targets.yml is the index of targets used by the code
for each target directory, there is a ligands.yml that includes experimental affinity data
target.yml
See this map:
00_data, 01_protein/crd and 02_ligands/<lig>/crd must be defined; at the moment top files manually curated
PLBenchmarks/metadata.py has some validation functions for checking internal consistency of index/top files with input data
03_hybrid is generated by workflow
If there are charges in the SDF file, workflow will use those charges
DD: will consider whether we can start using openff-system for gromacs parameterization
workflow3_solvate.py can generate many numbered replicates
the outputs of these would be used for interfacing with FAH
step 4 generates inputs for SGE, SLURM, ready for energy minimization
step 5 submits to queuing system
step 6 checks simulations for some basic issues
step 7 analyzes results
could be 30mins per target, about 10 seconds per replicate edge
Existing results live in benchmarkpl:
Random components
initial velocities of atoms
placement of solvent, ions
DH: you will likely need to install git-lfs in order to clone the full PLBenchmarks repo datasets
Action items
David Dotson will attempt to reproduce existing workflow on local infrastructure
David Dotson will produce an initial design document for FAH workflow prototype; this will be the basis of iteration before investment in heavy implementation
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