SVR-CKNN Applied in QSAR Model of HIV-1 Protease Inhibitors

In order to improve the predication precision of quantitative structure-activity relationship(QSAR) model,a novel combinatorial k-nearest neighbor method based on support vector machine regression(SVR-CKNN) was proposed,which could screen descriptors automatically and then builds several k-nearest neighbor models for combinatorial forecast.This model applied to data of 49 HIV-1 protease inhibitors,and it was then tested by jackknife method.The result showed new model was more precise than traditional,as it had the advantages in strong generalization ability,fitting small simples and independent on user's experience.The novel combination model,therefore,are broad prospect of application in QSAR for drug design.