Introduction: Alzheimer’s Disease (AD) is a progressive neurological condition that causes a gradual loss of memory and cognitive abilities, primarily caused by neuronal dysfunction and cell death. Recently, Computer-Aided Drug Design (CADD) has become a powerful tool for accelerating the discovery of novel therapeutic agents targeting complex diseases such as AD Materials and Methods: In this study, a series of indoylpropyl benzamidopiperazine derivatives was systematically optimized using both two-dimensional (2D) and three-dimensional quantitative structure-activity relationships. QSAR models were developed and validated using QSARINS and Schrödinger software suites. Molecular descriptors were tested using Multiple Linear Regression (MLR) for 2D QSAR and genetic algorithm (GA)-based methods for 3D QSAR modelling. The developed models were validated via internal and external validation techniques to ensure robustness and predictive reliability. Using QSAR, 149 new analogues targeting acetylcholinesterase (AChE) and serotonin transporter (SERT) were designed. These analogues were further tested through virtual screening, ADMET profiling, and molecular docking studies against AChE and SERT targets. Results: QSAR modeling and docking studies indicate that compound 75 is the most promising dual AChE/SERT inhibitor, with strong predicted biological activity and favorable pharmacokinetic and ADMET properties. Discussion: The built QSAR models were statistically quite accurate, as shown by correlation coefficients of R² = 0.8850 for the 2D QSAR model and R² = 0.8597 for the 3D QSAR model. Six of the designed counterparts had superior expected activity and satisfactory ADMET profiles. Six of the designed analogues exhibited better predicted activity and acceptable ADMET profiles. Molecular docking investigations confirmed these findings, identifying compound 75 as the most potent dual inhibitor due to its high binding affinity and several stabilising contacts within the active sites of AChE and SERT. Conclusion: This study effectively established reliable and predictive 2D and 3D QSAR models for indoylpropyl benzamidopiperazine derivatives, providing valuable insights into the structural features governing biological activity. The combination of QSAR-based design and molecular docking enabled the identification of promising multitarget lead candidates, particularly compound 75, which has potential for further development as a therapeutic agent for Alzheimer’s disease.
Patil et al. (Mon,) studied this question.