Designing of xanthine-based DPP-4 inhibitors: a structure-guided alignment dependent Multifacet 3D-QSAR modeling, and molecular dynamics simulation study

The DPP-4 enzyme degrades incretin hormones GLP-1 and GIP. DPP-4 inhibitors are found effective in the prevention of the degradation of incretins. Xanthine scaffold-bearing molecules are reported as potential DPP-4 inhibitors for treating type 2 diabetes mellitus, e.g. the marketed drug linagliptin. In this work, structure-guided alignment-dependent atom- and Gaussian field-based 3D-QSAR have been performed on a dataset of 75 molecules. The robustness and predictive ability of the developed multifacet 3D-QSAR models were validated on different statistical parameters and found to be statistically fit. The favorable and unfavorable pharmacophoric features were mapped for each multifacet 3D-QSAR model based on three alignment sets (1–3). A five-point common pharmacophore hypothesis was generated separately for each set of alignments. The molecular dynamics simulations (up to 100 ns) were performed for the potent molecule from each alignment set (Compounds 12, 40 and 57) compared to reference standard linagliptin to study the binding energy and stability of target-ligand complexes. The MM-PBSA calculations revealed that the binding free energy and stability of compounds 12 (−40.324 ± 17.876 kJ/mol), 40 (−80.543 ± 21.782 kJ/mol) and 57 (−50.202 ± 16.055 kJ/mol) were better than the reference drug linagliptin (−20.390 ± 63.200 kJ/mol). The generated contour maps from structure-guided alignment-dependent multifacet 3D-QSAR models offer information about the structure–activity relationship (SAR) and ligand-target binding energy and stability data from MD simulation may be utilized to design and develop target selective xanthine-based novel DPP-4 inhibitors.