Integrating docking scores, interaction profiles and molecular descriptors to improve the accuracy of molecular docking: toward the discovery of novel Akt1 inhibitors

Abstract

A set of forty-seven Akt1 inhibitors was used for the development of molecular docking based QSAR model by using nonlinear regression. The integration of docking scores, key interaction profiles and molecular descriptors remarkably improved the accuracy of the QSAR models, providing reasonable statistical parameters (Rtrain(2) = 0.948, Rtest(2) = 0.907 and Qcv(2) = 0.794). The established MD-SVR model based structural modification of new 4-amino-pyrimidine derivatives was further performed, and six compounds 56a,b and 60a-d with good prediction activities were synthesized and biologically evaluated. All of these compounds exhibited promising Akt1 inhibitory and antiproliferative activities, suggesting the reliability and good application value of the established MD-SVR model in the development of Akt1 inhibitors.

Keywords: Akt1 inhibitors; Antiproliferative activity; Molecular docking; Support vector regression (SVR); Synthesis.