Xanthine-based molecules such as serine protease dipeptidyl peptidase 4 (DPP4) inhibitors are compounds often used in improving glycemic control in type 2 diabetic patients and also used for their effects as mild stimulants and as bronchodilators, notably in treating asthma symptoms. Here, we aim to better understand the molecular features affecting activity of xanthine-based DPP4 inhibitors such as sitagliptin and related compounds and use these features to de novo predict improved sitagliptin derivatives. To this end, we performed a clinical study to examine the efficacy and safety of once-daily 100 mg oral sitagliptin as monotherapy in Romanian patients with type 2 diabetes. This study indicates that sitagliptin effectively decreases the glycemic level and provides very good glycemic equilibrium. To predict putative new drugs with identical pharmacological effects at lower dosages, we generate QSAR models based on compound series containing 35 DPP4 inhibitors. We establish that the physicochemical parameters critical for DPP4 inhibitory activity are: hydrophobicity described by the logarithm of the octanol/water partition coefficient, counts of rotatable bonds, hydrogen bond donor and acceptor atoms, and topological polar surface area. The predictive power of our QSAR models is indicated by significant values of statistical coefficients: cross-validated correlation q2 (0.77), fitted correlation coefficient r2 (0.85) and standard error of prediction (0.34). Based on the established QSAR equations, we propose and analyse 19 new sitagliptin derivatives with possibly improved pharmacological effect as DPP4 inhibitors.