Prediction of binding rate of drug to human plasma protein based on heuristic method and support vector machine

The binding rate to human plasma protein for 70 diverse drugs was modeled using the descriptors calculated from the molecular structure along with a quantitative structure-activity relationship (QSAR) technique. The heuristic method (HM) and support vector machine (SVM) were utilized to construct the linear and nonlinear prediction models, leading to a good cross-validation correlation coefficient R_cv² of 0.80 and 0.82, respectively. By comparison the stability with prediction ability of the models, it was found that support vector machine was a good method for predicting the binding rate of drug to human plasma protein.