POSIT tutorial¶
Given receptors, using POSIT is very straightforward. There are two basic ways to input molecules to POSIT.
-in
- converts input to 3D conformers ( if 3D structures are input, these initial structures are retained )
-dbase
- takes the input conformations as is (these are normally generated with OMEGA.
For usage of -dbase
see POSIT MPI Tutorial.
Given a set of input smiles strings:
> posit -receptor renin/receptors/*.oedu renin/merged/*.oedu -in renin/all.smi
Note
On Microsoft Windows systems, you need to expand the wildcard:
> posit -receptor renin\receptors\2IL2_rec.oedu renin\receptors\2IKU_rec.oedu \ renin\receptors\2IKO_rec.oedu reninmerged\combine_receptors_2IKO_rec_merged_2IKU_rec.oedu \ renin\merged\combine_receptors_2IKU_rec_merged_2IKO_rec.oedu -in renin\all.smi
The following files are output:
posit_docked.oedu
- contains all successful poses
posit_score.txt
- contains the scores of all successful poses
posit_report.txt
- contains the report of the run
posit_status.txt
- a periodic status file generated during a run
posit_settings.param
- parameters used in the run
The following files are output only if non-empty:
posit_clashed.oeb.gz
- contains all poses with good enough probability but clash
posit_undocked.oeb.gz
- contains all unsuccessful poses
There is more than one reason a pose may be unsuccessful. The
most common is that the probability of the predicted binding mode is
too low. To control this behavior use the posit -outputall
flag, which
writes all output to the file specified by -out
in order
of input molecule.
POSIT by default writes docked structure results to .oedu
file which can be viewed using VIDA 5. If an
.oeb
or .oeb.gz
file is desired use the hybrid -docked_molecule_file
flag.
To specify the -prefix option to add a prefix to all files output by POSIT or use the -docked_molecule_file option to output a pose file with particular name.
When POSIT is finished, it prints the final status and indicates what new data was added to the results that are output:
> posit -receptor renin/receptors/*.oedu -in renin/all.smi \ -prefix renin Sorting by input order --------Finished docking-------- Run time : 3m 46s (226.5seconds total) Time per molecule 20.59sec Molecules processed : 11 Molecules successfully docked : 7 Unsuccessful dockings : 4 Dock Statistics Count ---------------------- ----- Successfully Docked 7 Clashed with protein 4 Docked molecules outputted to renin_docked.oedu Docked (but clashing) molecules outputted to renin_clashed.oeb.gz Failed molecules written to: renin_undocked.oeb.gz Failed molecules log written to: renin_rejected.txt Scores are written to : renin_score.txt POSIT report was saved to file : renin_report.txt Finished
The following files are output by the command above:
renin_docked.oedu
- the successfully docked structures
renin_clashed.oeb.gz
- clashing poses with good probability
renin_undocked.oeb.gz
- all non docked structures
renin_score.txt
- scores of docked structures
renin_rejected.txt
- list of rejected structures and status of rejection
renin_report.txt
- report as seen above
renin_status.txt
- current status of run, number of molecules processed and so on.
renin_settings.param
- parameter file used for run
The score file contains the scores and ranking of docked structures (some contents have been removed for brevity):
Title
POSIT::Probability
POSIT receptor title
POSIT receptor name
POSIT::Method
Result
ren1
0.950000
2IKO(ABCDEF)sym1altA
2IKO_rec.oedu
SHAPEFIT
GREAT
ren2
0.890000
2IKU(ABCDEF)altA
2IKU_rec.oedu
SHAPEFIT
GREAT
ren3
0.950000
2IKU(ABCDEF)altA
2IKU_rec.oedu
SHAPEFIT
GREAT
ren5
0.790000
2IKU(ABCDEF)altA
2IKU_rec.oedu
SHAPEFIT
GREAT
ren8b
0.790000
2IKU(ABCDEF)altA
2IKU_rec.oedu
SHAPEFIT
GREAT
ren10
0.910000
2IL2(ABCDEF)altA
2IL2_rec.oedu
SHAPEFIT
GREAT
ren11
0.910000
2IL2(ABCDEF)altA
2IL2_rec.oedu
SHAPEFIT
GREAT
The rejected file can be used to identify the status of rejected molecules, for instance “All conformers clashed with protein” indicates that while the probability was good, the protein could not accept the desired pose:
Ligand#
Title
Status
3
ren4
Clashed with protein
5
ren6
Clashed with protein
6
ren7a
Clashed with protein
8
ren9
Clashed with protein
Note
While POSIT can take most molecule formats as input, with large datasets it is fastest to use a pre-generated database of OMEGA [Hawkins-2010] generated conformers. It is recommended, above two rotatable bonds, to generate 100 conformers per rotatable bond when running OMEGA:
> omega2 -in renin/all.smi -out all.oeb.gz -rangeIncrement 1 \ -maxConfRange 200,200,300,400,500,600,700,800,900,1000,1100,1200,1300,1400,1500,1600 > posit -receptor renin/receptors/*.oedu -dbase all.oeb.gz \ -prefix renin
See the posit usage section for more details.
POSIT MPI tutorial¶
Running POSIT on multiple cores is a simple matter
of adding the -mpi_np
argument and specifying the number
of cores desired. When POSIT is run on
a small job as shown above (with 11 molecules and 6) receptors,
using a large number of cores is overkill.
> posit -mpi_np 3 -receptor renin/receptors/*.oedu -dbase all.oeb.gz \ -prefix renin

POSIT performance varying the number of cores against a small lead-optimization example.¶
As seen in figure Posit Performance, running with 3 cores gives a large boost in the run-time and adding another is only marginally faster. Note that running under two cores is not recommended as one core is always the master so, in effect, this is the slowest way to run POSIT.
Also note that using OMEGA conformations as input is the fastest way to run POSIT.