shared/data-nbdcalc01/software/python_scripts/analogs_finder/analogs.shi Launch with: `bash analogs.sh` MDPocket (Office) -------------------- **Last Update:** 02-01-2020 .. code-block:: none README MDpocket SUWIPA April 4, 2019. 1. Cpptraj to extract snapshots from the autoimage & stripwater trajectory ##### parm ../run1_stripwatmembrane.top trajin ../run1_trajautoimage_md14-md19_pro450ns_stripwater.x 1 45000 10 reference ../initial_stripwatmembrane.crd rms reference :1-296@CA,C,N,O trajout snapshots/snap.pdb pdb multi go ##### Noted !! use multi command to save pdb into seperate files. 2. To convert snap.pdb.# to snap_#.pdb under directory snapshots run command: ls | cut -f3 -d"." | awk '{print "mv snap.pdb."$0" snap_"$0".pdb"}' | sh 3. use python script to create mdpocket input file (containing all snap_#.pdb files) python createMDPocketInputFile.py /home/ssaenoon/Alm_Par/MD_PAR2/AMBERMD/cutNter/run1/Analysis/MDpocket/snapshots mdpocket_input.txt 4. Run MDpocket using fpoket V2: /dist/fpocket/fpocket2/bin/mdpocket -L mdpocket_input.txt 5. Visulize the density grid (output "mdpout_dens_grid.dx" in VMD) - adjusting the isovalue for your selected pocket to be separated. 6. Use this python script to extract the selected_mdpoket_iso#.pdb usage: python extractISOPdb.py path/my_dx_file.dx outputname.pdb isovalue example: python extractISOPdb.py mdpout_dens_grid.dx mdpout_dens_iso3.pdb 3 7. In PYMOL: open file "mdpout_dens_iso3.pdb" in mode - selecting "molecule" --> select your selected pocket then save > Export Molecule > Swlwct "sele" > save file.pdb eg. mdpocket_selected_pocket_iso3.pdb 8. Then run /dist/fpocket/fpocket2/bin/mdpocket -L mdpocket_input.txt -f mdpocket_selected_pocket_iso3.pdb -v 10000 9. In the output file "mdpout_descriptors.txt" containing many columns, use: > awk '{print $1}' mdpout_descriptors.txt > snapshot.txt > awk '{print $2}' mdpout_descriptors.txt > volume.txt ... paste snapshot.txt volume.txt > snapshot_volume.txt .. code-block:: bash $ # Path: $ /shared/data-nbdcalc01/software/MDpocket/mdpocket_readme_suwipa/README_MDpocket Launch with: Follow instructions and copy paste to command line CAVIAR (cluster) ---------------- **Last Update:** 08-07-2021 .. code-block:: bash #!/bin/bash #SBATCH -J caviar #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=1 #SBATCH --mem-per-cpu=1000 module purge module load intel-oneapi module load imkl source /shared/work/NBD_Utilities/miniconda3/etc/profile.d/conda.sh conda activate /shared/work/NBD_Utilities/miniconda3/envs/caviar caviar -code 1dwc PSI4 (cluster) -------------- **Last Update:** 15-11-2021 .. code-block:: bash #!/bin/bash #SBATCH -J PSI4 #SBATCH --output=report_%j.out #SBATCH --error=report_%j.err #SBATCH --ntasks=16 #SBATCH --time=1:00:00 module purge source /shared/work/NBD_Utilities/PSI4/psi4conda/etc/profile.d/conda.sh conda activate psi4 -i input.in -o output.dat -n $SLURM_NPROCS