Integrated machine learning and structural bioinformatics guided identification of novel molecular scaffolds as renin inhibitors.

Abstract

Cardiovascular diseases (CVDs) remain the leading cause of death globally, with hypertension as its critical hallmark. The Renin-Angiotensin-Aldosterone-System (RAAS) plays a central role in regulating blood pressure, highlighting its relevance for antihypertensive drug development. Despite extensive research, Aliskiren remains the only clinically approved direct renin inhibitor (DRI), underscoring the necessity for novel scaffolds with improved pharmacokinetic profiles. In this study, we employed an integrated machine learning (ML), ligand-based (LBDD), and structure-based drug design (SBDD) approach to identify and characterize new chemical scaffolds with potential renin inhibitory activity. Multiple ML models were built using various molecular descriptors, followed by extensive feature selection, and data balancing with SMOTE. To enhance model interpretability, we performed SHAP analysis on the top ML models to reveal key descriptors and substructures associated with predictions for renin inhibition. In parallel, several ligand-based pharmacophore models were constructed using the crystal structure of human renin. Maybridge library was screened using the best models resulting from both approaches, and the consensus compounds were prioritized using molecular docking to assess their inhibitory potential through the renin inhibitory assay. Molecular dynamics, along with MM/PBSA, were then employed to evaluate the structural stability and binding persistence of the screened compounds with promising activity. The predicted ADME properties and structural analysis further established the relevance of the novel scaffolds identified through our robust integrated approach. From the 12 shortlisted compounds, our study identified 4 promising hits - HTS00804, HTS05294, BTB13902, and RJC01726 with diverse piperazine and piperidine-substituted scaffolds for renin inhibition. All four hits exhibited IC50 values between 1.29 µM and 4.19 µM. Among all, HTS00804 demonstrated 53 and 73% renin inhibition in vitro at 1µM and 10 µM concentrations, respectively and can be explored as a starting scaffold for further structural optimization through medicinal chemistry efforts to design next-generation direct renin inhibitors (DRIs).