QSAR study of 1,4-dihydropyridine calcium channel antagonists based on gene expression programming

The gene expression programming, a novel machine learning algorithm, is used to develop quantitative model as a potential screening mechanism for a series of 1,4-dihydropyridine calcium channel antagonists for the first time. The heuristic method was used to search the descriptor space and select the descriptors responsible for activity. A nonlinear, six-descriptor model based on gene expression programming with mean-square errors 0.19 was set up with a predicted correlation coefficient (R2) 0.92. This paper provides a new and effective method for drug design and screening.

The log (1/IC50) for 45 1,4-dihydropyridines was modeled using the descriptors calculated from the molecular structure along with a quantitative structure–activity relationship (QSAR) technique. The heuristic method (HM) and gene expression programming (GEP) were utilized to construct the linear and nonlinear prediction models, leading to a good prediction.Figure optionsDownload as PowerPoint slide