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.