Three-dimensional pharmacophore hypothesis was established based on a set of 
known DPP-IV inhibitor using PharmaGist software program understanding the 
essential structural features for DPP-IV inhibitor. The various marketed or 
under developmental status, potential gliptins have been opted to build a 
pharmacophore model, e.g. Sitagliptin (MK- 0431), Saxagliptin, Melogliptin, 
Linagliptin (BI-1356), Dutogliptin, Carmegliptin, Alogliptin and Vildagliptin 
(LAF237). PharmaGist web based program is employed for pharmacophore 
development. Four points pharmacophore with the hydrogen bond acceptor (A), 
hydrophobic group (H), Spatial Features and aromatic rings (R) have been 
considered to develop pharmacophoric features by PharmaGist program. The best 
pharmacophore model bearing the Score 16.971, has been opted to screen on 
ZincPharmer database to derive the novel potential anti-diabetic ligands. The 
best pharmacophore bear various Pharmacophore features, including General 
Features 3, Spatial Features 1, Aromatic 1 and Acceptors 2. The PharmaGist 
employed algorithm to identify the best pharmacophores by computing multiple 
flexible alignments between the input ligands. The multiple alignments are 
generated by combining alignments pair-wise between one of the gliptin input 
ligands, which acts as pivot and the other gliptin as ligand. The resulting 
multiple alignments reveal spatial arrangements of consensus features shared by 
different subsets of input ligands. The best pharmacophore model has been 
derived using both pair-wise and multiple alignment methods, which have been 
weighted in Pharmacophore Generation process. The highest-scoring pharmacophore 
model has been selected as potential pharmacophore model. In conclusion, 3D 
structure search has been performed on the "ZincPharmer Database" to identify 
potential compounds that have been matched with the proposed pharmacophoric 
features. The 3D ZincPharmer Database has been matched with various thousands of 
Ligands hits. Those matches were screened through the RMSD and max hits per 
molecule. The physicochemical properties of various "ZincPharmer Database" 
screened ligands have been calculated by PaDELDescriptor software. The all 
"ZincPharmer Database" screened ligands have been filtered based on the 
Lipinski's rule-of-five criteria (i.e. Molecular Weight < 500, H-bond acceptor ≤ 
10, H-bond donor ≤ 5, Log P ≤ 5) and were subjected to molecular docking studies 
to get the potential antidiabetic ligands. We have found various substituted as 
potential antidiabetic ligands, which can be used for further development of 
antidiabetic agents. In the present research work, we have covered rational of 
DPP-IV inhibitor based on Ligand-Based Pharmacophore detection, which is 
validated via the Docking interaction studies as well as Maximal Common 
Substructure (MCS).