Comparison of Two Virtual Screening Techniques for the Discovery of Novel SERCA Inhibitors

Abstract

Inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA) are valuable tools for the study of the enzyme’s physiological role. They also bear the potential of being developed into a promising new class of anti-cancer agents. Here, we describe the use of two different computational methods to virtually screen a large compound library for novel SERCA inhibitors. Using a docking-based protocol and an approach using recursive partitioning, we screened the same compound library. To test the performance of both screening methods, we took the top-ranked candidates from each screen and measured their inhibitory potencies for SERCA, using bioassays