Running ChemSTEP on CoreHPC

1. Source Environment

source /mnt/fac/CX900007_DS1/soft/chemstep/env.sh

2. Dock the Seed Set

Copy the .sdi file for the library you want to use into a directory containing your dockfiles:

Library	Path
22B	cp -r /mnt/fac/CX900007_DS1/work/kholland/22B_seed_building/sdi ./sdi

Then dock the seed set:

bash /mnt/fac/CX900007_DS1/soft/super_dock3r.sh

3. Gather Scores for the Seed Set

Once docking is complete, run the following from the directory one level above your docking output (MOLECULES_DIR_TO_BIND).

22B library:

python python $CHEMSTEP_INSTALL_PATH/chemstep-development/accessory/get_scores.py 0

Verify that scores_round_0.txt was correctly written:

wc -l scores_round_0.txt

4. Convert Scores to .npy Files

Convert scores to ChemSTEP-readable .npy files:

python $CHEMSTEP_INSTALL_PATH/chemstep-development/accessory/convert_scores_to_npy.py 0 CSLB

5. Set Up the ChemSTEP Run Directory

Create and enter a new run directory, then copy in the necessary files:

mkdir chemstep_run
cd chemstep_run
chemstep-run-new

This will populate the directory with params.txt, run_chemstep.py, and launch_chemstep_as_job.sh.

Optional: Integrated IFP

If running with integrated IFP for beacon selection, also run:

chemstep-run-ifp

This copies in the additional files ifp_acceptance_criteria.txt and interactions.txt.

6. Edit params.txt

Add the absolute paths to the ChemSTEP-readable score and indices .npy arrays generated in Step 4.

seed_indices_file:  /path/to/your/indices_round_0.npy
seed_scores_file:   /path/to/your/scores_round_0.npy
hit_pprop:          5.5
n_docked_per_round: 2000000
bundle_size:        1000
max_beacons:        100
max_n_rounds:       250

Parameter Reference

Parameter	Description
hit_pprop	Defines a "virtual hit." pProp = −log(rank%) within the total library score distribution. E.g., pProp 4 in 13B space ≈ top 0.01% (~1.3M molecules); pProp 5 ≈ 0.001% (~132K). The seed set should contain at least 10(pProp+2) molecules.
n_docked_per_round	Number of molecules prioritized per round. All must be built and docked between rounds. Too many slows throughput and may reduce diversity; too few slows virtual hit recovery. Recommended: 1-2 million
max_beacons	Diverse, well-scoring molecules used to guide prioritization. All molecules above the pProp threshold are candidates. Too many reduce inter-beacon diversity; too few hinder space exploration. Fewer beacons than specified may be assigned if an insufficient number of molecules clear the threshold. Recommended: 100
bundle_size	In auto docking mode, number of molecules submitted as a single build job.
max_n_rounds	No adjustment needed when running ChemSTEP prospectively as described here.

7. Edit run_chemstep.py

Note: All paths must be absolute paths.

Required Settings

Set lib_path to the library pickle for your library:

Library	Path
22B	/mnt/fac/CX900007_DS1/work/kholland/22B_fp_lib/22B_fplib.pickle

lib_path = '/full/path/to/library.pickle'

Set dockfiles_path:

dockfiles_path="/full/path/to/dockfiles"

Optional: minTD Exclusion Zone

Molecules will not be prioritized from within a specified Tanimoto distance of beacons. Comment in the relevant lines and update the value. Consider also setting enforce_n_docked_per_round = True when using this option:

min_td_search=0.5,
enforce_n_docked_per_round=True,

Optional: Integrated IFP

Only selects beacons that satisfy user-defined interaction criteria. Comment in the following lines and update the paths to the necessary files (copied in Step 5 if you ran chemstep-run-ifp):

use_IFP=True,
ifp_pdb_path='/full/path/to/rec.crg.pdb',
interactions_file='/full/path/to/interactions.txt',
ifp_acceptance_criteria_file='/full/path/to/ifp_acceptance_criteria.txt',

interactions.txt — one interaction per line, comma-separated. Format: interaction_type, residue_name_and_number. Example:

Hydrogen bond, GLY-19
Ionic, ASP-149

Supported interaction types include: Proximal, Hydrogen bond, Ionic, Cation-pi, Hydrophobic, Halogen bond, and others. See LUNA and IFP documentation for the full list.

ifp_acceptance_criteria.txt — defines the number of unsatisfied donors/acceptors/specific interactions required for a molecule to pass IFP and be considered for beacon selection. Example:

#_donors
#_acceptors
#_unstatisfied_donors == 0
#_unstatisfied_acceptors <= 4
Ionic/ASP-149 > 0

Optional: SMARTS exclusion filter

Integrated SMARTS filer can exclude problematic chemotypes from being built, docked, or selected as beacons. Multiple SMARTS patterns are tolerated. Comment in the following line in run_chemstep.py:

filter_smarts=['n1cncnc1', 'c1cccnc1[SH]']

TRIAZINES: 'n1cncnc1'

Example: AmpC on 22B with minTD=0.50, No IFP

lib_path = '/wynton/group/bks/work/shared/kholland/chemstep_auto_v04/scripts/libraries/22B/22B_fplib.pickle'
lib = load_library_from_pickle(lib_path)
algo = CSAlgo(lib, 'params.txt', 'output', 16, verbose=True,
    scheduler='sge', smi_id_prefix='CSLB',
    python_exec="/wynton/group/bks/work/shared/kholland/chemstep_auto_v04/bin/python",
    dockfiles_path="/wynton/group/bks/work/kholland/chemstep_ampc_22B/seed_docking/dockfiles",
    min_td_search=0.5,
    enforce_n_docked_per_round=True,
    #use_IFP=True,
    #ifp_pdb_path='/path/to/your/reference/rec.crg.pdb',
    #interactions_file='/path/to/your/interactions.txt',
    #ifp_acceptance_criteria_file='/path/to/your/ifp_acceptance_criteria.txt',
    docking_method="auto", track_beacon_orig=True)

8. Launch the Job

Submit the main ChemSTEP job:

sbatch launch_chemstep_as_job.sh

9. Monitor Job Status

Check job status with squeue -u USER_ID. The main job will run for up to 6 days given no errors. ChemSTEP will launch search, building, and docking jobs in successive rounds.

Note: If any building or docking subjobs hang, the main job will not proceed until those are canceled or finished. Monitor job statuses regularly and occasionally verify that docking output files (scores_round_*.txt) are being populated.