QSAR and Docking Based Screeningof Pyrrolidine Derivatives as Matrix Metalloproteinase-2 Inhibitors

Introduction Cancer remains a leading global health challenge, with drug resistance, toxicity, and economic burden limiting the effectiveness of existing therapies. Matrix metalloproteinase-2 (MMP-2), a key gelatinase involved in extracellular matrix (ECM) degradation, plays a crucial role in cancer metastasis and represents a promising target for anticancer drug development. Materials and Methods This study focuses on designing novel MMP-2 inhibitors by employing a comprehensive 2D-Quantitative Structure-Activity Relationship (2D-QSAR) analysis of 71 pyrrolidine derivatives with reported anticancer activity. Docking studies using Autodock Vina software were performed, followed by ADMET analysis using the SwissADME server. Results A robust QSAR model was developed using multiple linear regression (MLR) analysis, demonstrating high reliability, statistical significance, and predictive accuracy ( r = 0.918, r 2 cv = 0.842, r 2 pred = 0.798). Discussion Based on QSAR insights, new pyrrolidine derivatives were designed, and their anticancer potential was evaluated through molecular docking studies against MMP-2 (PDB ID: 1HOV). ADMET analysis revealed favorable pharmacokinetic and toxicity profiles for all of the designed compounds. Docking studies showed strong binding affinities, highlighting the potential of these compounds as selective and potent MMP-2 inhibitors. Conclusion An integrative approach using QSAR modeling, molecular docking, and ADMET analysis provides a valuable framework for designing effective anticancer agents targeting MMP-2.