Title:COMPUTATIONAL APPROACH-BASED STRUCTURE-ACTIVITY RELATIONSHIP OF BACE1 INHIBITORS USING MONTE CARLO ALGORITHM
Author:Md Lutful Islam1, Z. A. Usmani, Gulabchand K. Gupta
Keywords:QSAR, CORAL, Monte Carlo, BACE1, Alzheimer’s disease
Abstract:In the current manuscript Monte Carlo algorithm based quantitative structure-activity relationship (QSAR) was performed on BACE1 inhibitors to find out important chemical functionalities for therapeutic application in Alzheimer’s disease (AD). The molecular descriptors were developed from simplified molecular input-line entry system (SMILES) representation of chemical structures. The dataset was collected from BindingDB and further divided into training, calibration, test and validation sets. The training set was used to develop models, whereas remaining sets were applied to evaluate the predicted ability of the models. Two models were generated based on influence and without influence of cyclic rings on the inhibitory activity. The statistical parameters of both models were analysed and found that both models are statistically robust in nature. On comparison of statistical parameters it was revealed that cyclic rings have significant impact on inhibitory activity. Different SMILES molecular attributes were found to be crucial to increase or decrease biological activity which suggest that both models have mechanistic interpretation. Therefore, understanding of the model can be directed to design and discover potential BACE1 inhibitors for the AD.