Unraveling putative antiulcer phytoconstituents against Helicobacter pylori urease and human H+/K+-ATPase from Jacaranda mimosifolia using UPLC-MS/MS coupled to chemometrics and molecular docking

[Display omitted] •Metabolomic Profiling of Jacaranda mimosifolia secondary metabolites was implemented using UPLC-MS/MS technique.•In-vitro evaluation of anti-ulcer activities via targeting urease and H+/K+-ATPase enzymes were applied.•Chemometric analysis was implemented and subsequently establishing statistical models for organs’ discrimination.•Several statistical models viz, PCA, HCA, OPLS-DA, and PLS were constructed for multivariate analysis of obtained data.•In-silico molecular docking and in-vitro biological validation studies were performed on the putative biomarkers. Globally peptic ulcer disease is a severe public health issue caused by an imbalance between the defensive and aggressive mechanisms. In the current study, the phytochemical components of various organs (leaf, fruit, seed, and bark) of Jacaranda mimosifolia D. Don collected from Egypt at different seasons and geographical locations were investigated. UPLC-MS/MS allows a tentative identification of 53 compounds where flavonoids, quinoids, and triterpenoids represented the major identified classes. Multivariate statistical analysis (principle component analysis (PCA), hierarchical cluster analysis (HCA)-heat map and orthogonal projection to latent structures-discriminate analysis (OPLS-DA), and accompanied coefficient plots) was applied to investigate in-between and within-class discrimination of the different organs of Jacaranda mimosifolia D. Don. The obtained extracts were tested for their inhibitory activities against Helicobacter pylori Urease and human H+/K+-ATPase enzymes. Fruit extract showed the highest inhibitory activity against H. pylori urease. Meanwhile, leaf extract was found to be more potent, against human H+/K+-ATPase. The results of the biological activities were further modeled using Partial Least Squares Regression (PLSR) analysis together with the quantitative data. The optimal number of latent variables was determined with the aid of Variables important for the projection (VIP) plot to remove the uninformative variables. The developed model was validated using root mean square error of calibration (RMSEC), cross-validation (RMSECV) and prediction (RMSEP). PLS model coefficient plots showed that flavonoids as isoquercitrin and rutin were the most contributing metabolites/biomarkers to the detected anti-urease and H+/K+-ATPase activities, respectively. Molecular docking analysis was utilized to gain more insights into the interaction modalities for the top fifteen