Prediction of therapeutic potency of tacrine derivatives as BuChE inhibitors from quantitative structure–activity relationship modelling
Numerous studies show that tacrine derivatives exhibit increased inhibitory activity against butyrylcholinesterase (BuChE) and acetylcholinesterase (AChE). However, the screening assays for currently available BuChE inhibitors are expensive, time consuming and dependent on the inhibitory
compound. It is therefore desirable to develop alternative methods to facilitate the screening of these derivatives in the early phase of drug discovery. In order to develop robust predictive models, three regression methods were chosen in this study: multiple linear regression (MLR), support
vector regression (SVR) and multilayer perceptron network (MLP). Eight relevant descriptors were selected on a dataset of 151 molecules using a method based on genetic algorithms. Internal and external validation strategies play an important role. Also, to check the robustness of the selected
models, all available validation strategies were used, and all criteria used to validate these models revealed the superiority of the SVR model. The statistical parameters obtained with the SVR model were RMSE = 0.197, r
2 = 0.969 and Q
2 = 0.964 for the training
set, and r
2 = 0.906 and Q
2 = 0.891 for the test set. Therefore, the model developed in this study provides an excellent prediction of the inhibitory concentration of tacrine derivatives.
Keywords: BuChE inhibitors; QSAR; multilayer perceptron network; support vector regression
Document Type: Research Article
Affiliations: Département du Génie des Procédés et Environnement, Université de Médéa, Quartier Ain D’heb, Médéa, Algeria
Publication date: 04 March 2018
- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content