There is a file of the binding pocket residues, in .pdb format, and three files contain the top 100 poses obtained in this study and listed in Table 2, all in .mol2 format.  These files are:

Binding_pocket_residues.pdb
LEDOCK_top100.mol2
SMINA_top100.mol2
VINA_top100.mol2

The 100 poses are in the order found in Table 2 of the paper, so that pose 1 in the list is for Irolapride.

The optimal way to view this material is probably using PyMol.

Load into this package the Binding_pocket_residues.pdb file.

Load in one of the .mol2 files containing the 100 drug poses.  The poses are in the same orientation as the pocket residues so they will go into their binding sites as a result.  In PyMol it is possible to run through these poses in the file order (please refer to the PyMol manual for support on this point).

Should you wish to view or obtain each of the poses in this file separately then use the following command in PyMol (using the LEDOCK_top100.mol2 file data as an example):

split_state LEDOCK_top100

All of the 100 poses will now be separated into the package, that for Irolapride being the first one and numbered 2644.  The number associated with each one is related to Column E (labelled “Key”) in the accompanying excel spreadsheet file.

You may then select any of the poses in groups or individually and save them as you wish (please refer to the PyMol manual for support on this point).

Each compound has 3 related poses, one from each docking method used in the study (ledock, smina and vina).  These are the closest matched triplet for a given compound as identified using the "avRMSD", as defined in the paper.
 
As an example:

Irolapride is the first drug in the list of the top 100.  This has a key value of 2644 and so the poses that are related to this drug from each of the mol2 files will be the first in the list and labelled with 2644.